Skip to main content

Center for Artificial Intelligence and Modeling

To view the full list of publications across IGB's research portfolio, please visit our Illinois Experts page

2024

Widener, S., Njuguna, J. N., Clark, L. V., Anzoua, K. G., Bagmet, L., Chebukin, P., Dwiyanti, M. S., Dzyubenko, E., Dzyubenko, N., Ghimire, B. K., Jin, X., Jørgensen, U., Kjeldsen, J. B., Nagano, H., Peng, J., Petersen, K. K., Sabitov, A., Seong, E. S., Yamada, T., ... Lipka, A. E. (2024). Genotype by environment model predictive ability in Miscanthus. GCB Bioenergy, 16(1), Article e13113. https://doi.org/10.1111/gcbb.13113

Weber, L. L., Reiman, D., Roddur, M. S., Qi, Y., El-Kebir, M., & Khan, A. A. (2024). TRIBAL: Tree Inference of B Cell Clonal Lineages. In J. Ma (Ed.), Research in Computational Molecular Biology - 28th Annual International Conference, RECOMB 2024, Proceedings (pp. 364-367). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14758 LNCS). Springer. https://doi.org/10.1007/978-1-0716-3989-4_32

Weber, L. L., Reiman, D., Roddur, M. S., Qi, Y., El-Kebir, M., & Khan, A. A. (2024). Isotype-aware inference of B cell clonal lineage trees from single-cell sequencing data. Cell Genomics, 4(9), Article 100637. https://doi.org/10.1016/j.xgen.2024.100637

Umarani, M. S., Wang, D., O’dwyer, J. P., & D’andrea, R. (2024). A Spatial Signal of Niche Differentiation in Tropical Forests. American Naturalist, 203(4), 445-457. https://doi.org/10.1086/729218

Tuggle, C. K., Clarke, J. L., Murdoch, B. M., Lyons, E., Scott, N. M., Beneš, B., Campbell, J. D., Chung, H., Daigle, C. L., Das Choudhury, S., Dekkers, J. C. M., Dórea, J. R. R., Ertl, D. S., Feldman, M., Fragomeni, B. O., Fulton, J. E., Guadagno, C. R., Hagen, D. E., Hess, A. S., ... Schnable, P. S. (2024). Current challenges and future of agricultural genomes to phenomes in the USA. Genome biology, 25(1), Article 8. https://doi.org/10.1186/s13059-023-03155-w

Tkachenko, A. V., & Maslov, S. (2024). Emergence of catalytic function in prebiotic information-coding polymers. eLife, 12, Article RP91397. https://doi.org/10.7554/eLife.91397

Sutton, N. M., Suski, C., Payne, K., & O'dwyer, J. P. (2024). Moving beyond the mean: an analysis of faecal corticosterone metabolites shows substantial variability both within and across white-tailed deer populations. Conservation Physiology, 12(1), Article coae062. https://doi.org/10.1093/conphys/coae062

Subramanian, V., Syeda-Mahmood, T., & Do, M. N. (2024). Modelling-based joint embedding of histology and genomics using canonical correlation analysis for breast cancer survival prediction. Artificial Intelligence in Medicine, 149, Article 102787. https://doi.org/10.1016/j.artmed.2024.102787

Sima, J., Wu, C., Milenkovic, O., & Szpankowski, W. (2024). Online Distribution Learning with Local Privacy Constraints. Proceedings of Machine Learning Research, 238, 460-468.

Sickle, J. J., Higgins, W. H., Wright, W. J., Pharr, G. M., & Dahmen, K. A. (2024). A novel method may reveal bulk metallic glass compressive ductility trends in high data rate nanoindentation. Journal of Applied Physics, 135(21), Article 215104. https://doi.org/10.1063/5.0200416

Sickle, J. J., Mook, W. M., DelRio, F. W., Ilgen, A. G., Wright, W. J., & Dahmen, K. A. (2024). Quantifying chemomechanical weakening in muscovite mica with a simple micromechanical model. Nature communications, 15(1), Article 9552. https://doi.org/10.1038/s41467-024-53213-5

Shinn, L. M., Mansharamani, A., Baer, D. J., Novotny, J. A., Charron, C. S., Khan, N. A., Zhu, R., & Holscher, H. D. (2024). Fecal Metagenomics to Identify Biomarkers of Food Intake in Healthy Adults: Findings from Randomized, Controlled, Nutrition Trials. Journal of Nutrition, 154(1), 271-283. https://doi.org/10.1016/j.tjnut.2023.11.001

Salners, T., Dahmen, K. A., & Beggs, J. (2024). Simple model for the prediction of seizure durations. Physical Review E, 110(1), Article 014401. https://doi.org/10.1103/PhysRevE.110.014401

Rosok, L. M., Cannavale, C. N., Keye, S. A., Holscher, H. D., Renzi-Hammond, L., & Khan, N. A. (in press). Skin and macular carotenoids and relations to academic achievement among school-aged children. Nutritional Neuroscience. https://doi.org/10.1080/1028415X.2024.2370175

Roddur, M. S., Snir, S., & El-Kebir, M. (in press). Enforcing Temporal Consistency in Migration History Inference. Journal of Computational Biology. https://doi.org/10.1089/cmb.2023.0352

Rana, V., Peng, J., Pan, C., Lyu, H., Cheng, A., Kim, M., & Milenkovic, O. (2024). Interpretable online network dictionary learning for inferring long-range chromatin interactions. PLoS computational biology, 20(5 MAY), Article e1012095. https://doi.org/10.1371/journal.pcbi.1012095

Qi, Y., & El-Kebir, M. (2024). Consensus Tree Under the Ancestor–Descendant Distance is NP-Hard. Journal of Computational Biology, 31(1), 58-70. https://doi.org/10.1089/cmb.2023.0262

Qi, Y., & El-Kebir, M. (2024). Sapling: Inferring and Summarizing Tumor Phylogenies from Bulk Data Using Backbone Trees. In S. P. Pissis, & W.-K. Sung (Eds.), 24th International Workshop on Algorithms in Bioinformatics, WABI 2024 Article 7 (Leibniz International Proceedings in Informatics, LIPIcs; Vol. 312). Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.WABI.2024.7

Pountain, A. W., Jiang, P., Yao, T., Homaee, E., Guan, Y., McDonald, K. J. C., Podkowik, M., Shopsin, B., Torres, V. J., Golding, I., & Yanai, I. (2024). Transcription–replication interactions reveal bacterial genome regulation. Nature, 626(7999), 661-669. https://doi.org/10.1038/s41586-023-06974-w

O’Dwyer, J., Chisholm, R., & D’Andrea, R. (2024). Neutral Ecology and Beyond. In Encyclopedia of Biodiversity, Third Edition: Volume 1-7 (pp. V5-1-V5-12). Elsevier. https://doi.org/10.1016/B978-0-12-822562-2.00019-0

Nguyen, Q., Pham, H. H., Wong, K. S., Le Nguyen, P., Nguyen, T. T., & Do, M. N. (2024). FedDCT: Federated Learning of Large Convolutional Neural Networks on Resource-Constrained Devices Using Divide and Collaborative Training. IEEE Transactions on Network and Service Management, 21(1), 418-436. https://doi.org/10.1109/TNSM.2023.3314066

Nguyen, T. V. P., Wu, Y., Yao, T., Trinh, J. T., Zeng, L., Chemla, Y. R., & Golding, I. (2024). Coinfecting phages impede each other's entry into the cell. Current Biology, 34(13), 2841-2853.e18. https://doi.org/10.1016/j.cub.2024.05.032

Nambiar, A., Pan, C., Rana, V., Cheraghchi, M., Ribeiro, J., Maslov, S., & Milenkovic, O. (2024). Semi-quantitative group testing for efficient and accurate qPCR screening of pathogens with a wide range of loads. BMC bioinformatics, 25(1), Article 195. https://doi.org/10.1186/s12859-024-05798-3

Nambiar, A., Forsyth, J. M., Liu, S., & Maslov, S. (2024). DR-BERT: A protein language model to annotate disordered regions. Structure, 32(8), 1260-1268.e3. https://doi.org/10.1016/j.str.2024.04.010

Mysonhimer, A. R., Brown, M. D., Alvarado, D. A., Cornman, E., Esmail, M., Abdiel, T., Gutierrez, K., Vasquez, J., Cannavale, C. N., Miller, M. J., Khan, N. A., & Holscher, H. D. (2024). Honey Added to Yogurt with Bifidobacterium animalis subsp. lactis DN-173 010/CNCM I-2494 Supports Probiotic Enrichment but Does Not Reduce Intestinal Transit Time in Healthy Adults: A Randomized, Controlled, Crossover Trial. Journal of Nutrition, 154(8), 2396-2410. https://doi.org/10.1016/j.tjnut.2024.05.028

Moustakides, G. V., Liu, X., & Milenkovic, O. (2024). Optimal stopping methodology for the secretary problem with random queries. Journal of Applied Probability, 61(2), 578-602. https://doi.org/10.1017/jpr.2023.61

Monaco, M. H., Coyne, S., Wang, M., Flaws, J. A., Irudayaraj, J. M., Cann, I., & Donovan, S. M. (2024). Effects of early life exposure to di(2-ethylhexyl) phthalate on jejunal morphology, sucrase activity, and colonic microbiota composition in young pigs. Journal of Environmental Exposure Assessment, 3(3), Article 18. https://doi.org/10.20517/jeea.2024.10

Milenkovic, O., & Pan, C. (2024). DNA-Based Data Storage Systems: A Review of Implementations and Code Constructions. IEEE Transactions on Communications, 72(7), 3803-3828. https://doi.org/10.1109/TCOMM.2024.3367748

Mia, M. S., Abdelmeguid, M., Harris, R. A., & Elbanna, A. E. (2024). Rupture Jumping and Seismic Complexity in Models of Earthquake Cycles for Fault Stepovers with Off-Fault Plasticity. Bulletin of the Seismological Society of America, 114(3), 1466-1480. https://doi.org/10.1785/0120230249

McMath, A., Khan, N. A., Sutkus, L. T., Golden, R. K., Joung, S., Dilger, R. N., & Donovan, S. M. (2024). Pediatric Nutrition: Implications for the Developing Microbiota–Gut–Brain Axis. In N. Hyland, & C. Stanton (Eds.), The Gut-Brain Axis: Dietary, Probiotic, and Prebiotic Interventions on the Microbiota (2 ed., pp. 307-340). Academic Press. https://doi.org/10.1016/B978-0-323-99971-7.00009-6

McMath, A. L., Barton, J. M., Cai, T., Khan, N. A., Fiese, B. H., & Donovan, S. M. (2024). Western, Healthful, and Low-Preparation Diet Patterns in Preschoolers of the STRONG Kids2 Program. Journal of Nutrition Education and Behavior, 56(4), 219-229. https://doi.org/10.1016/j.jneb.2023.12.012

Lim, J., Koprowski, K., Stavins, R., Xuan, N., Hoang, T. H., Baek, J., Kindratenko, V., Khaertdinova, L., Kim, A. Y., Do, M., King, W. P., Valera, E., & Bashir, R. (in press). Point-of-Care Multiplex Detection of Respiratory Viruses. ACS Sensors, 9(8), 4058-4068. https://doi.org/10.1021/acssensors.4c00992

Le, M. Q., Nguyen, T. V., Le, T. N., Do, T. T., Do, M. N., & Tran, M. T. (2024). MaskDiff: Modeling Mask Distribution with Diffusion Probabilistic Model for Few-Shot Instance Segmentation. In M. Wooldridge, J. Dy, & S. Natarajan (Eds.), Technical Tracks 14 (3 ed., pp. 2874-2881). (Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 38, No. 3). Association for the Advancement of Artificial Intelligence. https://doi.org/10.1609/aaai.v38i3.28068

Kambar, N., Go, Y. K., Snyder, C., Do, M. N., & Leal, C. (2024). Structural characterization of lateral phase separation in polymer–lipid hybrid membranes. In Biophysical Approaches for the Study of Membrane Structure - Part A: Experimental (pp. 235-273). (Methods in Enzymology; Vol. 700). Academic Press Inc.. https://doi.org/10.1016/bs.mie.2024.04.023

Holthaus, T. A., Keye, S. A., Verma, S., Cannavale, C. N., Burd, N. A., Holscher, H. D., & Khan, N. A. (2024). Dietary patterns and carotenoid intake: Comparisons of MIND, Mediterranean, DASH, and Healthy Eating Index. Nutrition Research, 126, 58-66. https://doi.org/10.1016/j.nutres.2024.03.008

Holscher, H. D. (2024). Diving into dietary pattern and dietary diversity analyses. American Journal of Clinical Nutrition, 119(5), 1095-1096. Advance online publication. https://doi.org/10.1016/j.ajcnut.2024.03.014

Hoang, T. H., Zehni, M., Phan, H., Vo, D. M., & Do, M. N. (2024). Improving the Robustness of 3D Human Pose Estimation: A Benchmark Dataset and Learning from Noisy Input. In Proceedings - 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2024 (pp. 113-123). (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops). IEEE Computer Society. https://doi.org/10.1109/CVPRW63382.2024.00016

Gu, X., Qi, Y., & El-Kebir, M. (2024). DERNA Enables Pareto Optimal RNA Design. Journal of Computational Biology, 31(3), 179-196. https://doi.org/10.1089/cmb.2023.0283

Golding, I., & Amir, A. (2024). Colloquium: Gene expression in growing cells: A biophysical primer. Reviews of Modern Physics, 96(4), Article 041001. https://doi.org/10.1103/RevModPhys.96.041001

Geng, Y., Nguyen, T. V. P., Homaee, E., & Golding, I. (2024). Using bacterial population dynamics to count phages and their lysogens. Nature communications, 15(1), Article 7814. https://doi.org/10.1038/s41467-024-51913-6

Fung, T., Pande, J., Shnerb, N. M., O'Dwyer, J. P., & Chisholm, R. A. (2024). Processes governing species richness in communities exposed to temporal environmental stochasticity: A review and synthesis of modelling approaches. Mathematical Biosciences, 369, Article 109131. https://doi.org/10.1016/j.mbs.2023.109131

Fleming, S. A., Reyes, S. M., Donovan, S. M., Hernell, O., Jiang, R., Lönnerdal, B., Neu, J., Steinman, L., Sørensen, E. S., West, C. E., Kleinman, R., & Wallingford, J. C. (2024). An expert panel on the adequacy of safety data and physiological roles of dietary bovine osteopontin in infancy. Frontiers in Nutrition, 11, Article 1404303. https://doi.org/10.3389/fnut.2024.1404303

Erdman, J. W., & Donovan, S. M. (2024). Nutritional Science at the University of Illinois at Urbana-Champaign: 100 Years of Nutrition Research and Counting. Nutrition Today, 59(3), 110-118. https://doi.org/10.1097/NT.0000000000000683

Dubinkina, V., Bhogale, S., Hsieh, P. H., Dibaeinia, P., Nambiar, A., Maslov, S., Yoshikuni, Y., & Sinha, S. (2024). A transcriptomic atlas of acute stress response to low pH in multiple Issatchenkia orientalis strains. Microbiology Spectrum, 12(1). https://doi.org/10.1128/spectrum.02536-23

Daniels, V. C., Monaco, M. H., Hirvonen, J., Ouwehand, A. C., Jensen, H. M., Mukerjea, R., Christensen, N., Lehtinen, M. J., Dilger, R. N., & Donovan, S. M. (2024). Interactions between the human milk oligosaccharide 2′-fucosyllactose and Bifidobacterium longum subspecies infantis in influencing systemic immune development and function in piglets. Frontiers in Nutrition, 11, Article 1444594. https://doi.org/10.3389/fnut.2024.1444594

Colussi, J., Sonka, S., Schnitkey, G. D., Morgan, E. L., & Padula, A. D. (2024). A Comparative Study of the Influence of Communication on the Adoption of Digital Agriculture in the United States and Brazil. Agriculture (Switzerland), 14(7), Article 1027. https://doi.org/10.3390/agriculture14071027

Coates, P. M., Bailey, R. L., Blumberg, J. B., El-Sohemy, A., Floyd, E., Goldenberg, J. Z., Gould Shunney, A., Holscher, H. D., Nkrumah-Elie, Y., Rai, D., Ritz, B. W., & Weber, W. J. (2024). The Evolution of Science and Regulation of Dietary Supplements: Past, Present, and Future. Journal of Nutrition, 154(8), 2335-2345. https://doi.org/10.1016/j.tjnut.2024.06.017

Barton, J. M., McMath, A. L., Montgomery, S. P., Donovan, S. M., & Fiese, B. H. (2024). Longitudinal changes in home food availability and concurrent associations with food and nutrient intake among children at 24-48 months. Public Health Nutrition, 27(1), Article e62. https://doi.org/10.1017/S1368980024000375

Alvarado, D. A., Ibarra-Sánchez, L. A., Mysonhimer, A. R., Khan, T. A., Cao, R., Miller, M. J., & Holscher, H. D. (2024). Honey Varietals Differentially Impact Bifidobacterium animalis ssp. lactis Survivability in Yogurt through Simulated In Vitro Digestion. Journal of Nutrition, 154(3), 866-874. https://doi.org/10.1016/j.tjnut.2024.01.010

Abdelmeguid, M., Mia, M. S., & Elbanna, A. (2024). On the Interplay Between Distributed Bulk Plasticity and Local Fault Slip in Evolving Fault Zone Complexity. Geophysical Research Letters, 51(14), Article e2023GL108060. https://doi.org/10.1029/2023GL108060

Aagaard, K. M., Barkin, S. L., Burant, C. F., Carnell, S., Demerath, E., Donovan, S. M., Eneli, I., Francis, L. A., Gilbert-Diamond, D., Hivert, M. F., LeBourgeois, M. K., Loos, R. J. F., Lumeng, J. C., Miller, A. L., Okely, A. D., Osganian, S. K., Ramirez, A. G., Trasande, L., Van Horn, L. V., ... Yanovski, S. Z. (2024). Understanding risk and causal mechanisms for developing obesity in infants and young children: A National Institutes of Health workshop. Obesity Reviews, 25(4), Article e13690. https://doi.org/10.1111/obr.13690

2023

Raginsky, M. (2023). Biological Autonomy. Biological Theory, 18(4), 303–308. https://doi.org/10.1007/s13752-023-00440-

Song, C. L., Main, E. J., Simmons, F., Liu, S., Phillabaum, B., Dahmen, K. A., Hudson, E. W., Hoffman, J. E., & Carlson, . W. (2023). Critical nematic correlations throughout the superconducting doping range in Bi2−zPb zSr2−yLa yCuO6+x. Nature communications, 14(1), Article 2622. https://doi.org/10.1038/s41467-023-38249-3

Guo, B., Holscher, H. D., Auvil, L. S., Welge, M. E., Bushell, C. B., Novotny, J. A., Baer, D. J., Burd, N. A., Khan, N. A., & Zhu, R. (2023). Estimating Heterogeneous Treatment Effect on Multivariate Responses Using Random Forests. Statistics in Biosciences, 15(3), 545-561. https://doi.org/10.1007/s12561-021-09310-w

Huerta, E. A., Blaiszik, B., Brinson, L. C., Bouchard, K. E., Diaz, D., Doglioni, C., Duarte, J. M., Emani, M., Foster, I., Fox, G., Harris, P., Heinrich, L., Jha, S., Katz, D. S., Kindratenko, V., Kirkpatrick, C. R., Lassila-Perini, K., Madduri, R. K., Neubauer, M. S., ... Zhu, R. (2023). FAIR for AI: An interdisciplinary and international community building perspective. Scientific Data, 10(1), Article 487. https://doi.org/10.1038/s41597-023-02298-6

Salners, T., Avila, K. E., Nicholson, B., Myers, C. R., Beggs, J., & Dahmen, K. A. (2023). Recurrent activity in neuronal avalanches. Scientific reports, 13(1), Article 4871. https://doi.org/10.1038/s41598-023-31851-x

Lozano, A. C., Ding, H., Abe, N., & Lipka, A. E. (2023). Regularized multi-trait multi-locus linear mixed models for genome-wide association studies and genomic selection in crops. BMC bioinformatics, 24(1), Article 399. https://doi.org/10.1186/s12859-023-05519-2

Arya, S., George, A. B., & O’Dwyer, J. P. (2023). Sparsity of higher-order landscape interactions enables learning and prediction for microbiomes. Proceedings of the National Academy of Sciences, 120(48), Article e2307313120. https://doi.org/10.1073/pnas.2307313120

Pesantez, J. E., Li, B., Lee, C., Zhao, Z., Butala, M., & Stillwell, A. S. (2023). A Comparison Study of Predictive Models for Electricity Demand in a Diverse Urban Environment. Energy, 283, Article 129142. https://doi.org/10.1016/j.energy.2023.129142

Liu, X., Milenkovic, O., & Moustakides, G. V. (2023). Query-based selection of optimal candidates under the Mallows model. Theoretical Computer Science, 979, Article 114206. https://doi.org/10.1016/j.tcs.2023.114206

Greenberg, G., Ravi, A. N., & Shomorony, I. (2023). LexicHash: Sequence Similarity Estimation via Lexicographic Comparison of Hashes. Bioinformatics, 39(11). https://doi.org/10.1093/bioinformatics/btad652

Nambiar, A., Dubinkina, V., Liu, S., & Maslov, S. (2023). FUN-PROSE: A deep learning approach to predict condition-specific gene expression in fungi. PLoS computational biology, 19(11), 1-21. Article e1011563. https://doi.org/10.1371/journal.pcbi.1011563

Njuguna, J. N., Clark, L. V., Lipka, A. E., Anzoua, K. G., Bagmet, L., Chebukin, P., Dwiyanti, M. S., Dzyubenko, E., Dzyubenko, N., Ghimire, B. K., Jin, X., Johnson, D. A., Nagano, H., Peng, J., Petersen, K. K., Sabitov, A., Seong, E. S., Yamada, T., Yoo, J. H., ... Sacks, E. J. (2023). Genome-wide association and genomic prediction for yield and component traits of Miscanthus sacchariflorus. GCB Bioenergy, 15(11), 1355-1372. https://doi.org/10.1111/gcbb.13097

Della Coletta, R., Fernandes, S. B., Monnahan, P. J., Mikel, M. A., Bohn, M. O., Lipka, A. E., & Hirsch, C. N. (2023). Importance of genetic architecture in marker selection decisions for genomic prediction. Theoretical and Applied Genetics, 136(11), Article 220. https://doi.org/10.1007/s00122-023-04469-w

George, A. B., & O'Dwyer, J. P. (2023). Universal abundance fluctuations across microbial communities, tropical forests, and urban populations. Proceedings of the National Academy of Sciences, 120(44), Article e2215832120. https://doi.org/10.1073/pnas.2215832120

Weber, L. L., Zhang, C., Ochoa, I., & El-Kebir, M. (2023). Phertilizer: Growing a clonal tree from ultra-low coverage single-cell DNA sequencing of tumors. PLoS computational biology, 19(10), Article e1011544. https://doi.org/10.1371/journal.pcbi.1011544

Mia, M. S., Abdelmeguid, M., & Elbanna, A. E. (2023). The spectrum of fault slip in elastoplastic fault zones. Earth and Planetary Science Letters, 619, Article 118310. https://doi.org/10.1016/j.epsl.2023.118310

Cannavale, C. N., Keye, S. A., Rosok, L. M., Martell, S. G., Holthaus, T. A., Raine, L. R., Mullen, S. P., Holscher, H. D., Hillman, C. H., Kramer, A. F., Cohen, N. J., Hammond, B. R., Renzi-Hammond, L., & Khan, N. A. (2023). Macular Pigment Optical Density and Skin Carotenoids in a Childhood Sample. Journal of Nutrition, 153(10), 3144-3151. https://doi.org/10.1016/j.tjnut.2023.06.006

Deville, L., Emerson, T., Garibaldi, S., Reed, M. L., Washington, T. M., & Weekes, S. L. (2023). Supporting Faculty in Mentoring Students for Careers Beyond Academia. Notices of the American Mathematical Society, 70(9), 1442-1447. https://doi.org/10.1090/noti2784

Sarker, K., Zhu, R., Holscher, H. D., & Zhai, C. X. (2023). Augmenting nutritional metabolomics with a genome-scale metabolic model for assessment of diet intake. In ACM-BCB 2023 - 14th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics Article 4 (ACM-BCB 2023 - 14th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics). Association for Computing Machinery. https://doi.org/10.1145/3584371.3612958

Murphy, M. D., & Lipka, A. E. (2023). An application of vGWAS to differences in flowering time in maize across mega-environments. Crop Science, 63(5), 2807-2817. https://doi.org/10.1002/csc2.21051

George, A. B., Wang, T., & Maslov, S. (2023). Functional convergence in slow-growing microbial communities arises from thermodynamic constraints. ISME Journal, 17(9), 1482-1494. https://doi.org/10.1038/s41396-023-01455-4

Saldi, N., Başar, T., & Raginsky, M. (2023). Partially Observed Discrete-Time Risk-Sensitive Mean Field Games. Dynamic Games and Applications, 13(3), 929-960. https://doi.org/10.1007/s13235-022-00453-z

Fan, Y., McMath, A. L., & Donovan, S. M. (2023). Review on the Impact of Milk Oligosaccharides on the Brain and Neurocognitive Development in Early Life. Nutrients, 15(17), Article 3743. https://doi.org/10.3390/nu15173743

Hajarolasvadi, S., Celli, P., Kim, B., Elbanna, A. E., & Daraio, C. (2023). Experimental evidence of amplitude-dependent surface wave dispersion via nonlinear contact resonances. Applied Physics Letters, 123(8), Article 081704. https://doi.org/10.1063/5.0151294

Della Coletta, R., Liese, S. E., Fernandes, S. B., Mikel, M. A., Bohn, M. O., Lipka, A. E., & Hirsch, C. N. (2023). Linking genetic and environmental factors through marker effect networks to understand trait plasticity. Genetics, 224(4), Article iyad103. https://doi.org/10.1093/genetics/iyad103

Pattabiraman, S., Gabrys, R., & Milenkovic, O. (2023). Coding for Polymer-Based Data Storage. IEEE Transactions on Information Theory, 69(8), 4812-4836. https://doi.org/10.1109/TIT.2023.3267620

Cai, T., Sutter, C., Donovan, S. M., & Fiese, B. H. (2023). The Relationship Between Maternal and Infant Sleep Duration Across the First Two Years. Journal of Developmental and Behavioral Pediatrics, 44(6), E421-E428. https://doi.org/10.1097/DBP.0000000000001195

Gu, X., Qi, Y., & El-Kebir, M. (2023). Balancing Minimum Free Energy and Codon Adaptation Index for Pareto Optimal RNA Design. In D. Belazzougui, & A. Ouangraoua (Eds.), 23rd International Workshop on Algorithms in Bioinformatics, WABI 2023 Article 21 (Leibniz International Proceedings in Informatics, LIPIcs; Vol. 273). Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.WABI.2023.21

Roddur, M. S., Snir, S., & El-Kebir, M. (2023). Inferring Temporally Consistent Migration Histories. In D. Belazzougui, & A. Ouangraoua (Eds.), 23rd International Workshop on Algorithms in Bioinformatics, WABI 2023 Article 9 (Leibniz International Proceedings in Informatics, LIPIcs; Vol. 273). Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing. https://doi.org/10.4230/LIPIcs.WABI.2023.9

Holthaus, T. A., Sethi, S., Cannavale, C. N., Aguiñaga, S., Burd, N. A., Holscher, H. D., & Khan, N. A. (2023). MIND dietary pattern adherence is inversely associated with visceral adiposity and features of metabolic syndrome. Nutrition Research, 116, 69-79. https://doi.org/10.1016/j.nutres.2023.06.001

Stroet, M., Caron, B., Engler, M. S., van der Woning, J., Kauffmann, A., van Dijk, M., El-Kebir, M., Visscher, K. M., Holownia, J., Macfarlane, C., Bennion, B. J., Gelpi-Dominguez, S., Lightstone, F. C., van der Storm, T., Geerke, D. P., Mark, A. E., & Klau, G. W. (2023). OFraMP: a fragment-based tool to facilitate the parametrization of large molecules. Journal of Computer-Aided Molecular Design, 37(8), 357-371. https://doi.org/10.1007/s10822-023-00511-7

Robben, M., Nasr, M. S., Das, A., Veerla, J. P., Huber, M., Jaworski, J., Weidanz, J., & Luber, J. (2023). Comparison of the Strengths and Weaknesses of Machine Learning Algorithms and Feature Selection on KEGG Database Microbial Gene Pathway Annotation and Its Effects on Reconstructed Network Topology. Journal of Computational Biology, 30(7), 766-782. https://doi.org/10.1089/cmb.2022.0370

Baldeon, A. D., McDonald, D., Gonzalez, A., Knight, R., & Holscher, H. D. (2023). Diet Quality and the Fecal Microbiota in Adults in the American Gut Project. Journal of Nutrition, 153(7), 2004-2015. https://doi.org/10.1016/j.tjnut.2023.02.018

Unger, A. L., Astrup, A., Feeney, E. L., Holscher, H. D., Gerstein, D. E., Torres-Gonzalez, M., & Brown, K. (2023). Harnessing the Magic of the Dairy Matrix for Next-Level Health Solutions: A Summary of a Symposium Presented at Nutrition 2022. Current Developments in Nutrition, 7(7), Article 100105. https://doi.org/10.1016/j.cdnut.2023.100105

Baur, B., Shin, J., Schreiber, J., Zhang, S., Zhang, Y., Manjunath, M., Song, J. S., Noble, W. S., & Roy, S. (2023). Leveraging epigenomes and three-dimensional genome organization for interpreting regulatory variation. PLoS computational biology, 19(7), Article e1011286. https://doi.org/10.1371/journal.pcbi.1011286

Ivanovic, S., & El-Kebir, M. (2023). Modeling and predicting cancer clonal evolution with reinforcement learning. Genome Research, 33(7), 1078-1088. https://doi.org/10.1101/gr.277672.123

Morton, J. T., Jin, D. M., Mills, R. H., Shao, Y., Rahman, G., McDonald, D., Zhu, Q., Balaban, M., Jiang, Y., Cantrell, K., Gonzalez, A., Carmel, J., Frankiensztajn, L. M., Martin-Brevet, S., Berding, K., Needham, B. D., Zurita, M. F., David, M., Averina, O. V., ... Taroncher-Oldenburg, G. (2023). Multi-level analysis of the gut–brain axis shows autism spectrum disorder-associated molecular and microbial profiles. Nature Neuroscience, 26(7), 1208-1217. https://doi.org/10.1038/s41593-023-01361-0

Karakoc, D. B., Konar, M., Puma, M. J., & Varshney, L. R. (2023). Structural chokepoints determine the resilience of agri-food supply chains in the United States. Nature Food, 4(7), 607-615. https://doi.org/10.1038/s43016-023-00793-y

Jops, K., & O’Dwyer, J. P. (2023). Life history complementarity and the maintenance of biodiversity. Nature, 618(7967), 986-991. https://doi.org/10.1038/s41586-023-06154-w

Basu, S., Sattigeri, P., Ramamurthy, K. N., Chenthamarakshan, V., Varshney, K. R., Varshney, L. R., & Das, P. (2023). Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models. In B. Williams, Y. Chen, & J. Neville (Eds.), AAAI-23 Technical Tracks 6 (pp. 6788-6796). (Proceedings of the 37th AAAI Conference on Artificial Intelligence, AAAI 2023; Vol. 37). American Association for Artificial Intelligence (AAAI) Press.

Choraria, M., Ferwana, I., Mani, A., & Varshney, L. R. (2023). Learning Optimal Features via Partial Invariance. In B. Williams, Y. Chen, & J. Neville (Eds.), AAAI-23 Technical Tracks 6 (pp. 7175-7183). (Proceedings of the 37th AAAI Conference on Artificial Intelligence, AAAI 2023; Vol. 37). American Association for Artificial Intelligence (AAAI) Press.

Bleier, N., Wezelis, A., Varshney, L., & Kumar, R. (2023). Programmable Olfactory Computing. In ISCA 2023 - Proceedings of the 2023 50th Annual International Symposium on Computer Architecture (pp. 358-371). (Proceedings - International Symposium on Computer Architecture). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1145/3579371.3589061

Cannavale, C. N., Edwards, C. G., Liu, R., Keye, S. A., Iwinski, S. J., Holscher, H. D., Renzi-Hammond, L., & Khan, N. A. (2023). Macular pigment is inversely related to circulating C-reactive protein concentrations in school-aged children. Nutrition Research, 114, 13-19. https://doi.org/10.1016/j.nutres.2023.03.003

Bailey, M. A., Thompson, S. V., Mysonhimer, A. R., Bennett, J. N., Vanhie, J. J., De Lisio, M., Burd, N. A., Khan, N. A., & Holscher, H. D. (2023). Dietary fiber intake and fecal short chain fatty acid concentrations are associated with lower plasma lipopolysaccharide-binding protein and inflammation. American Journal of Physiology - Gastrointestinal and Liver Physiology, 324(5), G369-G377. https://doi.org/10.1152/ajpgi.00176.2021

Mysonhimer, A. R., & Holscher, H. D. (2023). Nondigestible Carbohydrate Consumption: Balancing Therapeutics With Gastrointestinal Effects and Tolerance. Nutrition Today, 58(3), 100-104. https://doi.org/10.1097/NT.0000000000000605

Pan, C., Chien, E., & Milenkovic, O. (2023). Unlearning Graph Classifiers with Limited Data Resources. In ACM Web Conference 2023 - Proceedings of the World Wide Web Conference, WWW 2023 (pp. 716-726). (ACM Web Conference 2023 - Proceedings of the World Wide Web Conference, WWW 2023). Association for Computing Machinery. https://doi.org/10.1145/3543507.3583547

Hughes, R. L., Pindus, D. M., Khan, N. A., Burd, N. A., & Holscher, H. D. (2023). Associations between Accelerometer-Measured Physical Activity and Fecal Microbiota in Adults with Overweight and Obesity. Medicine and Science in Sports and Exercise, 55(4), 680-689. https://doi.org/10.1249/MSS.0000000000003096

O’Shaughnessy, M. R., Schiff, D. S., Varshney, L. R., Rozell, C. J., & Davenport, M. A. (2023). What governs attitudes toward artificial intelligence adoption and governance? Science and Public Policy, 50(2), 161-176. Article scac056. https://doi.org/10.1093/scipol/scac056

Donovan, S. M., Aghaeepour, N., Andres, A., Azad, M. B., Becker, M., Carlson, S. E., Järvinen, K. M., Lin, W., Lönnerdal, B., Slupsky, C. M., Steiber, A. L., & Raiten, D. J. (2023). Evidence for human milk as a biological system and recommendations for study design—a report from “Breastmilk Ecology: Genesis of Infant Nutrition (BEGIN)” Working Group 4. American Journal of Clinical Nutrition, 117, S61-S86. https://doi.org/10.1016/j.ajcnut.2022.12.021

Kim, J. S., Takahagi, K., Inoue, K., Shimizu, M., Uehara-Yamaguchi, Y., Kanatani, A., Saisho, D., Nishii, R., Lipka, A. E., Hirayama, T., Sato, K., & Mochida, K. (2023). Exome-wide variation in a diverse barley panel reveals genetic associations with ten agronomic traits in Eastern landraces. Journal of Genetics and Genomics, 50(4), 241-252. https://doi.org/10.1016/j.jgg.2022.12.001

Erickson, B. A., Jiang, J., Lambert, V., Barbot, S. D., Abdelmeguid, M., Almquist, M., Ampuero, J. P., Ando, R., Cattania, C., Chen, A., Dal Zilio, L., Deng, S., Dunham, E. M., Elbanna, A. E., Gabriel, A. A., Harvey, T. W., Huang, Y., Kaneko, Y., Kozdon, J. E., ... Yang, Y. (2023). Incorporating Full Elastodynamic Effects and Dipping Fault Geometries in Community Code Verification Exercises for Simulations of Earthquake Sequences and Aseismic Slip (SEAS). Bulletin of the Seismological Society of America, 113(2), 499-523. https://doi.org/10.1785/0120220066

Mysonhimer, A. R., Cannavale, C. N., Bailey, M. A., Khan, N. A., & Holscher, H. D. (2023). Prebiotic Consumption Alters Microbiota but Not Biological Markers of Stress and Inflammation or Mental Health Symptoms in Healthy Adults: A Randomized, Controlled, Crossover Trial. Journal of Nutrition, 153(4), 1283-1296. https://doi.org/10.1016/j.tjnut.2023.02.015

Pan, C., Chien, E., Tabaghi, P., Peng, J., & Milenkovic, O. (2023). Provably accurate and scalable linear classifiers in hyperbolic spaces. Knowledge and Information Systems, 65(4), 1817-1850. https://doi.org/10.1007/s10115-022-01820-3

Reichhardt, C., Regev, I., Dahmen, K., Okuma, S., & Reichhardt, C. J. O. (2023). Reversible to irreversible transitions in periodic driven many-body systems and future directions for classical and quantum systems. Physical Review Research, 5(2), Article 021001. https://doi.org/10.1103/PhysRevResearch.5.021001

Donovan, S. M., Abrams, S. A., Azad, M. B., Belfort, M. B., Bode, L., Carlson, S. E., Dallas, D. C., Hettinga, K., Järvinen, K., Kim, J. H., Lebrilla, C. B., McGuire, M. K., Sela, D. A., & Neu, J. (2023). Summary of the Joint National Institutes of Health and the Food and Drug Administration Workshop Titled “Exploring the Science Surrounding the Safe Use of Bioactive Ingredients in Infant Formula: Considerations for an Assessment Framework”. Journal of Pediatrics, 255, 30-41.e1. https://doi.org/10.1016/j.jpeds.2022.11.027

Chakraborty, R., Xiong, M., Athreya, N., Tabatabaei, S. K., Milenkovic, O., & Leburton, J. P. (2023). Solid-State MoS2 Nanopore Membranes for Discriminating among the Lengths of RNA Tails on a Double-Stranded DNA: A New Simulation-Based Differentiating Algorithm. ACS Applied Nano Materials, 6(6), 4651-4660. https://doi.org/10.1021/acsanm.3c00129

Alexander, F. J., Reyes, K. R., Varshney, L. R., & Yoon, B. J. (2023). AI for optimal experimental design and decision-making. In Artificial Intelligence For Science: A Deep Learning Revolution (pp. 609-625). World Scientific Publishing Co. Pte Ltd. https://doi.org/10.1142/9789811265679_0032

Burroughs, C. H., Montes, C. M., Moller, C. A., Mitchell, N. G., Michael, A. M., Peng, B., Kimm, H., Pederson, T. L., Lipka, A. E., Bernacchi, C. J., Guan, K., & Ainsworth, E. A. (2023). Reductions in Leaf Area Index, Pod Production, Seed Size and Harvest Index Drive Yield Loss to High Temperatures in Soybean. Journal of experimental botany, 74(5), 1629–1641. Article erac503. https://doi.org/10.1093/jxb/erac503

Wen, B., Ravishankar, S., Zhao, Z., Giryes, R., & Ye, J. C. (2023). Physics-Driven Machine Learning for Computational Imaging: Part 2 [From the Guest Editors]. IEEE Signal Processing Magazine, 40(2), 13-15. https://doi.org/10.1109/MSP.2023.3236492

Rashid, F., Dubinkina, V., Ahmad, S., Maslov, S., & Irudayaraj, J. M. K. (2023). Gut Microbiome-Host Metabolome Homeostasis upon Exposure to PFOS and GenX in Male Mice. Toxics, 11(3), Article 281. https://doi.org/10.3390/toxics11030281

Wang, T., Wang, X. W., Lee-Sarwar, K. A., Litonjua, A. A., Weiss, S. T., Sun, Y., Maslov, S., & Liu, Y. Y. (2023). Predicting metabolomic profiles from microbial composition through neural ordinary differential equations. Nature Machine Intelligence, 5(3), 284-293. https://doi.org/10.1038/s42256-023-00627-3

Fei, F., Mia, M. S., Elbanna, A. E., & Choo, J. (2023). A phase-field model for quasi-dynamic nucleation, growth, and propagation of rate-and-state faults. International Journal for Numerical and Analytical Methods in Geomechanics, 47(2), 187-211. https://doi.org/10.1002/nag.3465

Holscher, H. D. (2023). Let's do the math: embracing mathematical modeling to advance nutrition research. American Journal of Clinical Nutrition, 117(2), 220-221. https://doi.org/10.1016/j.ajcnut.2022.12.011

Splichal, I., Donovan, S. M., Kindlova, Z., Stranak, Z., Neuzil Bunesova, V., Sinkora, M., Polakova, K., Valaskova, B., & Splichalova, A. (2023). Release of HMGB1 and Toll-like Receptors 2, 4, and 9 Signaling Are Modulated by Bifidobacterium animalis subsp. lactis BB-12 and Salmonella Typhimurium in a Gnotobiotic Piglet Model of Preterm Infants. International journal of molecular sciences, 24(3), Article 2329. https://doi.org/10.3390/ijms24032329

Rana, P., & Varshney, L. R. (2023). Exploring limits to tree planting as a natural climate solution. Journal of Cleaner Production, 384, Article 135566. https://doi.org/10.1016/j.jclepro.2022.135566

Shinn, L. M., Mansharamani, A., Baer, D. J., Novotny, J. A., Charron, C. S., Khan, N. A., Zhu, R., & Holscher, H. D. (2023). Fecal Metabolites as Biomarkers for Predicting Food Intake by Healthy Adults. The Journal of nutrition, 152(12), 2956-2965. Article nxac195. https://doi.org/10.1093/jn/nxac195

Holthaus, T. A., Kashi, M., Cannavale, C. N., Edwards, C. G., Aguiñaga, S., Walk, A. D. M., Burd, N. A., Holscher, H. D., & Khan, N. A. (2023). MIND Dietary Pattern Adherence Is Selectively Associated with Cognitive Processing Speed in Middle-Aged Adults. The Journal of nutrition, 152(12), 2941-2949. Article nxac203. https://doi.org/10.1093/jn/nxac203

Kim, Y., Shin, J., Cassuto, Y., & Varshney, L. R. (2023). Distributed Boosting Classification Over Noisy Communication Channels. IEEE Journal on Selected Areas in Communications, 41(1), 141-154. https://doi.org/10.1109/JSAC.2022.3221972

Zhao, Z., Ye, J. C., & Bresler, Y. (2023). Generative Models for Inverse Imaging Problems: From mathematical foundations to physics-driven applications. IEEE Signal Processing Magazine, 40(1), 148-163. https://doi.org/10.1109/MSP.2022.3215282

Wen, B., Ravishankar, S., Zhao, Z., Giryes, R., & Ye, J. C. (2023). Physics-Driven Machine Learning for Computational Imaging [From the Guest Editor]. IEEE Signal Processing Magazine, 40(1), 28-30. https://doi.org/10.1109/MSP.2022.3222888

Gabrys, R., Pattabiraman, S., & Milenkovic, O. (2023). Reconstruction of Sets of Strings From Prefix/Suffix Compositions. IEEE Transactions on Communications, 71(1), 3-12. https://doi.org/10.1109/TCOMM.2022.3222341

Rana, V., Chien, E., Peng, J., & Milenkovic, O. (2023). Small-Sample Estimation of the Mutational Support and Distribution of SARS-CoV-2. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 20(1), 668-682. https://doi.org/10.1109/TCBB.2022.3165395

Nambiar, A., Liu, S., Heflin, M., Forsyth, J. M., Maslov, S., Hopkins, M., & Ritz, A. (2023). Transformer Neural Networks for Protein Family and Interaction Prediction Tasks. Journal of Computational Biology, 30(1), 95-111. https://doi.org/10.1089/cmb.2022.0132

McMath, A. L., Iwinski, S., Shen, S., Bost, K. F., Donovan, S. M., & Khan, N. A. (2023). Adherence to screen time and physical activity guidelines is associated with executive function in US toddlers participating in the STRONG Kids 2 birth cohort study. The Journal of Pediatrics, 252, 22-30.e6. https://doi.org/10.1016/j.jpeds.2022.08.026

Luo, D., Chen, Z., Hu, K., Zhao, Z., Hur, V. M., & Clark, B. K. (2023). Gauge-invariant and anyonic-symmetric autoregressive neural network for quantum lattice models. Physical Review Research, 5(1), Article 013216. https://doi.org/10.1103/PhysRevResearch.5.013216

Varshney, K. R., & Varshney, L. R. (2023). A Banal Account of a Safety-Creativity Tradeoff in Generative AI. CEUR Workshop Proceedings, 3359, 163-165.

Liu, X., Milenkovic, O., & Moustakides, G. V. (2023). A Combinatorial Proof for the Dowry Problem. In 2023 IEEE Information Theory Workshop, ITW 2023 (pp. 538-543). (2023 IEEE Information Theory Workshop, ITW 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITW55543.2023.10161638

Shin, S., Zhao, H., & Shomorony, I. (2023). Adaptive Power Method: Eigenvector Estimation from Sampled Data. Proceedings of Machine Learning Research, 201, 1387-1410.

Islam, M. S., Corak, K., McCord, P., Hulse-Kemp, A. M., & Lipka, A. E. (2023). A first look at the ability to use genomic prediction for improving the ratooning ability of sugarcane. Frontiers in Plant Science, 14, Article 1205999. https://doi.org/10.3389/fpls.2023.1205999

Fan, Y., Khoo, Y., & Zhao, Z. (2023). A SPECTRAL METHOD FOR JOINT COMMUNITY DETECTION AND ORTHOGONAL GROUP SYNCHRONIZATION. SIAM Journal on Matrix Analysis and Applications, 44(2), 781-821. https://doi.org/10.1137/21m1467845

McMath, A. L., Aguilar-Lopez, M., Cannavale, C. N., Khan, N. A., & Donovan, S. M. (2023). A systematic review on the impact of gastrointestinal microbiota composition and function on cognition in healthy infants and children. Frontiers in Neuroscience, 17, Article 1171970. https://doi.org/10.3389/fnins.2023.1171970

Kim, S., Yuan, J. B., Woods, W. S., Newton, D. A., Perez-Pinera, P., & Song, J. S. (2023). Chromatin structure and context-dependent sequence features control prime editing efficiency. Frontiers in Genetics, 14, Article 1222112. https://doi.org/10.3389/fgene.2023.1222112

Nasr, M. S., Hajighasemi, A., Koomey, P., Malidarreh, P. B., Robben, M., Saurav, J. R., Shang, H. H., Huber, M., & Luber, J. M. (2023). Clinically Relevant Latent Space Embedding of Cancer Histopathology Slides Through Variational Autoencoder based Image Compression. In 2023 IEEE International Symposium on Biomedical Imaging, ISBI 2023 (Proceedings - International Symposium on Biomedical Imaging; Vol. 2023-April). IEEE Computer Society. https://doi.org/10.1109/ISBI53787.2023.10230343

Cannavale, C. N., Mysonhimer, A. R., Bailey, M. A., Cohen, N. J., Holscher, H. D., & Khan, N. A. (2023). Consumption of a fermented dairy beverage improves hippocampal-dependent relational memory in a randomized, controlled cross-over trial. Nutritional Neuroscience, 26(3), 265-274. https://doi.org/10.1080/1028415X.2022.2046963

Fan, Y., Vinjamuri, A., Tu, D., Lebrilla, C. B., & Donovan, S. M. (2023). Determinants of human milk oligosaccharides profiles of participants in the STRONG kids 2 cohort. Frontiers in Nutrition, 10, Article 1105668. https://doi.org/10.3389/fnut.2023.1105668

Golden, R. K., Sutkus, L. T., Bauer, L. L., Donovan, S. M., & Dilger, R. N. (2023). Determining the safety and efficacy of dietary supplementation with 3ˊ-sialyllactose or 6ˊ-sialyllactose on growth, tolerance, and brain sialic acid concentrations. Frontiers in Nutrition, 10, Article 1278804. https://doi.org/10.3389/fnut.2023.1278804

Bhimaraju, A., Chatterjee, A., & Varshney, L. R. (2023). Dynamic Resource Allocation to Minimize Concave Costs of Shortfalls. IEEE Control Systems Letters, 7, 3633-3638. Article 10347486. https://doi.org/10.1109/LCSYS.2023.3340247

Huang, C., Clark, G. G., Zaki, F. R., Won, J., Ning, R., Boppart, S. A., Elbanna, A. E., & Nguyen, T. H. (2023). Effects of phosphate and silicate on stiffness and viscoelasticity of mature biofilms developed with simulated drinking water. Biofouling, 39(1), 36-46. https://doi.org/10.1080/08927014.2023.2177538

Mac, K. N. C., Do, M. N., & Vo, M. P. (2023). Efficient Human Vision Inspired Action Recognition Using Adaptive Spatiotemporal Sampling. IEEE Transactions on Image Processing, 32, 5245-5256. https://doi.org/10.1109/TIP.2023.3310661

Shinn, L. M., Mansharamani, A., Baer, D. J., Novotny, J. A., Charron, C. S., Khan, N. A., Zhu, R., & Holscher, H. D. (in press). Fecal Metagenomics to Identify Biomarkers of Food Intake in Healthy Adults: Findings from Randomized, Controlled, Nutrition Trials. Journal of Nutrition. https://doi.org/10.1016/j.tjnut.2023.11.001

Vinderola, G., Cotter, P. D., Freitas, M., Gueimonde, M., Holscher, H. D., Ruas-Madiedo, P., Salminen, S., Swanson, K. S., Sanders, M. E., & Cifelli, C. J. (2023). Fermented foods: a perspective on their role in delivering biotics. Frontiers in Microbiology, 14, Article 1196239. https://doi.org/10.3389/fmicb.2023.1196239

Li, Y. H., Gabrys, R., Sima, J., Shomorony, I., & Milenkovic, O. (2023). Finding a Burst of Positives via Nonadaptive Semiquantitative Group Testing. In 2023 IEEE International Symposium on Information Theory, ISIT 2023 (pp. 1848-1853). (IEEE International Symposium on Information Theory - Proceedings; Vol. 2023-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT54713.2023.10206886

Levick, K., & Shomorony, I. (2023). Fundamental Limits of Multiple Sequence Reconstruction from Substrings. In 2023 IEEE International Symposium on Information Theory, ISIT 2023 (pp. 791-796). (IEEE International Symposium on Information Theory - Proceedings; Vol. 2023-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT54713.2023.10206707

Weinberger, N., & Shomorony, I. (2023). Fundamental Limits of Reference-Based Sequence Reordering. In 2023 IEEE International Symposium on Information Theory, ISIT 2023 (pp. 1062-1067). (IEEE International Symposium on Information Theory - Proceedings; Vol. 2023-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT54713.2023.10206760

Sakhale, S. A., Yadav, S., Clark, L. V., Lipka, A. E., Kumar, A., & Sacks, E. J. (2023). Genome-wide association analysis for emergence of deeply sown rice (Oryza sativa) reveals novel aus-specific phytohormone candidate genes for adaptation to dry-direct seeding in the field. Frontiers in Plant Science, 14, Article 1172816. https://doi.org/10.3389/fpls.2023.1172816

Yu, H., Evans, J. A., & Varshney, L. R. (2023). Information Lattice Learning. Journal of Artificial Intelligence Research, 77, 971-1019. https://doi.org/10.1613/jair.1.14277

Lipps, S., Lipka, A. E., Mideros, S., & Jamann, T. (2023). Inhibition of ethylene involved in resistance to E. turcicum in an exotic-derived double haploid maize population. Frontiers in Plant Science, 14, Article 1272951. https://doi.org/10.3389/fpls.2023.1272951

Zhao, X., Zhao, Z., & Schwing, A. G. (2023). Initialization and Alignment for Adversarial Texture Optimization. In L. Karlinsky, T. Michaeli, & K. Nishino (Eds.), Computer Vision – ECCV 2022 Workshops, Proceedings (pp. 587-604). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13803 LNCS). Springer. https://doi.org/10.1007/978-3-031-25066-8_34

Rojas-Gomez, R. A., Yeh, R. A., Do, M. N., & Nguyen, A. (2023). Inverting Adversarially Robust Networks for Image Synthesis. In L. Wang, J. Gall, T-J. Chin, I. Sato, & R. Chellappa (Eds.), Computer Vision – ACCV 2022 - 16th Asian Conference on Computer Vision, Proceedings (pp. 389-407). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13846 LNCS). Springer. https://doi.org/10.1007/978-3-031-26351-4_24

Chu, Y., & Raginsky, M. (2023). Majorizing Measures, Codes, and Information. In 2023 IEEE International Symposium on Information Theory, ISIT 2023 (pp. 660-665). (IEEE International Symposium on Information Theory - Proceedings; Vol. 2023-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT54713.2023.10206592

Wang, L., & Zhao, Z. (2023). Multi-Frequency Joint Community Detection and Phase Synchronization. IEEE Transactions on Signal and Information Processing over Networks, 9, 162-174. https://doi.org/10.1109/TSIPN.2023.3258062

Nguyen, T. T., Pham, H. H., Nguyen, P. L., Nguyen, T. H., & Do, M. (2023). Multi-stream Fusion for Class Incremental Learning in Pill Image Classification. In L. Wang, J. Gall, T-J. Chin, I. Sato, & R. Chellappa (Eds.), Computer Vision – ACCV 2022 - 16th Asian Conference on Computer Vision, 2022, Proceedings (pp. 341-356). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13842 LNCS). Springer. https://doi.org/10.1007/978-3-031-26284-5_21

Veeravalli, T., & Raginsky, M. (2023). Nonlinear Controllability and Function Representation by Neural Stochastic Differential Equations. Proceedings of Machine Learning Research, 211, 838-850.

Sima, J., Li, Y. H., Shomorony, I., & Milenkovic, O. (2023). On Constant-Weight Binary B2-Sequences. In 2023 IEEE International Symposium on Information Theory, ISIT 2023 (pp. 886-891). (IEEE International Symposium on Information Theory - Proceedings; Vol. 2023-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT54713.2023.10206632

Moustakides, G. V., Liu, X., & Milenkovic, O. (in press). Optimal stopping methodology for the secretary problem with random queries. Journal of Applied Probability. https://doi.org/10.1017/jpr.2023.61

Sima, J., Pan, C., & Milenkovic, O. (2023). Perturbation-Resilient Sets for Dynamic Service Balancing. In 2023 IEEE International Symposium on Information Theory, ISIT 2023 (pp. 2278-2283). (IEEE International Symposium on Information Theory - Proceedings; Vol. 2023-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT54713.2023.10206839

Chien, E., Zhang, J., Hsieh, C. J., Jiang, J. Y., Chang, W. C., Milenkovic, O., & Yu, H. F. (2023). PINA: Leveraging Side Information in eXtreme Multi-label Classification via Predicted Instance Neighborhood Aggregation. Proceedings of Machine Learning Research, 202, 5616-5630.

Song, J. S., & Manjunath, M. (2023). Predicting the molecular functions of regulatory genetic variants associated with cancer. Oncotarget, 14, 775-777. https://doi.org/10.18632/oncotarget.28451

Sommer, K. M., Lee, Y., Donovan, S. M., & Dilger, R. N. (2023). Purification methods to reduce interference by dextran sodium sulfate with quantification of gene expression in intestinal tissue samples from a piglet model of colitis. Journal of animal science, 101, Article skad202. https://doi.org/10.1093/jas/skad202

George, I., Chen, X., & Varshney, L. R. (2023). Search for Extraterrestrial Intelligence as One-Shot Hypothesis Testing. In 2023 57th Annual Conference on Information Sciences and Systems, CISS 2023 (2023 57th Annual Conference on Information Sciences and Systems, CISS 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CISS56502.2023.10089645

Wang, W., Lee, H., Jankelow, A. M., Hoang, T. H., Bacon, A., Sun, F., Chae, S., Kindratenko, V., Koprowski, K., Stavins, R. A., Ceriani, D., Engelder, Z., King, W. P., Do, M. N., Bashir, R., Valera, E., & Cunningham, B. T. (2023). Smartphone Clip-On Instrument and Microfluidic Processor for Rapid Sample-to-Answer Detection of Zika Virus in Whole Blood Using Spatial RT-LAMP. In G. L. Cote (Ed.), Optical Diagnostics and Sensing XXIII: Toward Point-of-Care Diagnostics Article 123870D (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 12387). SPIE. https://doi.org/10.1117/12.2649267

Mazooji, K., & Shomorony, I. (2023). Substring Density Estimation from Traces. In 2023 IEEE International Symposium on Information Theory, ISIT 2023 (pp. 803-808). (IEEE International Symposium on Information Theory - Proceedings; Vol. 2023-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT54713.2023.10206758

Tzen, B., Raj, A., Raginsky, M., & Bach, F. (2023). Variational Principles for Mirror Descent and Mirror Langevin Dynamics. IEEE Control Systems Letters, 7, 1542-1547. https://doi.org/10.1109/LCSYS.2023.3274069

 

2022

Fridman, Y., Wang, Z., Maslov, S., & Goyal, A. (2022). Fine-scale diversity of microbial communities due to satellite niches in boom and bust environments. PLoS computational biology, 18(12), [e1010244]. https://doi.org/10.1371/journal.pcbi.1010244

Milenkovic, O., Hernandez, A. G., Zhao, H., & Tabatabaei, S. (2022). Nick-based Data Storage In Native Nucleic Acids. (U.S. Patent No. 11538554).

Mysonhimer, A. R., & Holscher, H. D. (2022). Gastrointestinal Effects and Tolerance of Nondigestible Carbohydrate Consumption. Advances in Nutrition, 13(6), 2237-2276. [nmac094]. https://doi.org/10.1093/advances/nmac094

Holscher, H. D., Chumpitazi, B. P., Dahl, W. J., Fahey, G. C., Liska, D. J., Slavin, J. L., & Verbeke, K. (2022). Perspective: Assessing Tolerance to Nondigestible Carbohydrate Consumption. Advances in Nutrition, 13(6), 2084-2097. [nmac091]. https://doi.org/10.1093/advances/nmac091

Shomorony, I. (2022). Data-driven precision medicine through the analysis of biological functional modules. Cell Reports Medicine, 3(12), [100876]. https://doi.org/10.1016/j.xcrm.2022.100876

Xu, A., & Raginsky, M. (2022). Minimum Excess Risk in Bayesian Learning. IEEE Transactions on Information Theory, 68(12), 7935-7955. https://doi.org/10.1109/TIT.2022.3176056

Chen, Y., Huerta, E. A., Duarte, J., Harris, P., Katz, D. S., Neubauer, M. S., Diaz, D., Mokhtar, F., Kansal, R., Park, S. E., Kindratenko, V. V., Zhao, Z., & Rusack, R. (2022). A FAIR and AI-ready Higgs boson decay dataset. Scientific Data, 9(1), [31]. https://doi.org/10.1038/s41597-021-01109-0

Bailey, R. L., Stang, J. S., Davis, T. A., Naimi, T. S., Schneeman, B. O., Dewey, K. G., Donovan, S. M., Novotny, R., Kleinman, R. E., Taveras, E. M., Bazzano, L., Snetselaar, L. G., de Jesus, J., Casavale, K. O., Stoody, E. E., Goldman, J. D., Moshfegh, A. J., Rhodes, D. G., Herrick, K. A., ... Pannucci, T. R. (2022). Dietary and Complementary Feeding Practices of US Infants, 6 to 12 Months: A Narrative Review of the Federal Nutrition Monitoring Data. Journal of the Academy of Nutrition and Dietetics, 122(12), 2337-2345.e1. https://doi.org/10.1016/j.jand.2021.10.017

Long, A. A., Wright, W. J., Gu, X., Thackray, A., Nakib, M., Uhl, J. T., & Dahmen, K. A. (2022). Experimental evidence that shear bands in metallic glasses nucleate like cracks. Scientific reports, 12(1), [18499]. https://doi.org/10.1038/s41598-022-22548-8

Brown, M. D., Shinn, L. M., Reeser, G., Browning, M., Schwingel, A., Khan, N. A., & Holscher, H. D. (2022). Fecal and soil microbiota composition of gardening and non-gardening families. Scientific reports, 12(1), [1595]. https://doi.org/10.1038/s41598-022-05387-5

Ranoa, D. R. E., Holland, R. L., Alnaji, F. G., Green, K. J., Wang, L., Fredrickson, R. L., Wang, T., Wong, G. N., Uelmen, J., Maslov, S., Weiner, Z. J., Tkachenko, A. V., Zhang, H., Liu, Z., Ibrahim, A., Patel, S. J., Paul, J. M., Vance, N. P., Gulick, J. G., ... Burke, M. D. (2022). Mitigation of SARS-CoV-2 transmission at a large public university. Nature communications, 13(1), [3207]. https://doi.org/10.1038/s41467-022-30833-3

Abdelmeguid, M., & Elbanna, A. (2022). Modeling Sequences of Earthquakes and Aseismic Slip (SEAS) in Elasto-Plastic Fault Zones With a Hybrid Finite Element Spectral Boundary Integral Scheme. Journal of Geophysical Research: Solid Earth, 127(12), [e2022JB024548]. https://doi.org/10.1029/2022JB024548

Sashittal, P., Zaccaria, S., & El-Kebir, M. (2022). Parsimonious Clone Tree Integration in cancer. Algorithms for Molecular Biology, 17(1), [3]. https://doi.org/10.1186/s13015-022-00209-9

Pan, C., Tabatabaei, S. K., Tabatabaei Yazdi, S. M. H., Hernandez, A. G., Schroeder, C. M., & Milenkovic, O. (2022). Rewritable two-dimensional DNA-based data storage with machine learning reconstruction. Nature communications, 13(1), [2984]. https://doi.org/10.1038/s41467-022-30140-x

Khandelwal, A., Athreya, N., Tu, M. Q., Janavicius, L. L., Yang, Z., Milenkovic, O., Leburton, J. P., Schroeder, C. M., & Li, X. (2022). Self-assembled microtubular electrodes for on-chip low-voltage electrophoretic manipulation of charged particles and macromolecules. Microsystems and Nanoengineering, 8(1), [27]. https://doi.org/10.1038/s41378-022-00354-6

Nagarajan, K., Ni, C., & Lu, T. (2022). Agent-Based Modeling of Microbial Communities. ACS synthetic biology, 11(11), 3564-3574. https://doi.org/10.1021/acssynbio.2c00411

Ni, C., & Lu, T. (2022). Individual-Based Modeling of Spatial Dynamics of Chemotactic Microbial Populations. ACS synthetic biology, 11(11), 3714-3723. https://doi.org/10.1021/acssynbio.2c00322

Xiong, J., Yang, A., Raginsky, M., & Rosenbaum, E. (2022). Neural Ordinary Differential Equation Models of Circuits: Capabilities and Pitfalls. IEEE Transactions on Microwave Theory and Techniques, 70(11), 4869-4884. https://doi.org/10.1109/TMTT.2022.3208896

Sommer, K. M., Jespersen, J. C., Sutkus, L. T., Lee, Y., Donovan, S. M., & Dilger, R. N. (2022). Oral gamma-cyclodextrin-encapsulated tributyrin supplementation in young pigs with experimentally induced colitis. Journal of animal science, 100(11), [skac314]. https://doi.org/10.1093/jas/skac314

Smith, R., Varshney, L. R., Nagayama, S., Kazama, M., Kitagawa, T., Managi, S., & Ishikawa, Y. (2022). A computational neuroscience perspective on subjective wellbeing within the active inference framework. International Journal of Wellbeing, 12(4), 102-131. https://doi.org/10.5502/ijw.v12i4.2659

Berger, B., Tian, D., Li, W. V., El-Kebir, M., Tomescu, A. I., Singh, R., Beerenwinkel, N., Li, Y., Boucher, C., & Bar-Joseph, Z. (2022). What are the keys to succeeding as a computational biologist in today's research climate? Cell Systems, 13(10), 781-785. https://doi.org/10.1016/j.cels.2022.09.005

Kuehn, D., Zeisel, S. H., Orenstein, D. F., German, J. B., Field, C. J., Teerdhala, S., Knezevic, A., Patil, S., Donovan, S. M., & Lönnerdal, B. (2022). Effects of a Novel High-Quality Protein Infant Formula on Energetic Efficiency and Tolerance: A Randomized Trial. Journal of Pediatric Gastroenterology and Nutrition, 75(4), 521-528. https://doi.org/10.1097/MPG.0000000000003490

Lalani, Z., Chu, G., Hsu, S., Kagawa, S., Xiang, M., Zaccaria, S., & El-Kebir, M. (2022). CNAViz: An interactive webtool for user-guided segmentation of tumor DNA sequencing data. PLoS computational biology, 18(10), [e1010614]. https://doi.org/10.1371/journal.pcbi.1010614

Liu, X., & Milenkovic, O. (2022). Finding the second-best candidate under the Mallows model. Theoretical Computer Science, 929, 39-68. https://doi.org/10.1016/j.tcs.2022.06.029

Nijholt, E., & Deville, L. (2022). Dynamical systems defined on simplicial complexes: Symmetries, conjugacies, and invariant subspaces. Chaos, 32(9), [093131]. https://doi.org/10.1063/5.0093842

Greenberg, G., & Shomorony, I. (2022). Improving bacterial genome assembly using a test of strand orientation. Bioinformatics, 38, II34-II41. https://doi.org/10.1093/bioinformatics/btac516

Abdelmeguid, M., & Elbanna, A. (2022). Sequences of seismic and aseismic slip on bimaterial faults show dominant rupture asymmetry and potential for elevated seismic hazard. Earth and Planetary Science Letters, 593, [117648]. https://doi.org/10.1016/j.epsl.2022.117648

Amlani, F., Bhat, H. S., Simons, W. J. F., Schubnel, A., Vigny, C., Rosakis, A. J., Efendi, J., Elbanna, A. E., Dubernet, P., & Abidin, H. Z. (2022). Supershear shock front contribution to the tsunami from the 2018 Mw7.5 Palu, Indonesia earthquake. Geophysical Journal International, 230(3), 2089-2097. https://doi.org/10.1093/gji/ggac162

Punyasena, S. W., Haselhorst, D. S., Kong, S., Fowlkes, C. C., & Moreno, J. E. (2022). Automated identification of diverse Neotropical pollen samples using convolutional neural networks. Methods in Ecology and Evolution, 13(9), 2049-2064. https://doi.org/10.1111/2041-210X.13917

Salners, T., Curry, J. F., Hinkle, A. R., Babuska, T. F., Argibay, N., DelRio, F. W., Chandross, M., & Dahmen, K. (2022). Linking Friction Scales from Nano to Macro via Avalanches. Tribology Letters, 70(3), [82]. https://doi.org/10.1007/s11249-022-01619-x

Gibbs, T., Zhang, Y., Miller, Z. R., & ODwyer, J. P. (2022). Stability criteria for the consumption and exchange of essential resources. PLoS computational biology, 18(9), [e1010521]. https://doi.org/10.1371/journal.pcbi.1010521

Chien, E., Tabaghi, P., & Milenkovic, O. (2022). HyperAid: Denoising in Hyperbolic Spaces for Tree-fitting and Hierarchical Clustering. In KDD 2022 - Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 201-211). (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining). Association for Computing Machinery. https://doi.org/10.1145/3534678.3539378

Deter, H. S., & Lu, T. (2022). Engineering microbial consortia with rationally designed cellular interactions. Current Opinion in Biotechnology, 76, 102730. https://doi.org/10.1016/j.copbio.2022.102730

Aguilar-Lopez, M., Wetzel, C., MacDonald, A., Ho, T. T. B., & Donovan, S. M. (2022). Metagenomic profile of the fecal microbiome of preterm infants consuming mother’s own milk with bovine milk–based fortifier or infant formula: a cross-sectional study. American Journal of Clinical Nutrition, 116(2), 435-445. https://doi.org/10.1093/ajcn/nqac081

Hoang, T. H., Zehni, M., Xu, H., Heintz, G., Zallek, C., & Do, M. N. (2022). Towards a Comprehensive Solution for a Vision-Based Digitized Neurological Examination. IEEE Journal of Biomedical and Health Informatics, 26(8), 4020-4031. https://doi.org/10.1109/JBHI.2022.3167927

Liechty, J. M., Keck, A. S., Sloane, S., Donovan, S. M., & Fiese, B. H. (2022). Assessing Transdisciplinary Scholarly Development: A Longitudinal Mixed Method Graduate Program Evaluation. Innovative Higher Education, 47(4), 661-681. https://doi.org/10.1007/s10755-022-09593-x

Huang, X., Xin, Y., & Lu, T. (2022). A systematic, complexity-reduction approach to dissect the kombucha tea microbiome. eLife, 11, [e76401]. https://doi.org/10.7554/eLife.76401

Zhang, S., Leistico, J. R., Cho, R. J., Cheng, J. B., & Song, J. S. (2022). Spectral clustering of single-cell multi-omics data on multilayer graphs. Bioinformatics, 38(14), 3600-3608. https://doi.org/10.1093/bioinformatics/btac378

Wang, X., Shih, H. Y., & Goldenfeld, N. (2022). Stochastic Model for Quasi-One-Dimensional Transitional Turbulence with Streamwise Shear Interactions. Physical review letters, 129(3), [034501]. https://doi.org/10.1103/PhysRevLett.129.034501

Zhang, C., Sashittal, P., Xiang, M., Zhang, Y., Kazi, A., & El-Kebir, M. (2022). Accurate Identification of Transcription Regulatory Sequences and Genes in Coronaviruses. Molecular biology and evolution, 39(7), [msac133]. https://doi.org/10.1093/molbev/msac133

Das, P., & Varshney, L. R. (2022). Explaining Artificial Intelligence Generation and Creativity: Human interpretability for novel ideas and artifacts. IEEE Signal Processing Magazine, 39(4), 85-95. https://doi.org/10.1109/MSP.2022.3141365

Naik, A., Varshney, L. R., Hassaneen, W., & Arnold, P. M. (2022). Letter: Development of Machine Learning-Based Models to Predict Treatment Response to Spinal Cord Stimulation. Neurosurgery, 91(1), e30. https://doi.org/10.1227/neu.0000000000002017

Ishaq, S. L., Wissel, E. F., Wolf, P. G., Grieneisen, L., Eggleston, E. M., Mhuireach, G., Friedman, M., Lichtenwalner, A., Otero Machuca, J., Weatherford Darling, K., Pearson, A. L., Wertheim, F. S., Johnson, A. J., Hodges, L., Young, S. K., Nielsen, C. C., Kozyrskyj, A. L., MacRae, J. D., Myers, E. M., ... Hosler, S. (2022). Designing the Microbes and Social Equity Symposium: A Novel Interdisciplinary Virtual Research Conference Based on Achieving Group-Directed Outputs. Challenges, 13(2). https://doi.org/10.3390/challe13020030

Xu, Y., Yang, J., Li, W., Song, S., Shi, Y., Wu, L., Sun, J., Hou, M., Wang, J., Jia, X., Zhang, H., Huang, M., Lu, T., Gan, J., & Feng, Y. (2022). Three enigmatic BioH isoenzymes are programmed in the early stage of mycobacterial biotin synthesis, an attractive anti-TB drug target. PLoS pathogens, 18(7 July), [e1010615]. https://doi.org/10.1371/journal.ppat.1010615

Ge, X., Goodwin, R. T., Yu, H., Romero, P., Abdelrahman, O., Sudhalkar, A., Kusuma, J., Cialdella, R., Garg, N., & Varshney, L. R. (2022). Accelerated Design and Deployment of Low-Carbon Concrete for Data Centers. In Proceedings of the 4th ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies, COMPASS 2022 (pp. 340-352). (ACM International Conference Proceeding Series; Vol. Par F180472). Association for Computing Machinery. https://doi.org/10.1145/3530190.3534817

Jankelow, A. M., Lee, H., Wang, W., Hoang, T. H., Bacon, A., Sun, F., Chae, S., Kindratenko, V., Koprowski, K., Stavins, R. A., Ceriani, D. D., Engelder, Z. W., King, W. P., Do, M. N., Bashir, R., Valera, E., & Cunningham, B. T. (2022). Smartphone clip-on instrument and microfluidic processor for rapid sample-to-answer detection of Zika virus in whole blood using spatial RT-LAMP. Analyst, 147(17), 3838-3853. https://doi.org/10.1039/d2an00438k

Abolfathi, M., Shomorony, I., Vahid, A., & Jafarian, J. H. (2022). A Game-Theoretically Optimal Defense Paradigm against Traffic Analysis Attacks using Multipath Routing and Deception. In SACMAT 2022 - Proceedings of the 27th ACM Symposium on Access Control Models and Technologies (pp. 67-78). (Proceedings of ACM Symposium on Access Control Models and Technologies, SACMAT). Association for Computing Machinery. https://doi.org/10.1145/3532105.3535015

Bandak, D., Goldenfeld, N., Mailybaev, A. A., & Eyink, G. (2022). Dissipation-range fluid turbulence and thermal noise. Physical Review E, 105(6), [065113]. https://doi.org/10.1103/PhysRevE.105.065113

Davis, E. C., Wang, M., & Donovan, S. M. (2022). Microbial Interrelationships across Sites of Breastfeeding Mothers and Infants at 6 Weeks Postpartum. Microorganisms, 10(6). https://doi.org/10.3390/microorganisms10061155

Bode, L., & Donovan, S. M. (2022). Fructooligosaccharides are not the same as Fucosylated Human Milk Oligosaccharides. Advances in Nutrition, 13(3), 972-973. https://doi.org/10.1093/advances/nmac033

Goyal, M., Serrano, G., Argemi, J., Shomorony, I., Hernaez, M., & Ochoa-Alvarez, I. (2022). JIND: Joint integration and discrimination for automated single-cell annotation. Bioinformatics, 38(9), 2488-2495. https://doi.org/10.1093/bioinformatics/btac140

Bhimaraju, A., Chatterjee, A., & Varshney, L. R. (2022). Expected Extinction Times of Epidemics With State-Dependent Infectiousness. IEEE Transactions on Network Science and Engineering, 9(3), 1104-1116. https://doi.org/10.1109/TNSE.2021.3131954

Colussi, J., Morgan, E. L., Schnitkey, G. D., & Padula, A. D. (2022). How Communication Affects the Adoption of Digital Technologies in Soybean Production: A Survey in Brazil. Agriculture (Switzerland), 12(5), [611]. https://doi.org/10.3390/agriculture12050611

Kara, A. D., Raginsky, M., & Yüksel, S. (2022). Robustness to incorrect models and data-driven learning in average-cost optimal stochastic control. Automatica, 139, [110179]. https://doi.org/10.1016/j.automatica.2022.110179

Mia, M. S., Abdelmeguid, M., & Elbanna, A. E. (2022). Spatio-Temporal Clustering of Seismicity Enabled by Off-Fault Plasticity. Geophysical Research Letters, 49(8), [e2021GL097601]. https://doi.org/10.1029/2021GL097601

Sutkus, L. T., Joung, S., Hirvonen, J., Jensen, H. M., Ouwehand, A. C., Mukherjea, R., Donovan, S. M., & Dilger, R. N. (2022). Influence of 2′-Fucosyllactose and Bifidobacterium longum Subspecies infantis Supplementation on Cognitive and Structural Brain Development in Young Pigs. Frontiers in Neuroscience, 16, [860368]. https://doi.org/10.3389/fnins.2022.860368

Spencer, T. E., Wells, K. D., Lee, K., Telugu, B. P., Hansen, P. J., Bartol, F. F., Blomberg, L., Schook, L. B., Dawson, H., Lunney, J. K., Driver, J. P., Davis, T. A., Donovan, S. M., Dilger, R. N., Saif, L. J., Moeser, A., McGill, J. L., Smith, G., & Ireland, J. J. (2022). Future of biomedical, agricultural, and biological systems research using domesticated animals. Biology of reproduction, 106(4), 629-638. https://doi.org/10.1093/biolre/ioac019

Oh, C., Sashittal, P., Zhou, A., Wang, L., El-Kebir, M., & Nguyen, T. H. (2022). Design of SARS-CoV-2 Variant-Specific PCR Assays Considering Regional and Temporal Characteristics. Applied and environmental microbiology, 88(7), [e0228921]. https://doi.org/10.1128/aem.02289-21

Tabatabaei, S. K., Pham, B., Pan, C., Liu, J., Chandak, S., Shorkey, S. A., Hernandez, A. G., Aksimentiev, A., Chen, M., Schroeder, C. M., & Milenkovic, O. (2022). Expanding the Molecular Alphabet of DNA-Based Data Storage Systems with Neural Network Nanopore Readout Processing. Nano letters, 22(5), 1905-1914. https://doi.org/10.1021/acs.nanolett.1c04203

Ellis, J. L., Wang, M., Fu, X., Fields, C. J., Donovan, S. M., & Booth, S. L. (2022). Feeding Practice and Delivery Mode Are Determinants of Vitamin K in the Infant Gut: An Exploratory Analysis. Current Developments in Nutrition, 6(3), [nzac019]. https://doi.org/10.1093/cdn/nzac019

Moreno, L. A., Meyer, R., Donovan, S. M., Goulet, O., Haines, J., Kok, F. J., & Van't Veer, P. (2022). Perspective: Striking a Balance between Planetary and Human Health-Is There a Path Forward? Advances in Nutrition, 13(2), 355-375. https://doi.org/10.1093/advances/nmab139

Hughes, R. L., Alvarado, D. A., Swanson, K. S., & Holscher, H. D. (2022). The Prebiotic Potential of Inulin-Type Fructans: A Systematic Review. Advances in Nutrition, 13(2), 492-529. https://doi.org/10.1093/advances/nmab119

Hornick, T., Richter, A., Harpole, W. S., Bastl, M., Bohlmann, S., Bonn, A., Bumberger, J., Dietrich, P., Gemeinholzer, B., Grote, R., Heinold, B., Keller, A., Luttkus, M. L., Mäder, P., Motivans Švara, E., Passonneau, S., Punyasena, S. W., Rakosy, D., Richter, R., ... Dunker, S. (2022). An integrative environmental pollen diversity assessment and its importance for the Sustainable Development Goals. Plants People Planet, 4(2), 110-121. https://doi.org/10.1002/ppp3.10234

Traniello, I. M., Hamilton, A. R., Gernat, T., Cash-Ahmed, A. C., Harwood, G. P., Ray, A. M., Glavin, A., Torres, J., Goldenfeld, N., & Robinson, G. E. (2022). Context-dependent influence of threat on honey bee social network dynamics and brain gene expression. Journal of Experimental Biology, 225(6), [jeb243738]. https://doi.org/10.1242/jeb.243738

Lee, N. M., Varshney, L. R., Michelson, H. C., Goldsmith, P., & Davis, A. (2022). Digital trust substitution technologies to support smallholder livelihoods in Sub-Saharan Africa. Global Food Security, 32, [100604]. https://doi.org/10.1016/j.gfs.2021.100604

Fung, T., O'Dwyer, J. P., & Chisholm, R. A. (2022). Effects of temporal environmental stochasticity on species richness: a mechanistic unification spanning weak to strong temporal correlations. Oikos, 2022(3), [e08667]. https://doi.org/10.1111/oik.08667

Shen, H., Huerta, E. A., O'Shea, E., Kumar, P., & Zhao, Z. (2022). Statistically-informed deep learning for gravitational wave parameter estimation. Machine Learning: Science and Technology, 3(1), [015007]. https://doi.org/10.1088/2632-2153/ac3843

Shomorony, I., & Heckel, R. (2022). Information-Theoretic Foundations of DNA Data Storage. Foundations and Trends in Communications and Information Theory, 19(1), 1-106. https://doi.org/10.1561/0100000117

Lundquist, A., McBride, B. A., Donovan, S. M., & Wszalek, M. (2022). Father support for breastfeeding mothers who plan to utilize childcare: A qualitative look at Mothers’ perspectives. Appetite, 169, [105854]. https://doi.org/10.1016/j.appet.2021.105854

Kern, J., Dupraz, E., Aïssa-El-Bey, A., Varshney, L. R., & Leduc-Primeau, F. (2022). Optimizing the Energy Efficiency of Unreliable Memories for Quantized Kalman Filtering. Sensors, 22(3), [853]. https://doi.org/10.3390/s22030853

Lehman, S. Y., Christman, L. E., Jacobs, D. T., Johnson, N. S. D. E. F., Palchoudhuri, P., Tieman, C. E., Vajpeyi, A., Wainwright, E. R., Walker, J. E., Wilson, I. S., LeBlanc, M., McFaul, L. W., Uhl, J. T., & Dahmen, K. A. (2022). Universal aspects of cohesion. Granular Matter, 24(1), [35]. https://doi.org/10.1007/s10035-021-01188-1

Xia, F., Allen, J., Balaprakash, P., Brettin, T., Garcia-Cardona, C., Clyde, A., Cohn, J., Doroshow, J., Duan, X., Dubinkina, V., Evrard, Y., Fan, Y. J., Gans, J., He, S., Lu, P., Maslov, S., Partin, A., Shukla, M., Stahlberg, E., ... Stevens, R. (2022). A cross-study analysis of drug response prediction in cancer cell lines. Briefings in bioinformatics, 23(1), [bbab356]. https://doi.org/10.1093/bib/bbab356

El-Kebir, M., Morris, Q., Oesper, L., & Sahinalp, S. C. (2022). Emerging Topics in Cancer Evolution. Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 27, 397-401.

Daniels, V. C., Monaco, M. H., Wang, M., Hirvonen, J., Jensen, H. M., Ouwehand, A. C., Mukherjea, R., Dilger, R. N., & Donovan, S. M. (2022). Evaluation of 2’-fucosyllactose and bifidobacterium longum subspecies infantis on growth, organ weights, and intestinal development of piglets. Nutrients, 14(1), [199]. https://doi.org/10.3390/nu14010199

Liu, J. M., Solem, C., Lu, T., & Jensen, P. R. (2022). Harnessing lactic acid bacteria in synthetic microbial consortia. Trends in Biotechnology, 40(1), 8-11. https://doi.org/10.1016/j.tibtech.2021.09.002

Levick, K., Heckel, R., & Shomorony, I. (2022). Achieving the Capacity of a DNA Storage Channel with Linear Coding Schemes. In 2022 56th Annual Conference on Information Sciences and Systems, CISS 2022 (pp. 218-223). (2022 56th Annual Conference on Information Sciences and Systems, CISS 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CISS53076.2022.9751151

Pan, C., Gabrys, R., Liu, X., Colbourn, C., & Milenkovic, O. (2022). Balanced and Swap-Robust Trades for Dynamical Distributed Storage. In 2022 IEEE International Symposium on Information Theory, ISIT 2022 (pp. 2385-2390). (IEEE International Symposium on Information Theory - Proceedings; Vol. 2022-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT50566.2022.9834794

Ravi, A. N., Vahid, A., & Shomorony, I. (2022). Capacity of the Shotgun Sequencing Channel. In 2022 IEEE International Symposium on Information Theory, ISIT 2022 (pp. 210-215). (IEEE International Symposium on Information Theory - Proceedings; Vol. 2022-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT50566.2022.9834409

Zhang, C., Sashittal, P., & El-Kebir, M. (2022). CORSID Enables de novo Identification of Transcription Regulatory Sequences and Genes in Coronaviruses. In I. Pe’er (Ed.), Research in Computational Molecular Biology - 26th Annual International Conference, RECOMB 2022, Proceedings (pp. 360-362). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13278 LNBI). Springer. https://doi.org/10.1007/978-3-031-04749-7_28

Edwards, C. G., Walk, A. M., Thompson, S. V., Reeser, G. E., Dilger, R. N., Erdman, J. W., Burd, N. A., Holscher, H. D., & Khan, N. A. (2022). Dietary lutein plus zeaxanthin and choline intake is interactively associated with cognitive flexibility in middle-adulthood in adults with overweight and obesity. Nutritional Neuroscience, 25(7), 1437-1452. https://doi.org/10.1080/1028415X.2020.1866867

Hanson, J., & Raginsky, M. (2022). Fitting an immersed submanifold to data via Sussmann's orbit theorem. In 2022 IEEE 61st Conference on Decision and Control, CDC 2022 (pp. 5323-5328). (Proceedings of the IEEE Conference on Decision and Control; Vol. 2022-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC51059.2022.9993382

Mazooji, K., Kannan, S., Noble, W. S., & Shomorony, I. (2022). Fundamental Limits of Multi-Sample Flow Graph Decomposition. In 2022 IEEE International Symposium on Information Theory, ISIT 2022 (pp. 2403-2408). (IEEE International Symposium on Information Theory - Proceedings; Vol. 2022-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT50566.2022.9834518

Raman, R. K., & Varshney, L. R. (2022). Information-Theoretic Approaches to Blockchain Scalability. In Springer Optimization and Its Applications (pp. 257-296). (Springer Optimization and Its Applications; Vol. 194). Springer. https://doi.org/10.1007/978-3-031-07535-3_8

Hawthorne, K. M., Castle, J., & Donovan, S. M. (2022). Meat Helps Make Every Bite Count An Ideal First Food for Infants. Nutrition Today, 57(1), 8-13. https://doi.org/10.1097/NT.0000000000000523

Markowitz, S., Snyder, C., Eldar, Y. C., & Do, M. N. (2022). Multimodal Unrolled Robust PCA for Background Foreground Separation. IEEE Transactions on Image Processing, 31, 3553-3564. https://doi.org/10.1109/TIP.2022.3172851

Saldi, N., Başar, T., & Raginsky, M. (Accepted/In press). Partially Observed Discrete-Time Risk-Sensitive Mean Field Games. Dynamic Games and Applications. https://doi.org/10.1007/s13235-022-00453-z

Bhimaraju, A., & Varshney, L. R. (2022). Scheduling Group Tests over Time. In 2022 IEEE International Symposium on Information Theory, ISIT 2022 (pp. 886-891). (IEEE International Symposium on Information Theory - Proceedings; Vol. 2022-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT50566.2022.9834434

Marla, L., Varshney, L. R., Shah, D., Prakash, N. A., & Gale, M. E. (2022). Short and Wide Network Paths. IEEE Transactions on Network Science and Engineering, 9(2), 524-537. https://doi.org/10.1109/TNSE.2021.3123311

Wu, X., Hanganu, A., Hoshino, A., & Varshney, L. R. (2022). Source Identification for Exosomal Communication via Protein Language Models. In 2022 IEEE 32nd International Workshop on Machine Learning for Signal Processing, MLSP 2022 (IEEE International Workshop on Machine Learning for Signal Processing, MLSP; Vol. 2022-August). IEEE Computer Society. https://doi.org/10.1109/MLSP55214.2022.9943418

Nguyen-Ho, T. L., Pham, M. K., Nguyen, T. P., Nguyen, H. D., Do, M. N., Nguyen, T. V., & Tran, M. T. (2022). Text Query based Traffic Video Event Retrieval with Global-Local Fusion Embedding. In Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022 (pp. 3133-3140). (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; Vol. 2022-June). IEEE Computer Society. https://doi.org/10.1109/CVPRW56347.2022.00353

Golm, R., Nahvi, M., Gabrys, R., & Milenkovic, O. (2022). The Gapped k-Deck Problem. In 2022 IEEE International Symposium on Information Theory, ISIT 2022 (pp. 49-54). (IEEE International Symposium on Information Theory - Proceedings; Vol. 2022-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT50566.2022.9834537

DeVille, L. (2022). The generalized distance spectrum of a graph and applications. Linear and Multilinear Algebra, 70(13), 2425-2458. https://doi.org/10.1080/03081087.2020.1803187