Gerstein, Mark

Supervised enhancer prediction with epigenetic pattern recognition and targeted validation

Sethi, A., Gu, M., Gumusgoz, E., Chan, L., Yan, K.-K., Rozowsky, J., Barozzi, I., Afzal, V., Akiyama, J. A., Plajzer-Frick, I., et al. (2020) · Nature Methods

Genomics and Chromatin DynamicsEpigenetics and DNA Methylation

Cited by 109

Neuronal and glial 3D chromatin architecture informs the cellular etiology of brain disorders

Hu, B., Won, H., Mah, W., Park, R. B., Kassim, B., Spiess, K., Kozlenkov, A., Crowley, C. A., Pochareddy, S., The PsychENCODE Consortium, et al. (2021) · Nature Communications

Genomics and Chromatin DynamicsGenetic Associations and Epidemiology

Cited by 103

Analysis of deletion breakpoints from 1,092 humans reveals details of mutation mechanisms

Abyzov, A., Li, S., Kim, D. R., Mohiyuddin, M., Stütz, A. M., Parrish, N. F., Mu, X. J., Clark, W., Chen, K., Hurles, M., et al. (2015) · Nature Communications

Genomic variations and chromosomal abnormalitiesGenome Rearrangement Algorithms

Cited by 91

Decoding neuroproteomics: integrating the genome, translatome and functional anatomy

Kitchen, R. R., Rozowsky, J. S., Gerstein, M. B., & Nairn, A. C. (2014) · Nature Neuroscience

Advanced Proteomics Techniques and ApplicationsBioinformatics and Genomic Networks

Cited by 63

Insights from incorporating quantum computing into drug design workflows

Lau, B., Emani, P. S., Chapman, J., Yao, L., Lam, T., Merrill, P., Warrell, J., Gerstein, M. B., & Lam, H. Y. K. (2023) · Bioinformatics

Computational Drug Discovery MethodsQuantum Computing Algorithms and Architecture

Cited by 54

Igniting language intelligence: The hitchhiker’s guide from chain-of-thought reasoning to language agents

Zhang, Z., Yao, Y., Zhang, A., Tang, X., Ma, X., He, Z., Wang, Y., Gerstein, M., Wang, R., Liu, G., et al. (2025) · ACM Computing Surveys

Topic ModelingNatural Language Processing Techniques

Cited by 51

Personal phenotypes to go with personal genomes

Snyder, M., Weissman, S., & Gerstein, M. (2009) · Molecular Systems Biology

Bioinformatics and Genomic NetworksHealth, Environment, Cognitive Aging

Cited by 46

Investigating Data Contamination in Modern Benchmarks for Large Language Models

Deng, C., Zhao, Y., Tang, X., Gerstein, M., & Cohan, A. (2024) · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 45

The human proteome – a scientific opportunity for transforming diagnostics, therapeutics, and healthcare

Vidal, M., Chan, D. W., Gerstein, M., Mann, M., Omenn, G. S., Tagle, D., Sechi, S., & Participants, W. (2012) · Clinical Proteomics

Advanced Proteomics Techniques and ApplicationsAdvanced Biosensing Techniques and Applications

Cited by 41

Establishing a Global Standard for Wearable Devices in Sport and Exercise Medicine: Perspectives from Academic and Industry Stakeholders

Ash, G. I., Stults-Kolehmainen, M., Busa, M. A., Gaffey, A. E., Angeloudis, K., Muniz-Pardos, B., Gregory, R., Huggins, R. A., Redeker, N. S., Weinzimer, S. A., et al. (2021) · Sports Medicine

Mobile Health and mHealth ApplicationsPhysical Activity and Health

Cited by 41

Relationship between gene co-expression and probe localization on microarray slides

Kluger, Y., Yu, H., Qian, J., & Gerstein, M. (2003) · BMC Genomics

Gene expression and cancer classificationBioinformatics and Genomic Networks

Cited by 36

BioCoder: a benchmark for bioinformatics code generation with large language models

Tang, X., Qian, B., Gao, R., Chen, J., Chen, X., & Gerstein, M. B. (2024) · Bioinformatics

Software Engineering ResearchTopic Modeling

Cited by 30

PARE: a tool for comparing protein abundance and mRNA expression data

Yu, E. Z., Burba, A. E. C., & Gerstein, M. (2007) · BMC Bioinformatics

Bioinformatics and Genomic NetworksAdvanced Proteomics Techniques and Applications

Cited by 20

STK11/LKB1 Loss of Function Is Associated with Global DNA Hypomethylation and S -Adenosyl-Methionine Depletion in Human Lung Adenocarcinoma

Koenig, M. J., Agana, B. A., Kaufman, J. M., Sharpnack, M. F., Wang, W. Z., Weigel, C., Navarro, F. C. P., Amann, J. M., Cacciato, N., Arasada, R. R., et al. (2021) · Cancer Research

Epigenetics and DNA MethylationLung Cancer Treatments and Mutations

Cited by 18

Positional artifacts in microarrays: experimental verification and construction of COP, an automated detection tool

Yu, H., Nguyen, K., Royce, T., Qian, J., Nelson, K., Snyder, M., & Gerstein, M. (2006) · Nucleic Acids Research

Gene expression and cancer classificationBioinformatics and Genomic Networks

Cited by 13

Investigating Data Contamination in Modern Benchmarks for Large Language Models

Deng, C., Zhao, Y., Tang, X., Gerstein, M., & Cohan, A. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 8

ChemAgent: Self-updating Library in Large Language Models Improves Chemical Reasoning

Tang, X., Hu, T., Ye, M., Shao, Y., Yin, X., Ouyang, S., Zhou, W., Lu, P., Zhang, Z., Zhao, Y., et al. (2025) · arXiv

Machine Learning in Materials ScienceMultimodal Machine Learning Applications

Cited by 4

MedicalAgentsBench for Complex Medical Reasoning: Comparing Internalized Reasoning Models versus Externalized Agent-based Frameworks

Shao, Y., Tang, X., Sohn, J., Chen, J., Liao, Y., Zhang, J., Xiang, J., Wu, F., Zhao, Y., Wu, C., et al. (2025) · arXiv

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 3

ML-Bench: Evaluating Large Language Models and Agents for Machine Learning Tasks on Repository-Level Code

Tang, X., Liu, Y., Cai, Z., Shao, Y., Lu, J., Zhang, Y., Deng, Z., Hu, H., An, K., Huang, R., et al. (2023) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 2