Professor of Computer Science and the Lewis Sigler Institute for Integrative Genomics.

Areas of Research: Computational molecular biology, as well as its interface with machine learning and algorithms
Department|Program:
  • Computer Science and the Lewis-Sigler Institute for Integrative Genomics

msingh@cs.princeton.edu
Research Lab
609-258-2087
250 Carl Icahn Laboratory

Faculty Assistant:
Marybeth Fedele
fedele@princeton.edu
609-258-7058
Website

Computational molecular biology

My group develops algorithms for a diverse set of problems in computational molecular biology. We are particularly interested in predicting specificity in protein interactions and uncovering how molecular interactions and functions vary across context, organisms and individuals. We leverage high-throughput biological datasets in order to develop data-driven algorithms for predicting protein interactions and specificity; for analyzing biological networks in order to uncover cellular organization, functioning, and pathways; for uncovering protein functions via sequences and structures; and for analyzing proteomics and sequencing data. An appreciation of protein structure guides much of our research.

 


Selected Publications

  • Munro D, Ghersi D, Singh M. 2018 Two critical positions in zinc finger domains are heavily mutated in three human cancer types. PLoS Comput Biol. 14(6):e1006290. Pubmed
  • Hristov, B, and Singh, M. (2017) Network-based coverage of mutational profiles reveals cancer genes. Cell Systems. 5:221. Pubmed
  • Przytycki, P, and Singh, M. (2017) Diffrential analysis between somatic mutation and germline variation profiles reveals cancer-related genes. Genome Medicine. 9:79. Pubmed
  • Ochoa, A, and Singh, M. (2017) Domain prediction with probabilistic directional context. Bioinformatics. 33: 2471-2478. Pubmed
  • Pritykin, Y, Brito, T, Schupbach, T, Singh, M, Pane, A. (2017) Integrative analysis unveils new functions for the drosophila cutoff protein in non-coding RNA biogenesis and gene regulation. RNA. 7: 1097-1109. Pubmed
  • Ochoa A, Storey J, Llinás M, Singh M. (2015) Beyond the E-value: Stratified statistics for protein domain prediction. PLOS Computational Biology. 11:e1004509 PubMed
  • Pritykin Y, Ghersi D, Singh M. (2015) Genome-wide detection and analysis of multifunctional genes. PLOS Computational Biology. 11:1004467. PubMed
  • Nadimpalli S, Persikov AV, Singh M. (2015) Pervasive variation of transcription factor orthologs contributes to regulatory network evolution. PLoS Genet. 11(3): e1005011. Pubmed
  • Persikov AV, Wetzel JL, Rowland EF, Oakes BL, Xu DJ, Singh M, Noyes MB. (2015) A systematic survey of the Cys2His2 zinc finger DNA-binding landscape. Nucleic Acids Res. 43(3): 1965-84. Pubmed
  • Ghersi D, Singh M. (2014) molBLOCKS: decomposing small molecule sets and uncovering enriched fragments. Bioinformatics. 30: 2081-3. Pubmed
  • Jiang P, Singh M, Coller HA. (2013) Computational assessment of the cooperativity between RNA binding proteins and MicroRNAs in Transcript Decay. PLoS Comput Biol. 9: e1003075. Pubmed
  • Jiang P, Singh M. (2013) CCAT: Combinatorial Code Analysis Tool for transcriptional regulation. Nucleic Acids Res. 42: 2833-47. Pubmed
  • Ghersi D, Singh M. (2013) Interaction-based discovery of functionally important genes in cancers. Nucleic Acids Res. 42: e18. Pubmed
  • Persikov AV, Rowland EF, Oakes BL, Singh M, Noyes MB. (2013) Deep sequencing of large library selections allows computational discovery of diverse sets of zinc fingers that bind common targets. Nucleic Acids Res. 42: 1497-508. Pubmed
  • Pritykin Y, Singh M. (2013) Simple topological features reflect dynamics and modularity in protein interaction networks. PLoS Comput Biol. 9: e1003243. Pubmed

View complete list of Publications.