Benjamin James

I am a graduate student at MIT CSAIL performing research in computational biology in Manolis Kellis's lab. I am an NSF Graduate Research Fellow and a Frederick (1953) and Barbara Cronin Fellow. Previously, I completed my Bachelor of Science at the University of Tulsa in both Computer Science and Mathematics.

Broad Institute website

CSAIL website

CSAIL personal website

You can find my CV here

E-mail: benjames at mit

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Publications

last updated 3 February 2021, see Google Scholar for up to date publications

Peer-reviewed

  • Carles A. Boix, Benjamin T. James, Yongjin P. Park, Wouter Meuleman, Manolis Kellis (2021). Regulatory genomic circuitry of human disease loci by integrative epigenomics. Nature [paper]
  • Benjamin T. James, Brain B. Luczak, Hani Z. Girgis (2018). MeShClust: an intelligent tool for clustering DNA sequences. Nucleic Acids Research [paper]
  • Brain B. Luczak, Benjamin T. James, Hani Z. Girgis (2017). A survey and evaluations of histogram-based statistics in alignment-free sequence comparison. Briefings in Bioinformatics [paper]
  • Andrzej Zielezinski, Hani Z Girgis, Guillaume Bernard, Chris-Andre Leimeister, Kujin Tang, Thomas Dencker, Anna K Lau, Sophie Roehling, JaeJin Choi, Michael S Waterman, Matteo Comin, Sung-Hou Kim, Susana Vinga, Jonas S Almeida, Cheong Xin Chan, Benjamin T. James, Fengzhu Sun, Burkhard Morgenstern, Wojciech M Karlowski (2019). Benchmarking of alignment-free sequence comparison methods. Genome Biology [paper]
  • Alfredo Velasco II, Benjamin T. James, Vincent D. Wells, Hani Z. Girgis (2019). Look4TRs: A de-novo tool for detecting simple tandem repeats using self-supervised hidden Markov models. Bioinformatics [paper]
  • Hani Z. Girgis, Benjamin T. James, Brian B. Luczak (2021). Identity: rapid alignment-free prediction of sequence alignment identity scores using self-supervised general linear models. NAR Genomics and Bioinformatics [paper]

Preprints

  • Benjamin T. James, Hani Z. Girgis (2019). MeShClust2: Application of alignment-free identity scores in clustering long DNA sequences. bioRxiv [paper]