Hoffman research group

Michael M. Hoffman

We develop machine learning techniques to better understand chromatin biology. These models and algorithms transform high-dimensional functional genomics data into interpretable patterns and lead to new biological insight.

Software

  • Segway: semi-automated genomic annotation
  • Segtools: segmentation analysis and graphics
  • Genomedata: efficient storage and retrieval
  • Umap and Bismap: tools for quantifying mappability of the genome and methylome
  • BEHST: biological enrichment of hidden sequence targets
  • Virchip: predicting transcription factor binding by learning from the transcriptome
  • PeaKO: finding transcription factor binding motifs using knockout controls

Databases

  • DNAmod: the DNA modification database

People

Meet the team

  • Michael Hoffman
  • Eric Roberts
  • Coby Viner
  • Linh Huynh
  • Annie Lu
  • Luomeng Tan
  • Mary Agopian
  • Gergely Pap
  • Yahan Zhang
  • Natalia Mukhina

News

Contact

  •  
  • Twitter: @michaelhoffman
  • LinkedIn: michaelmhoffman