My group develops algorithms and software to facilitate the analysis and interpretation of large-scale genomic datasets. Source code is made freely available, mostly through GitHub. Follow the links below (sorted by most recent paper) for more information and please let us know if any of these tools helped you in your research.


The following are links to repositories that contain supplementary data and scripts to reproduce analyses in some of our papers (sorted by most recent paper).

  • FindrCausalInferenceOnYeast – Python code to reproduce the causal networks inferred from differential gene expression in yeast. [Homepage][BioRxiv 2020]
  • GraphFeatureAutoencoder – Code to implement graph feature auto-encoders to predict expression data using biological networks. [Homepage][arXiv 2020]
  • VSG analysis – Scripts for the analysis of a PacBio dataset of expressed antigen diversity in T. brucei infections. [Homepage] [PLOS Path 2019]
  • DHSgen – A list of high-confidence predicted interactions between regulatory genome regions and their target genes. [Homepage] [arXiv 2014]
  • RNA regulon-omics – A portal for molecular biologists who wish to design detailed hypotheses from a large-scale, top-down analysis of posttranscriptional regulation in yeast. [Homepage] [NAR 2011]