I contribute to several open-source projects hosted on GitHub.

  • INDRA (the Integrated Network and Dynamical Reasoning Assembler) assembles information about biochemical mechanisms into a common format that can be used to build several different kinds of explanatory models. Sources of mechanistic information include pathway databases, natural language descriptions of mechanisms by human curators, and findings extracted from the literature by text mining. Mechanistic information from multiple sources is de-duplicated, standardized and assembled into sets of mechanistic Statements with associated evidence. Sets of Statements can then be used to assemble both executable rule-based models (using PySB) and a variety of different types of network models.
  • PySB. A rule-based language for modeling biochemical pathways embedded within Python. Facilitates the creation of transparent, reusable, and composable models. Built on top of the rule-based languages BNGL and Kappa and integrated with Numpy/Scipy/Matplotlib (see Publications).
  • Extrinsic Apoptosis Reaction Model, 2.0 (EARM 2). A family of biochemical models of the extrinsic apoptosis pathway, focused on exploring possible mechanisms for regulation of mitochondrial outer membrane permeabilization by the Bcl-2 protein family.
  • BayesSB. Markov chain Monte Carlo for parameter estimation of biological and biochemical models implemented in PySB.
  • EstCC. Scala package for calculating channel capacity, mutual information, and entropy for continuous and discrete variables.