When we do differential measurements of proteins in cells/tissues and find out multiple changes or correlations, we often want to understand the cause-effect relations between them. CausalPath meticulously chains existing information in literature to find out links that suggest possible dependencies between proteomic changes. Integration of those possible relations generates a hypothesis of differential signaling between conditions. Find out more at www.causalpath.org.

Platelets are the smallest of the blood cells with a critical role in hemostasis. This project aims to thoroughly understand how the signaling mechanisms in platelets control its functional phenotypes. To investigate, we activate platelets under various additional perturbations, and measure phosphopeptides using mass spectrometry. Using CausalPath and other methods, we develop causal hypotheses and test them on platelets, eventually building a mechanistic model of platelet function.

Whole genome sequencing studies of individuals with disorders, such as ASD, identifies a set of novel gene mutations when compared to their parents and siblings, but majority of these are random innocuous mutations. It is a challenge to identify which of these de-novo mutations are actually functional in the development of the disorder. At the core of this project there is a critical observation: functional mutations in disease cohorts do not overlap in patients as much as random mutations. This is called mutual exclusivity of functional mutations. Searching for mutual exclusivity in mutation distributions can lead us to the functional ones. We previously developed Mutex for analyzing cancer somatic mutations. This project extends it to other diseases/disorders with germline de-novo mutations. Preprint available.