1. The Multi-perturbation Shapley value Analysis (MSA) is a framework for deducing causal function localization from multiple perturbations data. It provides insights to the workings of a given system, the "players" taking part in carrying out the different functions and the functional interactions between those "players". Learn more here.

2. The ADIOS (Automatic DIstillation Of Structure) project addresses the problem, fundamental to linguistics, bioinformatics and certain other disciplines, of using corpora of raw symbolic sequential data to infer underlying rules that govern their production. Given a corpus of strings (such as text, transcribed speech, nucleotide base pairs, amino acid sequence data, musical notation, etc.), our unsupervised algorithm recursively distills from it hierarchically structured patterns. Learn more here.

3. The Functional Influence Network (FIN) is a framework for studying gene networks from multiple knockouts data. In difference from existing approaches, which aim to reveal the network of interactions between genes, this method aims to identify functional networks, describing how given cellular functions are carried out by the genes studied. In the resulting network description obtained by the FIN, the genes’ states determine a quantitative phenotype of the network and the network’s architecture visualizes and explains how the studied function is actually carried out. Learn more here.

4. The Pepitope Server - provides epitope mappings using affinity-selected peptides.

5. Other projects carried out in the lab include the analysis of metabolic networks via constraint-based modeling; and the computational study of evolutionary questions.

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Background image adapted with permission from the E.Coli metabolic map
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Last updated: 9:7, 9/6/2013