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The Leslie lab developed a machine learning method that predicts transcription factor activity from a tumor’s protein expression profile and vice versa. Inferred protein signatures from mRNA profiles were useful for predicting drug response and survival.
The Altan-Bonnet lab showed that T cell populations scale their production of the cytokine IL-2 to antigen abundance over a large dynamic range, independent of population size.
The Sander lab developed a computational method, Statius, to systematically predict metabolic vulnerabilities in tumor samples from genomic profiles.
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at MSKCC pursues computational and systems biology research and bioinformatics resource development in the following areas:
Using a workflow involving mouse models, clinical studies, metagenomic analyses and mathematical modeling, a probiotic candidate was identified that corrects a clinically relevant microbiome deficiency and may protect against C. difficile infection.
Buffie CG, Bucci V, Stein RR, et al. Nature 2015 Jan 8. more
Oqtans, an open-source workbench for quantitative transcriptome
analysis that is integrated in Galaxy.
Sreedharan VT, Schultheiss SJ, Jean G, et al. Bioinformatics 2014 May 1, Vol 30(9):1300-1. more
Entropy-enthalpy compensation: role and ramifications in biomolecular ligand recognition and design
Chodera JD, Mobley DL. Annu Rev Biophys. 2013;42:121-142.more
Explore cancer genomics data via the cBio Cancer Genomics Portal.
The CGDS R-package has been released.
NetBox version 1 has been released.
The Cancer Genome Atlas has announced the selection of six Genome Data Analysis Centers.
Explore cancer genes with Gene Ranker.