Search Contact
About
Research
Scientists
Resources
Events
Education
Data & Models
Computational Modeling
Education & Outreach
 



Computational Modeling

The Computational Modeling Core is focused on developing improved computational methods for use not only by TCNC investigators but also by the broader cancer community.

The Computational Modeling Core of the TCNC has three scientific foci: development of methods for extracting biological mechanism from large phosphoproteomic datasets; development of methods for using and analyzing dynamical systems models for biological networks; and development of methods for integrating proteomic and transcriptomic datasets. In addition, the Core is responsible for facilitating data-sharing among TCNC member labs.

Specific Aim 1 - Development of methods of integration of protein-protein interaction data and phosphopeptide databases
Specific Aim 2 - Enhancement of dynamic systems modeling capabilities
Specific Aim 3 - Enhancing integrated proteomic and transcriptomics network models


Publications

Alexopoulos L, Saez-Rodriguez J, Cosgrove B, Lauffenburger DA, Sorger PK. Networks reconstructed from cell response data reveal profound differences in signaling by Toll-like receptors and NFkB in normal and transformed human hepatocytes. Submitted.

Apgar JF, Toettcher JE, Endy D, White FM, Tidor B. Stimulus design for model selection and validation in cell signaling. PLoS Comput Biol. 2008 Feb 15; 4(2): e30.

Huang SS, Fraenkel E. Integrating proteomic, transcriptional, and interactome data reveals hidden components of signaling and regulatory networks. Sci Signal. 2009 Jul 28;2(81):ra40.

Joughin BA, Naegle KM, Huang PH, Yaffe MB, Lauffenburger DA, White FM. An integrated comparative phosphoproteomic and bioinformatic approach reveals a novel class of MPM-2 motifs upregulated in EGFRvIII-expressing glioblastoma cells. Mol Biosyst. 2009 Jan;5(1):59-67.

King BM, Tidor B. MIST: Maximum Information Spanning Trees for dimension reduction of biological data sets. Bioinformatics. 2009 May 1;25(9):1165-72.

Lazzara MJ, Lauffenburger DA. Quantitative modeling perspectives on the ErbB system of cell regulatory processes. Exp Cell Res. 2009 Feb 15;315(4):717-25.

Pritchard J, Cosgrove BD Hemann MT, Griffith LG, Wands J, Lauffenburger DA. Three-kinase inhibitor combination recreates multipathway effects of Geldanamycin analog on hepatocellular carcinoma cell death. Submitted.

Sorger PK. A reductionist's systems biology: opinion. Curr Opin Cell Biol. 2005 Feb;17(1):9-11.

Spencer SL, Gaudet S, Albeck JG, Burke JM, Sorger PK. Non-genetic origins of cell-to-cell variability in TRAIL-induced apoptosis. Nature. 2009 May 21;459(7245):428-32.

Wilkins AK, Barton PI, Tidor B. The Per2 negative feedback loop sets the period in the mammalian circadian clock mechanism. PLoS Comput Biol. 2007 Dec 14;3(12):e242.

Key Personnel  

Douglas Lauffenburger, Ph.D., Core Leader
Professor of Biological Engineering, Chemical Engineering, and Biology; Head, Dept. of Biological Engineering; David H. Koch Institute

Ernest Fraenkel, Ph.D.
Assistant Professor of Biological Engineering

Brian A. Joughin, Ph.D.
Research Scientist, David H. Koch Institute

Peter K. Sorger, Ph.D.
Professor of Biology and Biological Engineering, MIT; Professor of Systems Biology, Harvard Medical School

Bruce Tidor, Ph.D.
Professor of Biological Engineering and Computer Science

Michael Yaffe, Ph.D., M.D.
Professor of Biology and Biological Engineering, David H. Koch Institute

MIT
Home Home