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General Departmental Seminar Series

ALGORITHMIC CHALLENGES AND BIOLOGICAL RESULTS IN
COMPUTATIONAL SYSTEMS BIOLOGY


Ryan Lilien, PhD
Dartmouth University
Tuesday, March 28th, 2006
4:00 p.m.
        Auditorium, Genetics/Biotechnology Center
425 Henry Mall

 

ABSTRACT

With the recent completion of the human genome project researchers are racing to determine the correlations between genomic sequence and protein expression, the structures and functions of these proteins and protein systems, and the molecular derangements present in disease.  This talk will
discuss a number of recent projects in Computational and Systems Biology with a focus on our work in developing efficient algorithms for (1) modeling of molecular flexibility using molecular ensembles for drug design and protein redesign (K*) and (2) analysis of mass spectrometry proteomics data of human blood sera for disease diagnosis (Q5).

     (1) We developed a novel algorithm for protein redesign, which combines a statistical mechanics-derived ensemble-based approach to computing the binding constant with the speed and completeness of a branch-and-bound pruning algorithm. In addition, we show that the state-of-the-art dead-end
elimination (DEE) pruning criteria can not be used directly in computing partition functions with energy minimization and extend the DEE framework to allow DEE to be incorporated into a hybrid ensemble-based mutation search incorporating DEE, A* search, and our ensemble-based scoring function K*.

     (2) Our algorithm, Q5, probabilistically classifies healthy vs. disease whole serum samples using mass spectrometry. The deterministic algorithm employs Principal Components Analysis (PCA) followed by Linear Discriminant Analysis (LDA) on whole spectrum Surface-Enhanced Laser Desorption/Ionization Time of Flight (SELDI-TOF) Mass Spectrometry (MS) data. Q5 identifies the masses of proteins present in different concentrations between the two states, thereby generating a complex multi-protein species 'fingerprint' of disease. Extensions of the Q5 algorithm may allow early prediction of treatment outcome and identification of disease subtypes.

Note: If you understand that, at a high-level, atoms come together to form molecules, then you have the necessary chemical and biological background for this talk.


; * * Systems Biology Job Candidate * *

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