[Colloquium] TTIC Talk: Alexander Schoenhuth, UC Berkeley

[Julia MacGlashan]

When:             *Friday, Apr 2 @ 11:00am*

Where:           * TTIC Conference Room #526*, 6045 S Kenwood Ave, 5th Floor


Who:              * **Alexander Schoenhuth*, UC Berkeley


Title:          *      **Classifying Cancer Tissue by Inferring Systemic
Markers*****



 There has been recent evidence that protein-protein interaction (PPI)
subnetworks which exhibit synergistic differential gene expression in
tumorigenic phenotypes are more accurate than single gene markers when it
comes to classifying such phenotypes. Here we compute markers as connected
subnetworks in confidence-scored PPI networks which achieve high overall
confidence scores and are dysregulated in a sufficient number of patients.
We do this by employing a novel, exhaustive search technique which, for the
first time, renders the inherent search problem on weighted-edge networks
tractable. We compute p-values for the resulting subnetworks and use the
most significant candidates for classification purposes. Thereby we obtain
sets of systemic markers which are superior in terms of gene ontology (GO)
term enrichment. As a result, we outperform all prior approaches when
classifying colon cancer versus healthy tissue.

Before that, I will briefly sketch how to identify hidden Markov processes.
Identifiability of hidden Markov processes has remained a driving question
since their introduction to the related communities. I obtain my answers
through usage of algebraic statistics, an emerging area of research whose
core theme is to treat application-driven concepts from
 statistics / statistical learning theory and computational biology in
algebraic and geometric settings.

Host:              Jinbo Xu, j3xu at ttic.edu
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