Scheduled Seminars on 11/9/2011

Xiuwei Zhang at 11:00  Edit  Reschedule  Delete
Location: 8th floor conference room
Affiliation: Ecole Polytechnique Federale de Lausanne
Host: Teresa Przytycka

Phylogenetic Transfer of Knowledge: Extending Comparative Approaches with an Application to Transcriptional Regulatory Networks
Transcriptional regulatory networks are key to the understanding of biological systems. However, the experimental determination of these networks in the laboratory remains difficult and time-consuming, while current computational inference methods achieve only modest accuracy.

In this talk, I will present two new methods to obtain more accurate networks, for a collection of related organisms. Both methods make use of the known evolutionary relationships among these organisms to gain the improvement. The first method, ProPhyC, is a phylogenetic probabilistic model, with an associated maximum likelihood algorithm. It takes as input the networks to be refined for a family of organisms, the phylogeny, and a network evolutionary model, and outputs the refined version of the input networks. The second method, Tree Transfer Learning (TTL), is based on transfer learning theory. It takes the gene-expression data for the family of organisms as input, and learns the network structures for all the organisms at once, while taking advantage of the phylogenetic relationships. Both methods clearly outperform existing network inference algorithms.

A framework like ProPhyC or TTL, can be adapted to other biological data such as other biological networks, protein structure, functional elements in the genomes. More generally, both can be viewed as methods for knowledge transfer, using a phylogenetic approach, among multiple organisms. Such a phylogenetic transfer of knowledge goes beyond the widespread comparative approach which involves only pairwise comparisons.

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