Cell Maps for Quantitative Biology

Abstract:

Advances in molecular technologies have led to rapid generation of data and information about cellular processes at an increasing rate. Current means of knowledge representation and scientific communication in biology cannot adequately deal with the complexity and volume of this information – a serious bottleneck for developing a causal, predictive understanding of the cell.

Pathway Commons project aims to create a common language and platform for building cell maps – system level, integrated models of cellular processes. I will briefly talk about three applications of cell maps we developed to (i) find causal explanations to correlations in large scale high throughput tumor profiles, (ii) improve network inference algorithms, (iii) find metabolic tumor vulnerabilities. I will then focus on the challenges one needs to consider when using qualitative large scale models to inform executable models or statistical inferences. I will discuss possible approaches and available tools.