TY - JOUR T1 - Prioritizing 2nd and 3rd order interactions via support vector ranking using sensitivity indices on time series Wnt measurements - Part B JF - bioRxiv DO - 10.1101/060228 SP - 060228 AU - Shriprakash Sinha Y1 - 2016/01/01 UR - http://biorxiv.org/content/early/2016/06/22/060228.abstract N2 - It is widely known that the sensitivity analysis plays a major role in computing the strength of the influence of involved factors in any phenomena under investigation. When applied to expression profiles of various intra/extracellular factors that form an integral part of a signaling pathway, the variance and density based analysis yields a range of sensitivity indices for individual as well as various combinations of factors. These combinations denote the higher order interactions among the involved factors. Computation of higher order interactions is often time consuming but they give a chance to explore the various combinations that might be of interest in the working mechanism of the pathway. For example, in a range of fourth order combinations among the various factors of the Wnt pathway, it would be easy to assess the influence of the destruction complex formed by APC, AXIN, CSKI and GSK3 interaction. But the effect of these combinations vary over time as measurements of fold changes and deviations in fold changes vary. In this work, after estimating the individual effects of factors for a higher order combination, the individual indices are considered as discriminative features. A combination, then is a multivariate feature set in higher order (>2). With an excessively large number of factors involved in the pathway, it is difficult to search for important combinations in a wide search space over different orders. Exploiting the analogy with the issues of prioritizing webpages using ranking algorithms, for a particular order, a full set of combinations of interactions can then be prioritized based on these features using a powerful ranking algorithm via support vectors. Recording the changing rankings of the combinations over time reveals of how higher order interactions behave within the pathway and when an intervention might be necessary to influence the interaction within the pathway. This could lead to development of time based therapeutic interventions. Code has been made available on Google drive at drive.google.com/folderview?id=0B7Kkv8wlhPU-V1Fkd1dMSTd5ak0&usp=sharing ER -