RT Journal Article
SR Electronic
T1 Hilbert-Schmidt and Sobol sensitivity indices for static and time series Wnt signaling measurements in colorectal cancer
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 035519
DO 10.1101/035519
A1 shriprakash sinha
YR 2015
UL http://biorxiv.org/content/early/2015/12/28/035519.abstract
AB Ever since the accidental discovery of Wingless [Sharma R.P., Drosophila information service, 1973, 50, p 134], research in the field of Wnt signaling pathway has taken significant strides in wet lab experiments and various cancer clinical trials augmented by recent developments in advanced computational modeling of the pathway. Information rich gene expression profiles reveal various aspects of the signaling pathway at work and help in studying different issues simultaneously. Hitherto, not many computational studies exist which incorporate the simultaneous study of these issues. This manuscript is an endeavour to • explore the strength of contributing factors in the signaling pathway, • analyze the existing causal relations among the inter/extracellular factors effecting the pathway based on prior biological knowledge and • investigate the recently found prevalence of psychophysical laws working in the pathway in a multi-parameter setting. To achieve this goal, local and global sensitivity analysis is conducted on the (non)linear responses between the factors, obtained from static and time series expression profiles, using the density (Hilbert-Schmidt Information Criterion) and variance (Sobol) based sensitivity indicies. The results in the manuscript show the superiority of the density based indices in comparison to the use of variance based indices mainly due to the former’s employment of distance measures using the kernel trick via Reproducing kernel Hilbert space (RKHS) that capture nonlinear relations among various intra/extracellular factors of the pathway in a higher dimensional space. In time series data, using these indices it is now possible to observe where in time, which factors get influenced as well as contribute to the pathway as changes in concentration of the other factors are made. This synergy of prior biological knowledge, sensitivity analysis indices and representations in higher dimensional spaces facilitates the above study to reveal a rich amount of hidden biological information within the data from colorectal cancer samples.