Nicolas Borisov , Alexander Aliper , Ksenia Lezhnina , Denis Shepelin, Michael Korzinkin , Artem Artemov, Qinsong Zhu, Alex Zhavoronkov and Anton Buzdin
Pharmaceuticals, Rms 2702-3, 27th Floor, Bank of East Asia Harbour View Centre, 56 Gloucester Road, Wan Chai, Hong Kong
Analysis of complete transcriptomes and proteomes is complicated by the problems with understanding overall functional conclusions basing on the large-scale gene expression figure. We report a computational biomedical technique termed OncoFinder, which enables performing both quantitative and qualitative analysis of the intracellular signaling and metabolic pathway activation. This method is universal and may be used for the analysis of any physiological, stress, malignancy and other specific conditions at the molecular level. In contrast to other techniques, OncoFinder utilizes an algorithm that distinguishes functional roles of every gene product in each pathway. OncoFinder showed a strong potential to neutralize batch effects and platform-specific differences for the experimental data obtained using NGS, microarray hybridization and proteome wide techniques. This approach allowed us to characterize new pathway signatures as better markers of cancer progression compared to individual gene products. OncoFinder also enables to correlate pathway activation with the success of medical treatment. We created a new biodata management platform and a software available to the academic community. The authors enthusiastically look for building international collaborations and partnerships in theoretical and applied biomedicine.