Big data integrated environment for computational analysis of cancer omics data

Abstract

Abstract newlineThe thesis is divided into five chapters. The first chapter provided an overview of multi- omics data with respect to sources, tools, methods and various computational approaches to handle big data shown in Figure i. It presents a comprehensive case study performed for the identification of putative biomarkers for breast cancer based on text mining and network-based approach generated gene-drug (GDI), gene-protein (GPI) and oncogenic pathway interaction networks. The second chapter consists of comprehensive molecular docking and dynamics studies and identification of potential multi-drug targets based on drug repurposing approach using chemotherapy drugs. We also identified novel twenty lead molecules by enumeration of virtual library. Third chapter emphasizes on the screening of natural products using in-silico and in-vitro studies. In-vitro studies were carried out for natural compounds using MCF-7 cell line with cytotoxicity, scratch assays and the apoptotic activity was investigated using flow cytometry (FACS) analysis. Further, in-silico validation was carried out by performing molecular docking of apoptotic targets against natural compounds. We observed the stability of best-docked apoptotic target by performing molecular dynamics simulation at 100 ns. These comprehensive studies have shown a good correlation between in-silico and wet lab studies. newlineFourth chapter deals with the designing and development of an integrated cancer omics profiles environment. Here, we developed a user-friendly web-based cancer omics portal Multi-omics Cancer Discovery Portal (MCDP 1.0) that addresses this need and allows users to systematically analyze high-throughput cancer omics data with customizable steps and interactive visualizations. The aim of the portal is to provide easy access to ten types of cancer data. The MCDP 1.0 has two major analytical modules, OncoFinder and OncoInterpreter. OncoFinder allows users to search for attributes that are associated with a query and analyze the results. OncoInterpreter help