Identification of Cervical Cancer Key Regulators using Network Biology Approach - Supplementary tables

This data contains large supplementary tables for the PhD dissertation of Dariia Vyshenska. Title of the Dissertation: "Identification of Cervical Cancer Key Regulators using Network Biology Approach" Dataset contains data from two researches. Research #1: Identification of bacterial regulators of cervical cancer gene expression. It contains microbial community's data from cervical cancer samples of human patients. Prevotella bivia was identified as a key bacterial regulator of cervical cancer gene expression using reconstruction of transkingdom network from patient's gene expression and bacterial abundance data. The data contains transkingdom network, information about bacteria found in each sample of cervical cancer, qRT PCR primers that were used to test host genes for being regulated by P. bivia. Research #2: Identification of key cervical cancer driver genes and their combinations that are critical for cancer proliferation. We identified 9 host genes responsible for cancer cell growth and identified the pairs of these driver genes that have the highest impact on the cancer proliferation. To achieve this goal, we identified targets of each driver gene and reconstructed gene co-expression network out of the union of these targets. The data contains gene co-expression network, qRT PCR primers for 34 tested potential drivers, network measurements for each confirmed driver gene (average shortest path, number of proliferation associated targets), and proliferation measurements for single driver or driver pairs knock downs.