Cancer is a complex disease that results from a combination of genetic and environmental perturbations to biomolecular networks that, in healthy tissues, maintain a homeostatic balance between normal cellular functional states. Computational and statistical techniques for analyzing primary tumors, metastases, or cell culture systems can help us to understand cellular dysfunction underlying cancer onset, progression, and metastasis as well as to develop novel diagnostic and prognostic tools.
MicroRNAs (miRNAs) are small non-coding RNAs that can regulate gene expression and that are frequently altered in human cancers. Computational approaches can help us understand how miRNAs are dysregulated and potentially offer new therapies.
The goal of the CTD2 Network is to understand how tumor heterogeneity leads to drug resistance in order to develop optimal combinations of chemotherapy or small molecules in combination with immunotherapy.
From the analysis of over 11,000 tumors from 33 of the most prevalent forms of cancer, the Pan-Cancer Atlas provides a uniquely comprehensive, in-depth, and interconnected understanding of how, where, and why tumors arise in humans.
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The Cancer Research Institute (CRI) iAtlas is an interactive web-based platform and set of analytic tools for studying interactions between tumors and the immune microenvironment.
Data Coordinating Center for the Human Tumor Atlas Network
Our group had the privilege of being part of The Cancer Genome Atlas (TCGA), a landmark cancer genomics program that molecularly characterized over 20,000 primary cancer and matched normal samples spanning 33 cancer types.
The ISB Cancer Genomics Cloud (ISB-CGC) is democratizing access to NCI Cancer Data and coupling it with unprecedented computational power to allow researchers to explore and analyze this vast data-space.