Welcome to the CBIIT Speaker Series Wiki
The Institute for Systems Biology (ISB) Cancer Genomics Cloud (ISB-CGC) is one of three pilot projects funded by the NCI with the goal of democratizing access to the TCGA data by substantially lowering the barriers to accessing and computing over this rich dataset. The ISB-CGC is a cloud-based platform that will serve as a large-scale data repository for TCGA data, while also providing the computational infrastructure and interactive exploratory tools necessary to carry out cancer genomics research at unprecedented scales. The ISB-CGC will provide interactive and programmatic access to the TCGA data, leveraging many aspects of Google Cloud Platform including BigQuery and Compute Engine. The ISB-CGC aims to serve the needs of a broad range of cancer researchers ranging from scientists or clinicians who prefer to use an interactive web-based application to access and explore the rich TCGA dataset, to computational scientists who want to write their own custom scripts using languages such as R or Python, accessing the data through APIs, to algorithm developers who want to spin up thousands of virtual machines to analyze hundreds of terabytes of sequence data. The ISB-CGC will allow scientists to interactively define and compare cohorts, examine the underlying molecular data for specific genes or pathways of interest, and share insights with collaborators around the globe.
Open commons containing large amounts of public biomedical data from the research community have the potential to speed up the pace of medical research. We describe the development of a large-scale open source data commons for genomic and associated clinical data and some of our experiences with it. We also discuss some of the different public and private data partnerships that are emerging for sharing genomic data.
The DataONE repository network, California Digital Library and Public Library of Science (PLOS) from October 2014–October 2015, works on a National Science Foundation-funded project to explore metrics — including citations, downloads and social media — for about 150,000 datasets. This presentation will summarize the major hurdles to make this work, the most important findings, and some ideas to go forward, including implementation as a production service.
SYNOPSIS: With each successive discovery in genetics, the true dynamic complexity of the genome has become increasingly apparent, requiring relatively consistent updates to the technical definition of the word "gene." It is now understood that the majority of human genes produce multiple functional products, or isoforms, primarily through alternative transcription and alternative splicing. Different isoforms within the same gene have been shown to participate in different functional pathways, and the altered expression of specific isoforms have been associated with numerous diseases. While the recent advances in NGS are facilitating the goal of studying gene regulation at isoform-level, there are a number of informatics challenges and difficulties that need to be addressed to improve the current state and fulfill the promise of studying gene regulation at gene isoform-level. Dr. Davuluri will present some of the recent approaches developed by our group, with an emphasis on how those methods have led to the development of a diagnostic assay for molecular sub-typing of cancer patients. In particular, he will challenge the use of basic gene-centric approaches in cancer genomics and argue that one should go beyond simple gene-based analyses but also consider isoform-level information that include gene expression/regulation of splice-variants. Looking forward, Dr. Davuluri will discuss the integrative application of different statistical and data-mining approaches to derive platform-independent classification models for identification of isoform-level gene signatures for cancer subtyping.
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