During this month’s Cancer Genomics Cloud (CGC) webinar, bioinformaticians Dr. Vesna Pajic and Nevena Vukojicic will show attendees how to use CGC features to perform multi-omics analysis on data from The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC).

In this public workshop, participants, including data repository managers, will discuss the challenges and opportunities for researchers, institutions, and funders to establish effective data management and sharing practices.

The latest NCI Genomic Data Commons (GDC) monthly support webinar will cover using the GDC Application Programming Interface (API) to systematically access its data and tools.

Register to attend a hands-on workshop on connecting and analyzing the Proteomic Data Commons’ data within the Cancer Genomics Cloud powered by Seven Bridges.

Dr. Eliezer Van Allen will describe how a patient’s cancer genome can be used to guide individualized treatment choices for precision medicine. He will examine how to identify treatment resistance mechanisms and show how certain phenotypic patterns can be paired with new modes of computation to further inform treatment decisions.

In this webinar, MD Anderson Cancer Center Professor, Dr. Nicholas Navin, will present on breast cancer evolution through the lens of single-cell genomics.

Looking to leverage data sets that are available through the National Center for Biotechnology Information’s servers? In this webinar, Mr. Gargi Chhatwal will demo Amazon’s Athena: a serverless, interactive query service that makes it easy to analyze this data in Amazon Simple Storage Service.

This presentation will provide an overview of the “CompTox Chemicals Dashboard,” illustrating not only how it has developed into an integrated data hub for environmental data, but also how it provides a foundation to support both exposomics and metabolomics research.

This webinar’s speaker, Dr. Nilanjan Chatterjee, is known for foundational and methodological contributions to multiple areas of modern biomedical data science, including large-scale analysis of genetic associations, gene-environment interactions, polygenic risk scores, and predictive model building by synthesis of information from multiple data sources.

The National Human Genome Research Institute (NHGRI) Data Science Working Group is hosting this 2-day workshop to bring together members of the genomics and machine learning (ML) research communities. Discussions will examine the opportunities and obstacles underlying the application of ML methods to basic genome sciences and genomic medicine.