Headshot of Antony Williams, Ph.D.
April 20, 2021 11:00 a.m. - 12:00 p.m. ET

Antony J. Williams, Ph.D.

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.

Professional Headshot of Nilanjan Chatterjee, Ph.D.
April 20, 2021 11:00 a.m. - 12:00 p.m. ET

Nilanjan Chatterjee, Ph.D.

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.

Depiction of robotic humanoid emitting a blue light projection and DNA-affiliated letters from the back of its cranium.
April 13, 2021 - April 14, 2021

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.

Brick sign outside of building reading, Frederick National Laboratory for Cancer Research
April 08, 2021 9:00 a.m. - 6:00 p.m. ET

Industries, academia, and other organizations who are interested in competing for the contract to operate the Frederick National Laboratory for Cancer Research (FNLCR) are invited to attend “FFRDC Industry Day.” This will be an opportunity to learn more about the FNLCR’s mission, scientific programs/capabilities (like cancer data science), and the laboratory’s management, facilities, and business operations.

Headshot of Charles Wang, M.D., Ph.D.
April 07, 2021 11:00 a.m. - 12:00 p.m. ET

Charles Wang, M.D., Ph.D., M.P.H.

Dr. Charles Wang will address the need for guidance in selecting algorithms for accurate biological interpretations of varied data types acquired with different single-cell RNA sequencing platforms.

Headshot of Dr. Saurabh Jha
April 05, 2021 1:00 p.m. - 2:00 p.m. ET

Saurabh Jha, MBBS MRCS MS

In this installment of the NCI Imaging and Informatics Community Webinar, Dr. Saurabh Jha will share hypothetical case studies and the legal scholarship surrounding the question: who gets sued when the algorithm makes a diagnostic error?

Headshot of Bill Wysocki, Ph.D.
March 29, 2021 2:00 p.m. - 3:00 p.m. ET

Bill Wysocki

The NCI Genomic Data Commons' (GDC's) upcoming webinar will introduce new users to its portal and library of computational resources. GDC experts will also answer questions about the GDC and genomic analyses and also share upcoming features of the system. As a component within NCI’s Cancer Research Data Commons (CRDC), the GDC is a knowledge system for cancer that helps researchers share and access genomic, clinical, and biospecimen data and facilitates precision oncology.

Headshot of Christina Curtis, Ph.D.
March 25, 2021 12:00 p.m. - 1:00 p.m. ET

Christina Curtis, Ph.D.

In this Cancer Moonshot℠ seminar, Stanford University’s Dr. Christina Curtis will describe her work in NCI's Human Tumor Atlas Network and give an update on the human tumor atlases.

Xavier BofillDeRos, Ph.D.
March 24, 2021 2:00 p.m. - 3:00 p.m. ET

Xavier Bofill-De Ros, Ph.D.

At the next Cancer Genome Cloud’s (CGC's) monthly webinar series, NCI Research Fellow, Dr. Xavier Bofill-De Ros, will share his experiences leveraging the NCI Cancer Research Data Commons (CRDC) Cloud Resources to study microRNA and its mechanisms.

Headshot of Dr. Mohammad Sahraeian
March 24, 2021 11:00 a.m. - 12:00 p.m. ET

Mohammad Sahraeian, Ph.D.

Accurate detection of somatic mutations is challenging but critical to understanding how cancer forms and progresses. In this Data Science Seminar, Dr. Mohammad Sahraeian will demonstrate how a neural network called NeuSomatic can outperform conventional detection approaches that involve low coverage, low mutation frequency, damaged DNA, and/or ambiguous genomic regions.