Tag: Bioinformatics

Jun 07

CANDLE: Scaling JDACS4C Machine Learning Algorithms to Unprecedented Magnitudes

                    This is the second of a series of posts that discuss the principles underlying the three-year collaborative program “Joint Design of Advanced Computing Solutions for Cancer (JDACS4C).” Investigators from the National Cancer Institute (NCI) and the Frederick National Laboratory for Cancer Research have been working collaboratively with …

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Permanent link to this article: https://ncip.nci.nih.gov/blog/candle-scaling-jdacs4c-algorithms-unprecedented-magnitudes/

May 17

Joint Design of Advanced Computing Solutions for Cancer (JDACS4C): The Right Collaboration at the Right Time to Accelerate Cancer Research

Authors of the blog

This is the first of a series of posts that discuss the pilot collaborative program “Joint Design of Advanced Computing Solutions for Cancer (JDACS4C)” being pursued by the National Cancer Institute (NCI) and the Department of Energy (DOE). Investigators from NCI and the Frederick National Laboratory for Cancer Research have been working collaboratively with experts …

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Permanent link to this article: https://ncip.nci.nih.gov/blog/joint-design-advanced-computing-solutions-cancer-jdacs4c-right-collaboration-right-time-accelerate-cancer-research/

Apr 05

NCI Requests Input on the Development of an Imaging Data Commons

By Stephen D Jett, Ph.D. AAAS Science & Technology Policy Fellow National Cancer Institute    In 2016, a Blue Ribbon Panel (BRP) was established, as part of the Beau Biden Cancer Moonshot, to make key recommendations that would support the Moonshot goals of accelerating progress in cancer research and breaking down barriers to developing new …

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Permanent link to this article: https://ncip.nci.nih.gov/blog/nci-requests-input-development-imaging-data-commons/

Jan 17

Artificial Intelligence in Cancer Diagnostics and Prognostics: Radiologists in the Driver’s Seat

Hugo Aerts, Ph.D.Hugo Aerts, Ph.D.

By Hugo Aerts, Ph.D. Director, Computational Imaging and Bioinformatics Laboratory (CIBL) Associate Professor, Harvard University In the past year, the use of Artificial Intelligence (AI) in radiology, also called “radiomics,” has been getting a lot of attention, mainly because of the progress Deep Learning (DL) has made from a sub-human performance to performance that is …

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Permanent link to this article: https://ncip.nci.nih.gov/blog/artificial-intelligence-cancer-diagnostics-prognostics-radiologists-drivers-seat/

Feb 13

Imaging: A Key Component of a Cancer Data Ecosystem

    By Edward Helton, Ph.D., Government Sponsor, CBIIT Clinical Imaging Program, Robert Nordstrom, Ph.D., Branch Chief, Imaging Guided Intervention Branch, and Eve Shalley, Program Manager, NCI CBIIT Cancer Informatics Branch Precision medicine has quickly moved to the forefront of clinical research and practice, and is particularly pertinent to cancer since cancer is a disease of the …

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Permanent link to this article: https://ncip.nci.nih.gov/blog/imaging-key-component-cancer-data-ecosystem/

Nov 29

Precision Medicine Inspires HPC

By Eric Stahlberg, Ph.D., Director, High Performance Computing Initiative, Data Science and Information Technology Program, Frederick National Laboratory for Cancer Research (FNLCR) The recent weeks have been momentous as the high-performance computing (HPC) community embraced the challenge of precision medicine.  The theme of this year’s leading international supercomputing conference, SC16,  was “HPC Matters” and it …

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Permanent link to this article: https://ncip.nci.nih.gov/blog/precision-medicine-inspires-hpc/

Jul 20

Cancer Data and Computation in the Cloud: One Path to Affordable Genomics Research

Dr. Gad Getz

By Gad Getz, Ph.D., Broad Institute / MGH The cost of DNA sequencing has dropped more than one million-fold over the last decade, making it increasingly possible to discover the genetic basis of cancer and response to treatment. Three challenges, however, impede this goal: 1) Analysts lack the resources to download, store and compute on …

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Permanent link to this article: https://ncip.nci.nih.gov/blog/cancer-data-computation-cloud-one-path-affordable-genomics-research/

May 06

Usable, Collaborative, Reproducible, and Extensible: Four Key Tenets of Cloud Computing

Brandi Davis-Dusenbery, Ph.D.

The Seven Bridges Cancer Genomics Cloud (CGC) is one of three pilot systems funded by the National Cancer Institute with the aim of co-localizing massive genomics datasets, like The Cancer Genomics Atlas (TCGA), alongside secure and scalable computational resources for analysis. TCGA comprises multidimensional matched tumor-normal data from over 11,000 patients and 33 cancer types. …

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Permanent link to this article: https://ncip.nci.nih.gov/blog/usable-collaborative-reproducible-extensible-four-key-tenets-cloud-computing/

Mar 15

NCI Data Catalog: Your One-Stop List for NCI Data

""Mervi Heiskanen, Ph.D.

If you aren’t aware of the NCI Data Catalog, you should check it out! The NCI Data Catalog is a consolidated listing of the publicly available data collections produced by NCI initiatives, including The Cancer Genome Atlas (TCGA), The Cancer Imaging Archive (TCIA) and Surveillance, Epidemiology, and End Results (SEER) database. The catalog has been …

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Permanent link to this article: https://ncip.nci.nih.gov/blog/your-one-stop-list-for-nci-datasets/

Feb 29

Informatics Community Crucial to the Cancer Moonshot

Warren Kibbe, Ph.D.

There has been a lot of press in the past couple of months about the “Cancer Moonshot,” first mentioned by Vice President Joe Biden in October 2015, and gaining steam recently with the President’s State of the Union address and an initial recommendation of $1 billion of funding. The White House released a Fact Sheet …

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Permanent link to this article: https://ncip.nci.nih.gov/blog/title-informatics-community-a-crucial-component-of-cancer-moonshot/