In this video, Jonathan Allen from LLNL describes how Lawrence Livermore’s supercomputers are playing a crucial role in advancing cancer research and treatment. “A historic partnership between the Department of Energy (DOE) and the National Cancer Institute (NCI) is applying the formidable computing resources at Livermore and other DOE national laboratories to advance cancer research and treatment. Announced in late 2015, the effort will help researchers and physicians better understand the complexity of cancer, choose the best treatment options for every patient, and reveal possible patterns hidden in vast patient and experimental data sets.”
In this video, Dr. Dimitri Kusnezov from the U.S. Department of Energy National Nuclear Security Administration presents: Supercomputing the Cancer Moonshot and Beyond. “How can the next generation of supercomputers unlock biomedical mysteries that will shape the future practice of medicine? Scientists behind the National Strategic Computing Initiative, a federal strategy for investing in high-performance computing, are exploring this question.”
Adam Buntzman and his colleagues at the University of Arizona recently developed a tool that uses CyVerse supercomputing resources to create the first nearly comprehensive map of the human immunome, all the possible immune receptors our bodies can make. “When people go to a clinic, it’s usually because they’re already sick,” Buntzman said. “If doctors could detect cancerous cells before they grow drastically out of proportion to healthy cells, patients would have much higher odds of successful cancer treatment and survival.”
Computer scientists at LLNL and Norwegian researchers are collaborating to apply high performance computing to the analysis of medical data to improve screening for cervical cancer. The team is developing a flexible, extendable model that incorporates new data such as other biomolecular markers, genetics and lifestyle factors to individualize risk assessment, according to Abdulla. “We want to identify the optimal interval for screening each patient.”
In this video from the DDN booth at SC15, Dr. Erik Deumens of the University of Florida describes why unpredictable and less standard architectures and system configurations are necessary to meet the agility, availability and responsiveness requirements to meet the mission of innovation and exploration. “The University of Florida’s Interdisciplinary Center for Biotechnology Research (ICBR) offers access to cutting-edge technologies designed to enable university faculty, staff and students, as well as research and commercial partners worldwide with the tools and resources needed to advance scientific research.”
In this video from the HPC in the Cloud Educational Series, Marco Novaes, Solutions Engineer with the Google Cloud Platform team explains how the Broad Institute was able to use Google Pre-Emptible VMs to leverage over 50,000 cores to advance cancer research. “Cancer researchers saw value in a highly-complex genome analysis, but even though they already had powerful processing systems in-house, running the analysis would take months or more. We thought this would be a perfect opportunity to utilize Google Compute Engine’s Preemptible VMs to further their cancer research, which was a natural part of our mission. And now that Preemptible VMs are generally available, we’re excited to tell you about this work.”
Today DDN announced that the University of Miami’s Center for Computational Science (CCS) has deployed high-performance, DDN GS12K scale-out file storage to speed scientific discoveries and boost collaboration with researchers around the world. CCS maintains one of the largest centralized academic cyberinfrastructures in the country, which fuels vital and critical discoveries in Alzheimer’s, Parkinson’s, gastrointestinal cancer, paralysis and climate modeling as well as marine and atmospheric science research.
Linding Lab at the University of Copenhagen used an SGI UV system to discover how genetic diseases such as cancer systematically attack the networks controlling human cells. By developing advanced algorithms to integrate data from quantitative mass-spectrometry and next generation sequencing of tumor samples, the UCPH researchers have been able to uncover cancer related changes to phospho-signaling networks at a global scale. The studies are some of the early results of the strategic collaboration between SGI and the Linding Lab at UCPH. The landmark findings have been published in two back-to-back papers in today’s Cell journal.
In this video from IDF 2015, Intel and Oregon Health & Science University (OHSU) announce the Collaborative Cancer Cloud, a precision medicine analytics platform that allows hospitals and research institutions to securely share patient genomic, imaging, and clinical data for potentially lifesaving discoveries.
In this podcast, Karen Vasquez and Albino Bacolla of the University of Texas at Austin describe how TACC supercomputers have helped scientists find a surprising link between cross-shaped pieces of DNA and human cancer.