The insideBIGDATA Guide to Healthcare & Life Sciences is a useful new resource directed toward enterprise thought leaders who wish to gain strategic insights into this exciting new area of technology. The guide provides an overview of the utilization of big data technologies as an emerging discipline in healthcare and life sciences. It explores the characteristics of this business strategy and the benefits of leveraging big data technologies within these sectors. It also touches on the challenges and future directions of big data and analytics in the healthcare and life sciences industries.
Intel Enterprise Edition for Lustre* Software has taken a leap toward greater enterprise capabilities and improved features for HPC with release of version 3.0. This latest version includes new security enhancements, dynamic LNET configuration support, ZFS snapshots, and other features asked for by the HPC community inside and outside the enterprise. Additionally, it adds the Intel Omni-Path Architecture drivers.
In this special guest feature, Sagar Anisingaraju, Chief Strategy Officer at Saama, discusses how new approaches to big data analytics are helping the pharmaceutical industry address major shifts toward value-based-care.
In a recently accepted manuscript titled “Deep learning applications for predicting pharmacological properties of drugs and drug repurposing using transcriptomic data”, scientists from Insilico Medicine, Inc located at the Emerging Technology Centers at Johns Hopkins University in collaboration with Datalytic Solutions and Mind Research Network presented a novel approach applying deep neural networks (DNNs) to predict pharmacologic properties of many drugs.
In this special guest feature, Rani Hublou, Chief Product Officer at Comprehend, provides her views on why pharmaceutical data is such a sticking point for the R&D process.
Arterys Inc., a privately-held company dedicated to deep learning medical imaging technology, continues to advance improved imaging capabilities bringing artificial intelligence called deep learning to the healthcare field, beginning with the heart.
You can now access the genome sequence data of 3,024 rice varieties that have been aligned and analyzed against five different reference genomes as an AWS Public Data Set. The data contains over 30 million genetic variations that span across all known and predicted rice genes, as well as potential regulatory regions surrounding these genes.
Sinequa, a leader in real-time Big Data search and analytics, today announced that UCB has selected the Sinequa Big Data Search & Analytics Platform to speed vital information discovery of its clinical trial file share.
Qubole, the big data-as-a-service company, announced that Station X, a leading developer of technologies that make large-scale human genome management and analysis easier, is using Presto on Qubole’s cloud-based big data platform to power GenePool™, a powerful software-as-a-service solution for real-time analytics of genomic and medical information.
This executive report is based on an in-depth study by the IBM Institute for Business Value research team. It looks at the current state of analytics across the healthcare ecosystem, including how organizations are implementing analytics strategies.