Jan 27, 2023 · Life Sciences. We're working on groundbreaking research aiming to revolutionize the field of life sciences. We're solving some of the most important issues humanity faces with artificial intelligence, developing novel and unconventional computing structures, as well as mathematical and computational modeling.

Jan 5, 2023 · Healthcare and Life Sciences. The combination of increasingly powerful computers and AI offers the possibility to be able to detect, diagnose, and cure diseases like never before. At IBM Research, we’re working on creating software and AI systems that can convert reams of health data into useable information for clinicians the world over. Our ...

Technology has tremendous potential to be a primary catalyst for transformation in the healthcare and life sciences industry. Today a convergence of computing revolutions is taking place that will help accelerate the rate of scientific discovery.

The term life sciences refers to the disciplines that study living organisms and life processes, and include chemistry, biology, medicine, and a range of other related disciplines. Research efforts in life sciences are heavily data-driven, as they produce and consume vast amounts of scientific data, much of which is intrinsically relational and ...

Mar 21, 2023 · In late 2021, Cleveland Clinic and IBM entered into a landmark 10-year partnership to use emerging technologies to help crack some of the biggest challenges in healthcare and life sciences. Using a combination of state-of-the-art high-performance hybrid cloud computing, next-generation AI, and quantum computing, the goal was to create a ...

In this review, we list methods for the generation and manipulation of microfluidic hydrodynamic confinements in free-flowing liquids and near surfaces, and elucidate the associated underlying theory and discuss their utility in the emerging area of open space microfluidics applied to …

Life sciences researchers are under pressure to innovate faster than ever. Big data offer the promise of unlocking novel insights and accelerating breakthroughs. Ironically, although more data are available than ever, only a fraction is being integrated, understood, and analyzed.

Michal has published more than 70 peer-reviewed papers that were cited more than 6400 times according to Google Scholar. She is a member of the iScience Editorial Advisory Board, PlosOne editor, a co-leader of the AI Alliance for drug discovery working group and a board member of the International Network for Life Sciences, AI-LIFE.

Foundation models for Targets Discovery. Targets discovery models learn the representation of DNA, bulk RNA, single-cell RNA expression data and other cell level signaling information for the identification of novel diagnostic and therapeutic targets, allowing tasks such as cell type annotation and classification, gene perturbation prediction, disease state prediction, splice …

Dr. Filippo Utro is a Senior Research Scientist in computational genomics within the Healthcare and Life Sciences research team at the IBM T. J. Watson Research Center in Yorktown Heights, NY. Filippo's research is focused on designing algorithms for various omics data on different diseases and organisms.