AstraZeneca's new Cancer Discovery paper defines what a pharma data fabric needs to look like for AI agents. Misha Kapushesky on FAIR+T, semantic layers, and what's harder than the paper suggests.
At Bio-IT 2025, Genestack and Dr. Sehyun Oh (CUNY) showcased their collaboration using ODM and OmicsMLRrepoR to harmonize public omics data making it FAIR and AI-ready.
Unlock new insights in brain research with Genestack’s Open Data Manager (ODM). This article shows how to effortlessly integrate EEG data with multi-omics, overcoming challenges like data volume and security. By combining diverse datasets, ODM accelerates discoveries in neuroinformatics, making it an essential tool for advancing our understanding of brain diseases.
Boost your research with FAIR data! Our latest article shows how making data Findable, Accessible, Interoperable, and Reusable (FAIR) transforms scientific inquiry and accelerates breakthroughs. Discover how FAIR principles and tools like Large Language Models (LLMs) help you find the right datasets and avoid redundant experiments, enabling smarter, data-driven decisions.
In the modern era, data has become a crucial part of our lives. Data provides the required information to drive decision-making, foster innovation, and improve life quality. The amount of data obtained through various sources is growing exponentially.
In this article we continue our series of six steps to FAIR data by discussing the importance of data curation and the do’s and don’ts of using LLMs to assist you.
Genestack’s ODM exceeds Bayer Crop Science’s Expectations for Small Molecule Omics Data Integration.
CUNY (City University of New York) and Genestack Ltd are pleased to announce their collaboration aimed at streamlining data curation for the BioConductor program. This innovative partnership brings together the expertise of CUNY in biomedical research and Genestack's advanced data management platform, offering significant benefits to researchers in the field.
In this brief article, the first of a series of three brief articles, we share some of our direct experience using Large Language Models (LLMs) in life science R&D.
In his upcoming talk at BioIT 2024 our CEO Misha Kapushesky will discuss “The Uses of LLMs in Discovery Bioinformatics, the Role of Data Management & Lessons in Practical Applications.”
Life Sciences runs on data. From high complexity omics data through to validatory assays, from clinical trials patient data through to sales and manufacturing. It is an asset and a resource that every organization relies on.
