Using LLMs in Life Sciences
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 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.
In the age of informatics how do the leaders in the life science industry keep their winning edge? We interviewed some of the top thought leaders in 2023 about what they thought the keys for success were when it came to data.
Radiomics is a new approach for noninvasive tumor subtyping that is showing excellent results. In this article we show an example of such an analysis and the importance of excellent data management for fast and complete insight production.
True Multi-Omics analysis is often out of reach for life science researchers due to the difficulty of integrating and harmonizing the data. This use case shows how easy it can be with Genestack’s Open Data Manager.
The amount of data generated in metabolomics can often be overwhelming, so effective data management is critical for success. In this use case, we will use data from the field of Nutraceuticals to show how simple it can be with ODM.
In this study we combine proteomics and blood test results for 400,000 patient samples to explore atopic dermatitis. We show how simple it is to handle this volume of data with ODM.
This article zooms into the details of getting data in, and sees how to make it possible on a tactical level and in practice via the use of agricultural and irrigation based metaphors.
There is no universal way to connect and model things. You need a system that will flex, that will allow you to define different data models for different modalities and different use cases. In this podcast the Wellcome Sanger Insititute and Genestack sit down and talk about the key to success in life sciences research.