Metabolomics—often referred to as the youngest of the omics—provides key insight into phenotype. However, bulk metabolomics requires the homogenization of the sample and is thus unable to discern metabolic differences at a cellular level.
Metabolomics—often referred to as the youngest of the omics—provides key insight into phenotype. However, bulk metabolomics requires the homogenization of the sample and is thus unable to discern metabolic differences at a cellular level.
The past few years have seen several flashy demonstrations of how artificial intelligence (AI) algorithms may transform biomedical research, particularly with respect to drug discovery.
Marilyn Matz, CEO of Paradigm4, and Zachary Pitluk, Vice President of Life Sciences at Paradigm4, explain why scalable data science platforms are key to supporting integrated analysis of single-cell genomic data sets.
Paradigm4’s REVEAL Integrative Analytics platform enables Alnylam Pharmaceuticals to discover novel, genetically-validated drug targets from population scale biobank genotype-phenotype datasets and underlies the extraordinary pace and productivity of Alnylam’s RNAi therapeutics pipeline.