The Data Science and Data Engineering group organize and interpret the extensive data generated by drug discovery projects. Our data engineers develop integrated application ecosystems that automate every step of the drug discovery workflow. By applying statistics and the latest machine learning technologies, our team extracts authentic patterns representing the underlying drivers of the biological system.
We utilize a wide range of data science methodologies at GNF. Our success stories include meta- and orthogonal integration of OMICs studies to discover common and unique biological pathways, novel statistical algorithms for prioritizing screening hits, mechanism-of-action characterization of active small molecules through mining profiling databases, and automatic quality control pipelines for large-scale high-throughput screening datasets, among others.
Investigators at GNF employ a wide range of experimental approaches to investigate numerous biological diseases. The Bioinformatics team at GNF works closely with investigators helping to guide experimental plans and optimize the ability for target identification and validation in initiating new drug discovery programs.
The expertise of the group is diverse and includes manipulation and analyses of a wide range of data types such as DNA sequence and expression, global splicing, population genetics in mouse and human to infer causal relationships, in vitro and in