DSCI DS590 Data Science in Practice

DS590 Data Science in Practice is a graduate course designed to help students gain critical, practical skills in applying data science to real world problems. Students will work in teams of 3-5 to tackle a real-world problem defined by a project sponsor. Project sponsors can be academics or industry practitioners. Students work with the project sponsor to understand the problem domain, identify where their data science skills can be applied, and to design, implement and test a solution.

Chem2Bio2RDF: a semantic framework for linking and data mining chemogenomic and systems chemical biology data

We have created a single repository called Chem2Bio2RDF by aggregating data from multiple chemogenomics repositories that is cross-linked into Bio2RDF and LODD. We have also created a linked-path generation tool to facilitate SPARQL query generation, and have created extended SPARQL functions to address specific chemical/biological search needs. We demonstrate the utility of Chem2Bio2RDF in investigating polypharmacology, identification of potential multiple pathway inhibitors, and the association of pathways with adverse drug reactions.

About David Wild

David Wild is a practitioner and educator in informatics & computing, data science, and pharmaceutical research.  He is associate professor in the School of Informatics, Computing and Engineering (SICE) and Director of the Integrative Data Science Lab at Indiana University, and is President of Data2Discovery, Inc.