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The Drug Discovery Team use a distributed and parallelized computing environment for many of our modeling and data analysis procedures. The Team is working on innovative computational‐driven approaches and technologies that are relatively broadly targeted at the analysis and modeling at life science data with the goal towards developing small molecule chemical probes and human therapeutics.

The Drug Discovery program has a number of specific, cheminformatics-related projects with focus in these areas:

  • Ontology Development
  • Structure-Based Drug Design
  • Biological Categorization and Analysis of Screening Data
  • Systematic Data Modeling and Analysis of very large Chemical Structure-Activity Data Sets
  • Library Diversity Analysis and Design
  • Structure-Activity Data Visualization, Modeling of Adverse Drug Reactions and Toxicity
  • In-Silico Synthetic Chemistry
  • Machine Learning
  • Algorithm Development
  • Chemoinformatics Software Development and Integration

Projects are suitable for graduate- and undergraduate-level research for students with an interest in pharmacology, biology, biochemistry, computer science and engineering, computational chemistry, or synthetic chemistry.


Research Highlights

BD2K-LINCS Summer Research Training Program Has Begun

Summer Research Training Program in Biomedical Big Data […]

Posted in News - Archived | Tagged , , ,

UM Awarded NIH Big Data to Knowledge (BD2K) Grant

UM reserach team will create a Data Coordination and Integration Center for the LINCS program.

Posted in Featured, Grants | Tagged , , , , ,

Allosteric Inhibition of the IRE1α RNase Preserves Cell Viability and Function during Endoplasmic Reticulum Stress

ER stress triggers a “terminal UPR” via hyperactivation of IRE1α, an ER kinase/RNase

Posted in Publications, Research - Archived | Tagged , , ,

MASTHEAD IMAGE SOURCE:  Wikimedia Commons, Public Domain Chemical Genomics Robot photo by Maggie Bartlett, National Human Genome Research Institute.

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