Bioinformatics and Biomedicine

People Involved

  • Devendra Dhami
  • Mayukh Das

Bioinformatics is the field of applying statistics and computer science to the field of molecular biology. Our lab focuses mainly on the subarea of pattern recognition in biomedical data.

Biomedical data is composed of data in many formats: electronic health records are inherently relational, while the results of clinical tests tend to be propositional. The data can have multiple views—imagining data, clinical data, genomic data, or text from medical literature—which may all describe the same concept from different perspectives.

Learning from such disparate sources of information is a challenging task. We develop methods which can deal with such data separately, either as standalone datasets or combined in such a way that multiple types of data are used for prediction in a single model.


  1. Devendra Singh Dhami, Gautam Kunapuli, Mayukh Das, David Page, and Sriraam Natarajan. Drug-Drug Interaction Discovery: Kernel Learning from Heterogeneous Similarities. (Under review in IEEE Conference on Connected Health: Applications, Systems, and Engineering Technologies (CHASE), 2018.
  2. Devendra Singh Dhami, Ameet Soni, David Page, Sriraam Natarajan, Identifying Parkinson’s Patients : A Functional Gradient Boosting Approach, Artificial Intelligence in Medicine (AIME) (2017).