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Welcome to Dr. Kann's Bioinformatics Lab

The availability of genomic data derived from hundreds of genome projects has generated a great challenge: to understand the complexity of biological process and to decipher the mechanisms that lead to healthy or diseased organisms. Integration of knowledge and computational tools has been the key to understand the complexity of biological mechanisms. Further progress in this area requires an interdisciplinary effort. My goal is to develop interdisciplinary approaches to understanding protein networks through a combination of computational methods, biological insight, and close collaborations with experimentalists.

My research interests include the development of computational methods for detecting protein domains and their interactions in large-scale biological data sets. Since complete protein domains are the functional and evolutionary modules of the cell, sequence-based domain recognition methods have become one the most convenient and practical tools to gain insights into protein evolution and to infer protein function.  Predicting the network of interacting domains will also lead to a better understanding of the molecular basis of those protein interactions related with diseases. This will aid the development of drugs to inhibit pathological protein interactions, and the design of novel protein interactions with appropriate domain architectures.

My group's focus is on developing the methodologies and computational resources to derive molecular signatures of prostate and breast cancer.

RECRUITING GRADUATE STUDENTS, IF YOU ARE  INTERESTED IN A PH.D. THESIS ON COMPUTATIONAL BIOLOGY, BIOINFORMATICS, SYSTEMS BIOLOGY AND/OR APPLICATIONS OF THESE AREAS TO UNDERSTANDING HUMAN DISEASES PLEASE DON'T HESITATE TO CONTACT (mkann at umbc dot edu).

Memberships:

Advisory board member, PubMedCentral National Committee (2009-2013)

American Association for the Advancement of Science

American Medical Informatics Association

Editorial Board Member, Journal of Biomedical Informatics (2009-2012)

Editorial Review Board Member, International Journal of Computational Models and Algorithms in Medicine

International Society for Computational Biology


About Dr. Kann

Postdoctorate, National Center for Biotechnology Information, NIH, 2007; Ph.D., University of Michigan, Ann Arbor, 2001

Contact Information Office: BS 116

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