Maricel Kann, Ph.D.

Associate Professor

Maricel Kann

Office: BS 116
Phone: 410-455-2258
Lab: BS 109
Lab Phone: 410-455-2062

Research Group



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

Professional Interests

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 proteins and domains  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.


Other affiliations:

Affiliate Assistant Professor, Computational Sciences and Engineering Department, UMBC


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

American Association for the Advancement of Science

American Medical Informatics Association

Associate Editor, Journal of Biomedical Informatics (2012-now) (

Editorial Board Member, Journal of Biomedical Informatics (2009-2011) (

Editorial Board Member, In Silico Biology ( )

University of Maryland, Baltimore County, Diversity Council

University of Maryland, Baltimore County, Chemistry and Biology Interface Program (

The University of Maryland Marlene and Stewart Greenebaum Cancer Center (

University of Maryland School of Medicine Program in Biochemistry and Molecular Biology (

Scientific Advisory board member, UniProt (2011-2013) (

Conference Organizer, Translational Bioinformatics Conference;(November, 2011 and October 2012) (

Conference Organizer, Brazilian Symposium on Bioinformatics;(August 2012) ( )

Conference Scientific Program Committee, RECOMB Conference on Regulatory and Systems Genomics;(2011 and 2012) ( )


Nehrt, NL, Peterson, T, Park, D & Kann, MG (2012). Domain landscapes of somatic mutations in cancer. BMC genomics 13 Suppl 4, S9.
[Abstract] [Text] [PDF]

Peterson, TA, Nehrt, NL, Park, D & Kann, MG. (2012) Incorporating molecular and functional context into the analysis and prioritization of human variants associated with cancer. Journal of the American Medical Informatics Association : JAMIA 19, 275-283.
[Abstract] [Text] [PDF]

Regan, K, Wang, K, Doughty, E, Li, H, Li, J, Lee, Y, Kann, MG & Lussier, YA. (2012) Translating Mendelian and complex inheritance of Alzheimer’s disease genes for predicting unique personal genome variants. Journal of the American Medical Informatics Association : JAMIA 19, 306-316.
[Abstract] [Text] [PDF]

Capriotti, E, Nehrt, NL, Kann, MG & Bromberg, Y. (2012) Bioinformatics for personal genome interpretation. Briefings in bioinformatics, 13(4):495-512.
[Abstract] [Text] [PDF]

Doughty, E, Kertesz-Farkas, A, Bodenreider, O, Thompson, G, Adadey, A, Peterson, T & Kann, MG.(2011) Toward an automatic method for extracting cancer- and other disease-related point mutations from the biomedical literature. Bioinformatics (Oxford, England) (27), 408-415.
[Abstract] [Text] [PDF]

 Peterson, T.A., Adadey, A., Santana-Cruz ,I., Sun, Y., Winder A, Kann, M.G. (2010) DMDM: Domain Mapping of Disease Mutations. Bioinformatics 26 (19), 2458-2459.
[Abstract] [Text] [PDF]
Carroll, HD, Kann, MG, Sheetlin, SL & Spouge, JL. (2010) Threshold Average Precision (TAP-k): A Measure of Retrieval Designed for Bioinformatics. Bioinformatics 26 (14), 1708-1713.
[Abstract] [PDF]
Mort, M., Evani, U.S., Krishnan, V.G., Kamati, K.K., Baenziger, P.H., Bagchi, A., Peters, B.J., Sathyesh, R., Li, B., Sun, Y., Xue, B., Shah, N.H., Kann, M.G., Cooper, D.N., Radivojac, P. & Mooney, S.D. (2010)  In silico functional profiling of human disease-associated and polymorphic amino acid substitutions. Hum Mutat 31, 335-346.
[Abstract] [Text] [PDF]
Kann, M.G. (2010)  Advances in translational bioinformatics: computational approaches for the hunting of disease genes. Briefings in bioinformatics 11, 96-110.
[Abstract] [Text] [PDF]
Alkan, C., Brudno, M., Eichler, E.E., Kann, M.G. & Sahinalp, S.C. (2010) PERSONAL GENOMICS – Session Introduction. Pac Symp Biocomput 15, 302-304.
[Abstract] [Text] [PDF]
Kann, M. G., Shoemaker, B. A., Panchenko, A. R. & Przytycka, T. M. (2009). Correlated evolution of interacting proteins: looking behind the mirrortree. J Mol Biol 385, 91-8.Radivojac, P., Baenziger, P. H.,
Kann, M. G., Mort, M. E., Hahn, M. W. & Mooney, S. D. (2008). Gain and loss of phosphorylation sites in human cancer. Bioinformatics 24, i241-7.
Singh, A., Olowoyeye, A., Baenziger, P.H., Dantzer, J., Kann, M.G., Radivojac, P., Heiland, R. & Mooney, S.D. (2008)MutDB: update on development of tools for the biochemical analysis of genetic variation. Nucleic acids research 36, D815-819
[Abstract] [Text] [PDF]
Kann, M. G. (2007). “Protein interactions and disease: computational approaches to uncover the etiology of diseases.” Brief Bioinform, 8(5):333-46. Epub 2007 Jul 16[Abstract] [Text] [PDF]
Kann, M. G., S. L. Sheetlin, Y. Park, et al. (2007). “The identification of complete domains within protein sequences using accurate E-values for semi-global alignment.” Nucleic Acids Res 35(14): 4678-85.
[Abstract] [Text] [PDF]
Kann, M. G., R. Jothi, P. F. Cherukuri, et al. (2007). “Predicting protein domain interactions from coevolution of conserved regions.” Proteins 67(4): 811-20
[Abstract] [Text] [PDF]
Valdivia-Granada, W. A., M. G. Kann and J. Malaga (2007). “Transcriptional Interactions during smallpox infection and identification of early infection biomarkers.” Pac Symp Biocomput.: 100-111.
[Abstract] [PDF]
Kann, M. G., P. A. Thiessen, A. R. Panchenko, et al. (2005). “A structure-based method for protein sequence alignment.” Bioinformatics 21(8): 1451-6.
[Abstract] [Text] [PDF]
Jothi, R., M. G. Kann and T. M. Przytycka (2005). “Predicting protein-protein interaction by searching evolutionary tree automorphism space.” Bioinformatics 21 Suppl 1: i241-i250
[Abstract] [PDF]
Marino-Ramirez, L., M. G. Kann, B. A. Shoemaker, et al. (2005). “Histone structure and nucleosome stability.” Expert Rev Proteomics 2(5): 719-29.
[Abstract] [Text] [PDF]
Valdivia-Granada, W. A., C. D. Keating, M. Kann, et al. (2005). Detection of Encephalic and Hemorrhagic Viruses: Integration of Micro and Nano-fabrication with Computational Tools. IEEE.International Conference on MEMS, NANO and Smart Systems, IEEE.
Kann, M. and R. A. Goldstein (2004). OPTIMA: A new score function for the detection of remote homologs. inMathematical Methods for Protein Structure Analysis and Design. Lectures Notes in Computer Science. Springer-Verlag. Heidelberg: 99-107.
[Abstract] [PDF]
Kann, M. G. and R. A. Goldstein (2002). “Performance evaluation of a new algorithm for the detection of remote homologs with sequence comparison.” Proteins 48(2): 367-76.
[Abstract] [Text] [PDF]
Kann, M., B. Qian and R. A. Goldstein (2000). “Optimization of a new score function for the detection of remote homologs.” Proteins 41(4): 498-503.
[Abstract] [Text] [PDF]
Kann, M. and R. A. Goldstein (2000). Optimizing for Success: A new score function for distantly related proteins. Fourth annual international conference on computational molecular biology (RECOMB). Tokyo, Japan, ACM: 177-182
[Abstract] [PDF]


The NCI Transition Career Development Award (K22)
NIH Intramural Research Training Award.
NIH Fellows Award for Research Excellence.
Annual competition in recognition for the outstanding scientific research performed by intramural postdoctoral fellows.
Susan Lipschutz Award for Women Graduate Students
The University of Michigan
Two awards of $5000 given to students with exceptional scholarly achievement, a sense of social responsibility and an interest in the academic community (only one student per department could be nominated).
Sloan Foundation Summer Graduate Fellowship.
Sloan Foundation
Graduate Fellowship of the Organization of the American States
Two-year full scholarship ($90,000).


R01LM009722 (Mooney, PI)
Role: collaborator
1K22CA143148 (Kann, PI)
Role: PI

Courses Taught

BIOL 495: Seminar in Bioinformatics