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Maricel G. Kann

Affiliations: 
Biological Sciences University of Maryland, Baltimore County, Baltimore, MD, United States 
Area:
Computational Biology
Website:
http://biology.umbc.edu/directory/faculty/kann/
Google:
"Maricel Kann"
Bio:

Dr. Maricel Kann is an Associate Professor at the University of Maryland,
Baltimore County. She received a B. Sc. degree in Chemistry and a graduate
degree in Pharmaceutical Chemistry from the Universidad de la Republica in
Montevideo (Uruguay), where she was a research assistant in the Quantum
Chemistry Department. In 2001, she obtained a doctoral degree from the
University of Michigan in Chemistry. Her thesis work under the guidance of Dr.
Richard A.
Goldstein focused on the theory, statistics and methods for protein sequence
alignment. After completing her Ph.D., Dr. Kann joined the Structure group at
the National Center for Biotechnology Information (NIH) as a postdoctoral
fellow. In August 2007, she joined the Department of Biological Sciences at UMBC
as an Assistant Professor. Dr. Kann's research focuses on computational
approaches to annotate the human genome with the goal of revealing the molecular
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Parents

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Richard A. Goldstein grad student 1996-2001 University of Michigan
 (Protein sequence alignment: Theory, algorithms, and optimal score function.)

Children

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Mileidy Gonzalez grad student 2010 UMBC

Collaborators

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Publications

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Voskanian A, Katsonis P, Lichtarge O, et al. (2019) Assessing the performance of in-silico methods for predicting the pathogenicity of variants in the gene CHEK2, among Hispanic females with breast cancer. Human Mutation
Peters B, Brenner SE, Wang E, et al. (2018) Putting benchmarks in their rightful place: The heart of computational biology. Plos Computational Biology. 14: e1006494
Cirincione AG, Clark KL, Kann MG. (2018) Pathway networks generated from human disease phenome. Bmc Medical Genomics. 11: 75
Gauran IIM, Park J, Lim J, et al. (2017) Empirical null estimation using zero-inflated discrete mixture distributions and its application to protein domain data. Biometrics
Peterson TA, Gauran IIM, Park J, et al. (2017) Oncodomains: A protein domain-centric framework for analyzing rare variants in tumor samples. Plos Computational Biology. 13: e1005428
Peterson TA, Mort M, Cooper DN, et al. (2016) Regulatory Single Nucleotide Variant Predictor (RSVP) Increases Predictive Performance of Functional Regulatory Variants. Human Mutation
Burger JD, Doughty E, Khare R, et al. (2014) Hybrid curation of gene-mutation relations combining automated extraction and crowdsourcing. Database : the Journal of Biological Databases and Curation. 2014
Peterson TA, Doughty E, Kann MG. (2013) Towards precision medicine: advances in computational approaches for the analysis of human variants. Journal of Molecular Biology. 425: 4047-63
Peterson TA, Park D, Kann MG. (2013) A protein domain-centric approach for the comparative analysis of human and yeast phenotypically relevant mutations. Bmc Genomics. 14: S5
Gonzalez MW, Kann MG. (2012) Chapter 4: Protein interactions and disease. Plos Computational Biology. 8: e1002819
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