Maricel G Kann

Summary

Affiliation: University of Maryland
Country: USA

Publications

  1. pmc Correlated evolution of interacting proteins: looking behind the mirrortree
    Maricel G Kann
    Department of Biological Sciences, University of Maryland, Baltimore County, MD 21250, USA
    J Mol Biol 385:91-8. 2009
  2. pmc Chapter 4: Protein interactions and disease
    Mileidy W Gonzalez
    National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, United States of America
    PLoS Comput Biol 8:e1002819. 2012
  3. pmc Advances in translational bioinformatics: computational approaches for the hunting of disease genes
    Maricel G Kann
    University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA
    Brief Bioinform 11:96-110. 2010
  4. pmc Predicting protein-protein interaction by searching evolutionary tree automorphism space
    Raja Jothi
    National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health Bethesda, MD 20894, USA
    Bioinformatics 21:i241-50. 2005
  5. pmc The identification of complete domains within protein sequences using accurate E-values for semi-global alignment
    Maricel G Kann
    National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20894, USA
    Nucleic Acids Res 35:4678-85. 2007
  6. ncbi request reprint Predicting protein domain interactions from coevolution of conserved regions
    Maricel G Kann
    Department of Health and Human Services, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
    Proteins 67:811-20. 2007
  7. pmc Threshold Average Precision (TAP-k): a measure of retrieval designed for bioinformatics
    Hyrum D Carroll
    National Center for Biotechnology Information, Bethesda, MD 20894, USA
    Bioinformatics 26:1708-13. 2010
  8. pmc Domain landscapes of somatic mutations in cancer
    Nathan L Nehrt
    Department of Biological Sciences, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA
    BMC Genomics 13:S9. 2012
  9. pmc Towards precision medicine: advances in computational approaches for the analysis of human variants
    Thomas A Peterson
    Department of Biological Sciences, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA Electronic address
    J Mol Biol 425:4047-63. 2013
  10. ncbi request reprint Protein interactions and disease: computational approaches to uncover the etiology of diseases
    Maricel G Kann
    National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20894, USA
    Brief Bioinform 8:333-46. 2007

Detail Information

Publications17

  1. pmc Correlated evolution of interacting proteins: looking behind the mirrortree
    Maricel G Kann
    Department of Biological Sciences, University of Maryland, Baltimore County, MD 21250, USA
    J Mol Biol 385:91-8. 2009
    ....
  2. pmc Chapter 4: Protein interactions and disease
    Mileidy W Gonzalez
    National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, United States of America
    PLoS Comput Biol 8:e1002819. 2012
    ..We will describe the application of protein interaction networks as a translational approach to the study of human disease and evaluate the challenges faced by these approaches...
  3. pmc Advances in translational bioinformatics: computational approaches for the hunting of disease genes
    Maricel G Kann
    University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA
    Brief Bioinform 11:96-110. 2010
    ..This review highlights the latest advances in the field of translational bioinformatics, focusing on the advances of computational techniques to search for and classify disease genes...
  4. pmc Predicting protein-protein interaction by searching evolutionary tree automorphism space
    Raja Jothi
    National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health Bethesda, MD 20894, USA
    Bioinformatics 21:i241-50. 2005
    ..Many of these methods are limited by the fact that they can handle only a small number of protein sequences. Also, details on evolutionary tree topology are missing as they use similarity matrices in lieu of the trees...
  5. pmc The identification of complete domains within protein sequences using accurate E-values for semi-global alignment
    Maricel G Kann
    National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20894, USA
    Nucleic Acids Res 35:4678-85. 2007
    ..When searching for complete protein domains, therefore, GLOBAL avoids disadvantages commonly associated with HMMs, yet maintains their superior retrieval performance...
  6. ncbi request reprint Predicting protein domain interactions from coevolution of conserved regions
    Maricel G Kann
    Department of Health and Human Services, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
    Proteins 67:811-20. 2007
    ..We provide a theoretical validation of our results leading to new insights into the interplay between coevolution and speciation of interacting proteins...
  7. pmc Threshold Average Precision (TAP-k): a measure of retrieval designed for bioinformatics
    Hyrum D Carroll
    National Center for Biotechnology Information, Bethesda, MD 20894, USA
    Bioinformatics 26:1708-13. 2010
    ..Unfortunately, the pooled ROC(n) score does not faithfully reflect actual usage of retrieval algorithms. Additionally, a pooled ROC(n) score can be very sensitive to retrieval results from as little as a single query...
  8. pmc Domain landscapes of somatic mutations in cancer
    Nathan L Nehrt
    Department of Biological Sciences, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA
    BMC Genomics 13:S9. 2012
    ..These highly mutated domains potentially reveal disruptions of protein function necessary for cancer development...
  9. pmc Towards precision medicine: advances in computational approaches for the analysis of human variants
    Thomas A Peterson
    Department of Biological Sciences, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA Electronic address
    J Mol Biol 425:4047-63. 2013
    ..We expect these resources and tools to become the foundation for understanding the molecular details of genomic variants leading to disease, which in turn will enable the promise of precision medicine...
  10. ncbi request reprint Protein interactions and disease: computational approaches to uncover the etiology of diseases
    Maricel G Kann
    National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20894, USA
    Brief Bioinform 8:333-46. 2007
    ..Recent contributions from genetics, protein structure and protein interaction network analyses to the understanding of diseases are discussed here...
  11. pmc Incorporating molecular and functional context into the analysis and prioritization of human variants associated with cancer
    Thomas A Peterson
    University of Maryland, Baltimore County, Baltimore, Maryland 21250, USA
    J Am Med Inform Assoc 19:275-83. 2012
    ..A statistical method has been developed to assess the significance of disease mutation clusters on protein domains by incorporating domain functional annotations to assist in the functional characterization of novel variants...
  12. pmc A protein domain-centric approach for the comparative analysis of human and yeast phenotypically relevant mutations
    Thomas A Peterson
    Department of Biological Sciences, University of Maryland, Baltimore County, Baltimore, MD, USA
    BMC Genomics 14:S5. 2013
    ..Focusing on two evolutionarily distant organisms, human and yeast, we describe the first inter-species analysis of mutations of phenotypic relevance at the protein domain level...
  13. pmc Toward an automatic method for extracting cancer- and other disease-related point mutations from the biomedical literature
    Emily Doughty
    University of Maryland, Baltimore County, Baltimore, MD 21250, USA
    Bioinformatics 27:408-15. 2011
    ..We introduce a high-throughput computational method for the identification of relevant disease mutations in PubMed abstracts applied to prostate (PCa) and breast cancer (BCa) mutations...
  14. pmc A mutation-centric approach to identifying pharmacogenomic relations in text
    Bastien Rance
    National Library of Medicine, Bethesda, MD 20894, USA
    J Biomed Inform 45:835-41. 2012
    ..To explore the notion of mutation-centric pharmacogenomic relation extraction and to evaluate our approach against reference pharmacogenomic relations...
  15. ncbi request reprint A structure-based method for protein sequence alignment
    Maricel G Kann
    National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20894, USA
    Bioinformatics 21:1451-6. 2005
    ....
  16. pmc DMDM: domain mapping of disease mutations
    Thomas A Peterson
    Department of Biological Sciences, University of Maryland, Baltimore County, Baltimore, MD 21250, USA
    Bioinformatics 26:2458-9. 2010
    ..DMDM's protein domain view highlights molecular relationships among mutations from different diseases that might not be clearly observed with traditional gene-centric visualization tools...
  17. pmc Histone structure and nucleosome stability
    Leonardo Mariño-Ramírez
    Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
    Expert Rev Proteomics 2:719-29. 2005
    ..The authors review recent findings on the structure of chromatin that confirm previous interparticle interactions observed in crystal structures...