Hagit Shatkay

Summary

Affiliation: Queen's University
Country: Canada

Publications

  1. pmc Multi-dimensional classification of biomedical text: toward automated, practical provision of high-utility text to diverse users
    Hagit Shatkay
    The Computational Biology and Machine Learning Lab, School of Computing, Queen s University, Kingston, Ontario, Canada
    Bioinformatics 24:2086-93. 2008
  2. pmc New directions in biomedical text annotation: definitions, guidelines and corpus construction
    W John Wilbur
    National Center for Biotechnology Information NLM, NIH, Bethesda, MD, USA
    BMC Bioinformatics 7:356. 2006
  3. pmc Discovering semantic features in the literature: a foundation for building functional associations
    Monica Chagoyen
    Biocomputing Unit, Centro Nacional de Biotecnologia CSIC, Madrid, Spain
    BMC Bioinformatics 7:41. 2006
  4. ncbi request reprint Mining the biomedical literature in the genomic era: an overview
    Hagit Shatkay
    School of Computing, Queen s University, Kingston, Ontario, Canada K7L3N6
    J Comput Biol 10:821-55. 2003
  5. ncbi request reprint ThurGood: evaluating assembly-to-assembly mapping
    Hagit Shatkay
    School of Computing, Queen s University, Kingston, Ontario, Canada
    J Comput Biol 11:800-11. 2004
  6. ncbi request reprint Hairpins in bookstacks: information retrieval from biomedical text
    Hagit Shatkay
    School of Computing, Queen s University, Kingston, Ontario, K7L 3N6, Canada
    Brief Bioinform 6:222-38. 2005
  7. ncbi request reprint SherLoc: high-accuracy prediction of protein subcellular localization by integrating text and protein sequence data
    Hagit Shatkay
    School of Computing, Queen s University, Kingston, Ontario, Canada
    Bioinformatics 23:1410-7. 2007
  8. ncbi request reprint Integrating image data into biomedical text categorization
    Hagit Shatkay
    School of Computing, Queen s University, Kingston, Ontario, Canada
    Bioinformatics 22:e446-53. 2006
  9. pmc F-SNP: computationally predicted functional SNPs for disease association studies
    Phil Hyoun Lee
    Computational Biology and Machine Learning Lab, School of Computing, Queen s University, Kingston, ON, Canada
    Nucleic Acids Res 36:D820-4. 2008
  10. pmc Protein function prediction using text-based features extracted from the biomedical literature: the CAFA challenge
    Andrew Wong
    Computational Biology and Machine Learning Lab, School of Computing, Queen s University, Kingston, ON, K7L 3N6, Canada
    BMC Bioinformatics 14:S14. 2013

Collaborators

Detail Information

Publications14

  1. pmc Multi-dimensional classification of biomedical text: toward automated, practical provision of high-utility text to diverse users
    Hagit Shatkay
    The Computational Biology and Machine Learning Lab, School of Computing, Queen s University, Kingston, Ontario, Canada
    Bioinformatics 24:2086-93. 2008
    ....
  2. pmc New directions in biomedical text annotation: definitions, guidelines and corpus construction
    W John Wilbur
    National Center for Biotechnology Information NLM, NIH, Bethesda, MD, USA
    BMC Bioinformatics 7:356. 2006
    ..Our ultimate goal is to annotate a significant corpus of biomedical text and train machine learning methods to automatically categorize such text along certain dimensions that we have defined...
  3. pmc Discovering semantic features in the literature: a foundation for building functional associations
    Monica Chagoyen
    Biocomputing Unit, Centro Nacional de Biotecnologia CSIC, Madrid, Spain
    BMC Bioinformatics 7:41. 2006
    ..Therefore, the development of automated text mining tools to assist in such interpretation is one of the main challenges in current bioinformatics research...
  4. ncbi request reprint Mining the biomedical literature in the genomic era: an overview
    Hagit Shatkay
    School of Computing, Queen s University, Kingston, Ontario, Canada K7L3N6
    J Comput Biol 10:821-55. 2003
    ....
  5. ncbi request reprint ThurGood: evaluating assembly-to-assembly mapping
    Hagit Shatkay
    School of Computing, Queen s University, Kingston, Ontario, Canada
    J Comput Biol 11:800-11. 2004
    ..These tools have already proved useful in the evaluation and ranking of several methods for assembly-to-assembly mapping, which were recently used to map multiple versions of the human genome to each other (Istrail et aL, 2004)...
  6. ncbi request reprint Hairpins in bookstacks: information retrieval from biomedical text
    Hagit Shatkay
    School of Computing, Queen s University, Kingston, Ontario, K7L 3N6, Canada
    Brief Bioinform 6:222-38. 2005
    ..This paper introduces the basics of information retrieval, discusses its applications in biomedicine, and presents traditional and non-traditional ways in which it can be used...
  7. ncbi request reprint SherLoc: high-accuracy prediction of protein subcellular localization by integrating text and protein sequence data
    Hagit Shatkay
    School of Computing, Queen s University, Kingston, Ontario, Canada
    Bioinformatics 23:1410-7. 2007
    ..Numerous localization prediction systems are described in the literature; some focus on specific localizations or organisms, while others attempt to cover a wide range of localizations...
  8. ncbi request reprint Integrating image data into biomedical text categorization
    Hagit Shatkay
    School of Computing, Queen s University, Kingston, Ontario, Canada
    Bioinformatics 22:e446-53. 2006
    ..We show preliminary results, demonstrating that the method has a strong potential to enhance and complement traditional text-based categorization methods...
  9. pmc F-SNP: computationally predicted functional SNPs for disease association studies
    Phil Hyoun Lee
    Computational Biology and Machine Learning Lab, School of Computing, Queen s University, Kingston, ON, Canada
    Nucleic Acids Res 36:D820-4. 2008
    ..g. starting from SNP identifier, genomic region, gene or target disease). The F-SNP database is available at http://compbio.cs.queensu.ca/F-SNP/...
  10. pmc Protein function prediction using text-based features extracted from the biomedical literature: the CAFA challenge
    Andrew Wong
    Computational Biology and Machine Learning Lab, School of Computing, Queen s University, Kingston, ON, K7L 3N6, Canada
    BMC Bioinformatics 14:S14. 2013
    ..In this paper, we present the preliminary work and evaluation that we performed for our system, as part of the CAFA challenge...
  11. doi request reprint An integrative scoring system for ranking SNPs by their potential deleterious effects
    Phil Hyoun Lee
    Computational Biology and Machine Learning Lab, School of Computing, Queen s University, Kingston, ON, Canada
    Bioinformatics 25:1048-55. 2009
    ..As of yet, little has been done to quantitatively assess the possible deleterious effects of SNPs for effective association studies...
  12. ncbi request reprint BNTagger: improved tagging SNP selection using Bayesian networks
    Phil Hyoun Lee
    School of Computing, Queen s University, Kingston, ON, Canada
    Bioinformatics 22:e211-9. 2006
    ..The results demonstrate that our method consistently improves upon previous methods in terms of prediction accuracy. Moreover, our method retains its good performance even when a very small number of tagging SNPs are used...
  13. ncbi request reprint Combining multi-species genomic data for microRNA identification using a Naive Bayes classifier
    Malik Yousef
    The Wistar Institute, Philadelphia, PA 19104, USA
    Bioinformatics 22:1325-34. 2006
    ..The resulting algorithm exhibits higher specificity and similar sensitivity compared to currently used algorithms that rely on conserved genomic regions to decrease the rate of FPs...
  14. pmc Whole-genome shotgun assembly and comparison of human genome assemblies
    Sorin Istrail
    Applied Biosystems, 45 West Gude Drive, Rockville, MD 20850, USA
    Proc Natl Acad Sci U S A 101:1916-21. 2004
    ..The Celera results provide more order and orientation, and the consortium sequence provides better coverage of exact and nearly exact repeats...