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Volumn , Issue , 2006, Pages 17-24

Term generalization and synonym resolution for biological abstracts: Using the gene ontology for subcellular localization prediction

Author keywords

[No Author keywords available]

Indexed keywords

ABSTRACTING; CLASSIFICATION (OF INFORMATION); GENES; MOLECULAR BIOLOGY; NATURAL LANGUAGE PROCESSING SYSTEMS; PROTEINS; SEMANTICS; COMPUTATIONAL LINGUISTICS; GENE ONTOLOGY; TEXT PROCESSING;

EID: 54949096505     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (1)

References (15)
  • 1
    • 0034069495 scopus 로고    scopus 로고
    • Gene ontology: Tool for the unification of biology the gene ontology consortium
    • Michael Ashburner et al. 2000. Gene ontology: Tool for the unification of biology the gene ontology consortium. Nature Genetics, 25(1):25-29.
    • (2000) Nature Genetics , vol.25 , Issue.1 , pp. 25-29
    • Ashburner, M.1
  • 5
    • 39049189808 scopus 로고    scopus 로고
    • Significantly improved prediction of subcellular localization by integrating text and protein sequence data
    • Annette Höglund et al. 2006. Significantly improved prediction of subcellular localization by integrating text and protein sequence data. In Pacific Symposium on Biocomputing, pages 16-27.
    • (2006) Pacific Symposium on Biocomputing , pp. 16-27
    • Höglund, A.1
  • 8
    • 1542400030 scopus 로고    scopus 로고
    • Predicting subcellular localization of proteins using machine-learned classifiers
    • Zhiyong Lu et al. 2004. Predicting subcellular localization of proteins using machine-learned classifiers. Bioinformatics, 20(4):547-556.
    • (2004) Bioinformatics , vol.20 , Issue.4 , pp. 547-556
    • Lu, Z.1
  • 9
    • 84948481845 scopus 로고
    • An algorithm for suffix stripping
    • Martin F. Porter. 1980. An algorithm for suffix stripping. Program, 14(3):130-137.
    • (1980) Program , vol.14 , Issue.3 , pp. 130-137
    • Porter, M.F.1
  • 10
    • 33947390929 scopus 로고    scopus 로고
    • Mining protein function from text using term-based support vector machines
    • Simon B Rice et al. 2005. Mining protein function from text using term-based support vector machines. BMC Bioinformatics, 6:S22.
    • (2005) BMC Bioinformatics , vol.6 , pp. S22
    • Rice, S.B.1
  • 12
    • 0036358850 scopus 로고    scopus 로고
    • Predicting the sub-cellular location of proteins from text using support vector machines
    • B. J. Stapley et al. 2002. Predicting the sub-cellular location of proteins from text using support vector machines. In Pacific Symposium on Biocomputing, pages 374-385.
    • (2002) Pacific Symposium on Biocomputing , pp. 374-385
    • Stapley, B.J.1
  • 13
    • 3242876302 scopus 로고    scopus 로고
    • Proteome analyst: Custom predictions with explanations in a web-based tool for high-throughput proteome annotations
    • Duane Szafron et al. 2004. Proteome analyst: Custom predictions with explanations in a web-based tool for high-throughput proteome annotations. Nucleic Acids Research, 32:W365-W371.
    • (2004) Nucleic Acids Research , vol.32 , pp. W365-W371
    • Szafron, D.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.