Learning from positive and unlabeled documents for automated detection of alternative splicing sentences in MEDLINE abstracts

2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2011

Volumn , Issue , 2011, Pages 530-537

  Chen, Yang ^a   Torii, Manabu ^b   Lu, Chang Tien ^a   Liu, Hongfang ^c  

^a VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY   (United States)

^b GEORGETOWN UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c MAYO CLINIC   (United States)

Author keywords

Alternative Splicing; Document Retrieval; LPU

Indexed keywords

ALTERNATIVE SPLICING; AUTOMATED DETECTION; BIOLOGICAL RESEARCH; DATA SETS; DNA SPLICING; DOCUMENT FILTERING SYSTEMS; DOCUMENT RETRIEVAL; FUNCTIONAL COMPLEXITY; HIGH-THROUGHPUT GENOMICS; KEY FACTORS; KNOWLEDGE BASIS; LPU; MEDLINE; POSITIVE DOCUMENTS; UNLABELED DATA; UNLABELED DOCUMENTS;

GENES; INFORMATION RETRIEVAL SYSTEMS; LEARNING SYSTEMS;

LEARNING ALGORITHMS;

EID: 84862957370     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/BIBMW.2011.6112425     Document Type: Conference Paper

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