Automatic recognition of regions of intrinsically poor multiple alignment using machine learning

Proceedings of the 2003 IEEE Bioinformatics Conference, CSB 2003

Volumn , Issue , 2003, Pages 482-483

  Shan, Y ^a   Milios, E E ^a   Roger, A J ^b   Blouin, C ^b   Susko, E ^a  

^a DALHOUSIE UNIVERSITY   (Canada)

^b DALHOUSIE UNIVERSITY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BIOINFORMATICS; DECISION TREES; GENES; LEARNING SYSTEMS; SUPPORT VECTOR MACHINES;

AUTOMATIC ALIGNMENT; AUTOMATIC RECOGNITION; C4.5 DECISION TREES; MACHINE LEARNING APPROACHES; MULTIPLE ALIGNMENT; NAIVE BAYES; PHYLOGENETIC ANALYSIS; PROTEIN SEQUENCES;

ALIGNMENT;

EID: 40649103884     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CSB.2003.1227381     Document Type: Conference Paper

References (2)

1. G. M. Weiss and F. Provost. The effect of class distribution on classifier learning. Technical Report ML-TR 43, Department of Computer Science, Rutgers University, 2001.
2. I. Witten and E. Frank. Data mining: Practical machine learning tools and techniques with java implementations. 1999.