Filtration and depth annotation improve non-linear projection for RNA motif discovery

Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB'06

Volumn , Issue , 2006, Pages 352-359

  Schonfeld, Justin ^a   Ashlock, Daniel ^b  

^a IOWA STATE UNIVERSITY   (United States)

^b UNIVERSITY OF GUELPH   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BIOCOMMUNICATIONS; CHLORINE COMPOUNDS; EXPERIMENTS; INFORMATION SCIENCE; INTELLIGENT CONTROL; NUCLEIC ACIDS; PIPELINES; POROUS MATERIALS; RNA; WAVE FILTERS;

BIOLOGICAL DATA; COMPUTATIONAL BIOLOGY; COMPUTATIONAL INTELLIGENCE; MOTIF DISCOVERY; NON-LINEAR PROJECTIONS; RNA MOTIFS; SECONDARY STRUCTURES; SYNTHETIC DATA SETS;

BIOINFORMATICS;

EID: 50249107390     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CIBCB.2006.330957     Document Type: Conference Paper

References (22)

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