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  1. Proceedings of the KDD-09 Workshop on Statistical and Relational Learning in Bioinformatics (StReBio '09)
  2. Can we improve on the identification of transcription factor binding sites?
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Using random forests to uncover bivariate interactions in high dimensional small data sets
Identification of structurally important amino acids in proteins by graph-theoretic measures
Lift-based search for significant dependencies in dense data sets
Finding optimal parameters for edit distance based sequence classification is NP-hard
Multi-class protein fold recognition using large margin logic based divide and conquer learning
Protein sequence alignment and structural disorder: a substitution matrix for an extended alphabet
Handling missing values and censored data in PCA of pharmacological matrices
Comparing graph-based representations of protein for mining purposes
Can we improve on the identification of transcription factor binding sites?

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Simultaneous Identification for Synergistic Transcription Factors and their Transcription Factor Binding Sites

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Can we improve on the identification of transcription factor binding sites?

Content Provider ACM Digital Library
Author Shanahan, H. P.
Abstract This paper gives a brief introduction into the biology of Transcription Factor Bindings Sites (TFBS's) and their importance. It discusses the present methods employed in detecting them, which are typically based on single-site frequencies, their shortcomings and how new data is likely to revolutionise the area in the near future. The challenges associated with motif detection for methods that do not employ the standard approaches are addressed. Finally, there is a walk through of some of the available data sets for those interested in working on this problem.
Starting Page 39
Ending Page 40
Page Count 2
File Format PDF
ISBN 9781605586670
DOI 10.1145/1562090.1562099
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2009-06-28
Publisher Place New York
Access Restriction Subscribed
Subject Keyword String kernel Transcription factor binding site
Content Type Text
Resource Type Article
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