Performance Evaluation of DNA MOTIF discovery programs

Abstract

Abstract:Methods for the identification of transcription factor binding sites have proved to be useful for deciphering genetic regulatory networks. The strengths and weaknesses for a number of available web tools are not fully understood. Here, we designed a comprehensive set of performance measures and benchmarked sequence-based motif discovery tools using large scale datasets (derived from Escherichia coli genome and RegulonDB database). The benchmark study showed that nucleotide based and binding site based prediction accuracy is often low and activator binding site based prediction accuracy is high.

Retraction for Singh et al., Performance evaluation of DNA Motif discovery programs

“…The article “Performance evaluation of DNA motif discovery programs”, by Singh et al . Bioinformation 2008 3(5): 205-212 [ 1 ], has text that was taken directly from the article “Limitations and potentials of current motif discovery algorithms” by Hu et al . Nucleic Acids Res.…”

Mechanisms and Evolution of Control Logic in Prokaryotic Transcriptional Regulation

“…Because so many different tools are available for DNA motif discovery, balanced comparisons are of major importance. Although some efforts in this have been attempted (134,276,293), it remains a major challenge to the work field to find objective standards for algorithm evaluation. The main reason for this is that the various tools score differently depending on the data sets, and absolute benchmarks are lacking (256,293) (134).…”

Retraction Notice for Singh et al. Performance evaluation of DNA Motif discovery programs Published on December 31, 2018

“…The article 1 retracted 2 by the journal (Bioinformation) was communicated by the first author (Chandra Prakash Singh) without our knowledge, willingness and consent. Hence, we the following report our innocence in this context.…”