Add to ORKG*Background:* Methods for finding overrepresented sequence motifs are useful in several key areas of computational biology. They aim at detecting very weak signals responsible for biological processes requiring robust sequence identification like transcription-factor binding to DNA or docking sites in proteins. Currently, general performance of the model-based motif-finding methods is unsatisfactory; however, different methods are successful in different cases. This leads to the practical problem of combining results of different motif-finding tools, taking into account current knowledge collected in motif databases.
*Results:* We propose a new complete service allowing researchers to submit their sequences for analysis by four dif...
Understanding the mechanisms that regulate gene expression is a major challenge in biology. One of t...
Analysis of sequence homology has always played a major role in the understanding of biological fact...
Abstract Background De novo prediction of Transcription Factor Binding Sites (TFBS) using computatio...
*Background:* Methods for finding overrepresented sequence motifs are useful in several key areas of...
Context of the thesis:Regulation of gene expression is a key mechanism for organisms to live and gro...
Computational methods for de novo identification of gene regulation elements, such as transcription ...
Abstract Background Discovery of functionally signifi...
AbstractDetection of over-represented motifs corresponding to known TFBSs (Transcription Factor Bind...
Background: In recent years, substantial effort has been applied to de novo regulatory motif discove...
Background Understanding gene regulatory networks has become one of the central research problems in...
Despite the diversity of motif representations and search algorithms, the de novo computational iden...
Background Understanding gene regulatory networks has become one of the central research problems in...
Background Understanding gene regulatory networks has become one of the central research problems in...
In the post-genomic era, identification of specific regulatory motifs or transcription factor bindin...
Background: Unraveling the mechanisms that regulate gene expression is a major challenge in biology....
Understanding the mechanisms that regulate gene expression is a major challenge in biology. One of t...
Analysis of sequence homology has always played a major role in the understanding of biological fact...
Abstract Background De novo prediction of Transcription Factor Binding Sites (TFBS) using computatio...
*Background:* Methods for finding overrepresented sequence motifs are useful in several key areas of...
Context of the thesis:Regulation of gene expression is a key mechanism for organisms to live and gro...
Computational methods for de novo identification of gene regulation elements, such as transcription ...
Abstract Background Discovery of functionally signifi...
AbstractDetection of over-represented motifs corresponding to known TFBSs (Transcription Factor Bind...
Background: In recent years, substantial effort has been applied to de novo regulatory motif discove...
Background Understanding gene regulatory networks has become one of the central research problems in...
Despite the diversity of motif representations and search algorithms, the de novo computational iden...
Background Understanding gene regulatory networks has become one of the central research problems in...
Background Understanding gene regulatory networks has become one of the central research problems in...
In the post-genomic era, identification of specific regulatory motifs or transcription factor bindin...
Background: Unraveling the mechanisms that regulate gene expression is a major challenge in biology....
Understanding the mechanisms that regulate gene expression is a major challenge in biology. One of t...
Analysis of sequence homology has always played a major role in the understanding of biological fact...
Abstract Background De novo prediction of Transcription Factor Binding Sites (TFBS) using computatio...