Eggeling , R , Grosse , I & Grau , J 2017 , ' InMoDe: tools for learning and visualizing intra-motif dependencies of DNA binding sites ' , Bioinformatics , vol. 33 , no. 4 , btw689 , pp. 580-582 . https://doi.org/10.1093/bioinformatics/btw689
Title: | InMoDe: tools for learning and visualizing intra-motif dependencies of DNA binding sites |
Author: | Eggeling, Ralf; Grosse, Ivo; Grau, Jan |
Contributor organization: | Helsinki Institute for Information Technology Department of Computer Science |
Date: | 2017-02-15 |
Language: | eng |
Number of pages: | 3 |
Belongs to series: | Bioinformatics |
ISSN: | 1367-4803 |
DOI: | https://doi.org/10.1093/bioinformatics/btw689 |
URI: | http://hdl.handle.net/10138/182241 |
Abstract: | Summary: Recent studies have shown that the traditional position weight matrix model is often insufficient for modeling transcription factor binding sites, as intra-motif dependencies play a significant role for an accurate description of binding motifs. Here, we present the Java application InMoDe, a collection of tools for learning, leveraging and visualizing such dependencies of putative higher order. The distinguishing feature of InMoDe is a robust model selection from a class of parsimonious models, taking into account dependencies only if justified by the data while choosing for simplicity otherwise. Availability and Implementation: InMoDe is implemented in Java and is available as command line application, as application with a graphical user-interface, and as an integration into Galaxy on the project website at http://www.jstacs.de/index.php/InMoDe. |
Subject: |
113 Computer and information sciences
112 Statistics and probability 1182 Biochemistry, cell and molecular biology |
Peer reviewed: | Yes |
Rights: | cc_by_nc |
Usage restriction: | openAccess |
Self-archived version: | publishedVersion |
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