LedPred: an R/bioconductor package to predict regulatory sequences using support vector machines
Abstract. Summary: Supervised classification based on support vector machines (SVMs) has successfully been used for the prediction of cis-regulatory modules (CRMs)
Gespeichert in:
| Hauptverfasser: | , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
2016
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| In: |
Bioinformatics
Year: 2015, Jahrgang: 32, Heft: 7, Pages: 1091-1093 |
| ISSN: | 1367-4811 |
| DOI: | 10.1093/bioinformatics/btv705 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1093/bioinformatics/btv705 Verlag, lizenzpflichtig, Volltext: https://academic.oup.com/bioinformatics/article/32/7/1091/1744134 
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| Verfasserangaben: | Denis Seyres, Elodie Darbo, Laurent Perrin, Carl Herrmann and Aitor González |
| Zusammenfassung: | Abstract. Summary: Supervised classification based on support vector machines (SVMs) has successfully been used for the prediction of cis-regulatory modules (CRMs) |
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| Beschreibung: | Advance access publication date: 1 December 2015 Gesehen am 13.05.2020 |
| Beschreibung: | Online Resource |
| ISSN: | 1367-4811 |
| DOI: | 10.1093/bioinformatics/btv705 |