BacillusRegNet

a transcriptional regulation database and analysis platform for Bacillus species

Goksel Misirli, Jennifer Hallinan, Richard Röttger, Jan Baumbach, Anil Wipat

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

As high-throughput technologies become cheaper and easier to use, raw sequence data and corresponding annotations for many organisms are becoming available. However, sequence data alone is not sufficient to explain the biological behaviour of organisms, which arises largely from complex molecular interactions. There is a need to develop new platform technologies that can be applied to the investigation of whole-genome datasets in an efficient and cost-effective manner. One such approach is the transfer of existing knowledge from well-studied organisms to closely-related organisms. In this paper, we describe a system, BacillusRegNet, for the use of a model organism, Bacillus subtilis, to infer genome-wide regulatory networks in less well-studied close relatives. The putative transcription factors, their binding sequences and predicted promoter sequences along with annotations are available from the associated BacillusRegNet website (http://bacillus.ncl.ac.uk).

Original languageEnglish
JournalJournal of Integrative Bioinformatics
Volume11
Issue number2
Pages (from-to)244
ISSN1613-4516
DOIs
Publication statusPublished - 2014

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title = "BacillusRegNet: a transcriptional regulation database and analysis platform for Bacillus species",
abstract = "As high-throughput technologies become cheaper and easier to use, raw sequence data and corresponding annotations for many organisms are becoming available. However, sequence data alone is not sufficient to explain the biological behaviour of organisms, which arises largely from complex molecular interactions. There is a need to develop new platform technologies that can be applied to the investigation of whole-genome datasets in an efficient and cost-effective manner. One such approach is the transfer of existing knowledge from well-studied organisms to closely-related organisms. In this paper, we describe a system, BacillusRegNet, for the use of a model organism, Bacillus subtilis, to infer genome-wide regulatory networks in less well-studied close relatives. The putative transcription factors, their binding sequences and predicted promoter sequences along with annotations are available from the associated BacillusRegNet website (http://bacillus.ncl.ac.uk).",
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BacillusRegNet : a transcriptional regulation database and analysis platform for Bacillus species. / Misirli, Goksel; Hallinan, Jennifer; Röttger, Richard; Baumbach, Jan; Wipat, Anil.

In: Journal of Integrative Bioinformatics, Vol. 11, No. 2, 2014, p. 244.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - BacillusRegNet

T2 - a transcriptional regulation database and analysis platform for Bacillus species

AU - Misirli, Goksel

AU - Hallinan, Jennifer

AU - Röttger, Richard

AU - Baumbach, Jan

AU - Wipat, Anil

PY - 2014

Y1 - 2014

N2 - As high-throughput technologies become cheaper and easier to use, raw sequence data and corresponding annotations for many organisms are becoming available. However, sequence data alone is not sufficient to explain the biological behaviour of organisms, which arises largely from complex molecular interactions. There is a need to develop new platform technologies that can be applied to the investigation of whole-genome datasets in an efficient and cost-effective manner. One such approach is the transfer of existing knowledge from well-studied organisms to closely-related organisms. In this paper, we describe a system, BacillusRegNet, for the use of a model organism, Bacillus subtilis, to infer genome-wide regulatory networks in less well-studied close relatives. The putative transcription factors, their binding sequences and predicted promoter sequences along with annotations are available from the associated BacillusRegNet website (http://bacillus.ncl.ac.uk).

AB - As high-throughput technologies become cheaper and easier to use, raw sequence data and corresponding annotations for many organisms are becoming available. However, sequence data alone is not sufficient to explain the biological behaviour of organisms, which arises largely from complex molecular interactions. There is a need to develop new platform technologies that can be applied to the investigation of whole-genome datasets in an efficient and cost-effective manner. One such approach is the transfer of existing knowledge from well-studied organisms to closely-related organisms. In this paper, we describe a system, BacillusRegNet, for the use of a model organism, Bacillus subtilis, to infer genome-wide regulatory networks in less well-studied close relatives. The putative transcription factors, their binding sequences and predicted promoter sequences along with annotations are available from the associated BacillusRegNet website (http://bacillus.ncl.ac.uk).

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DO - 10.2390/biecoll-jib-2014-244

M3 - Journal article

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SP - 244

JO - Journal of Integrative Bioinformatics

JF - Journal of Integrative Bioinformatics

SN - 1613-4516

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