ArticleBioinformatics (Oxford, England)2016
No Promoter Left Behind (NPLB): learn de novo promoter architectures from genome-wide transcription start sites.
Article in Bioinformatics (Oxford, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Identifying promoter sequence architectures via a chunking-based algorithm using non-negative matrix factorisation.PLoS computational biology · 2023Article
- Disentangling transcription factor binding site complexity.Nucleic acids research · 2018Article
- THiCweed: fast, sensitive detection of sequence features by clustering big datasets.Nucleic acids research · 2018Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
unlabelledPromoters have diverse regulatory architectures and thus activate genes differently. For example, some have a TATA-box, many others do not. Even the ones with it can differ in its position relative to the transcription start site (TSS). No Promoter Left Behind (NPLB) is an efficient, organism-independent method for characterizing such diverse architectures directly from experimentally identified genome-wide TSSs, without relying on known promoter elements. As a test case, we show its application in identifying novel architectures in the fly genome. AVAILABILITY AND IMPLEMENTATION: Web-server at http://nplb.ncl.res.in Standalone also at https://github.com/computationalBiology/NPLB/ (Mac OSX/Linux). CONTACT: l.narlikar@ncl.res.in SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Registered trials
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