ArticleBMC bioinformatics2006
A machine learning strategy to identify candidate binding sites in human protein-coding sequence.
Article in BMC bioinformatics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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Who cites it
11 citing papers in PubMed, 14 citations in OpenAlex.
- A primer on machine learning techniques for genomic applications.Computational and structural biotechnology journal · 2021Review
- CodingMotif: exact determination of overrepresented nucleotide motifs in coding sequences.BMC bioinformatics · 2012Article
- Locating protein-coding sequences under selection for additional, overlapping functions in 29 mammalian genomes.Genome research · 2011Article
- COMIT: identification of noncoding motifs under selection in coding sequences.Genome biology · 2009Article
- A search for conserved sequences in coding regions reveals that the let-7 microRNA targets Dicer within its coding sequence.Proceedings of the National Academy of Sciences of the United States of America · 2008Article
- Automatic detection of exonic splicing enhancers (ESEs) using SVMs.BMC bioinformatics · 2008Article
- Genomic mid-range inhomogeneity correlates with an abundance of RNA secondary structures.BMC genomics · 2008Article
- Resolving the structural features of genomic islands: a machine learning approach.Genome research · 2008Article
- Calculation of splicing potential from the Alternative Splicing Mutation Database.BMC research notes · 2008Article
- The Alternative Splicing Mutation Database: a hub for investigations of alternative splicing using mutational evidence.BMC research notes · 2008Article
- Exploiting residue-level and profile-level interface propensities for usage in binding sites prediction of proteins.BMC bioinformatics · 2007Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
backgroundThe splicing of RNA transcripts is thought to be partly promoted and regulated by sequences embedded within exons. Known sequences include binding sites for SR proteins, which are thought to mediate interactions between splicing factors bound to the 5' and 3' splice sites. It would be useful to identify further candidate sequences, however identifying them computationally is hard since exon sequences are also constrained by their functional role in coding for proteins.
resultsThis strategy identified a collection of motifs including several previously reported splice enhancer elements. Although only trained on coding exons, the model discriminates both coding and non-coding exons from intragenic sequence.
conclusionWe have trained a computational model able to detect signals in coding exons which seem to be orthogonal to the sequences' primary function of coding for proteins. We believe that many of the motifs detected here represent binding sites for both previously unrecognized proteins which influence RNA splicing as well as other regulatory elements.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.