ArticleGenome research2003
Sequence information for the splicing of human pre-mRNA identified by support vector machine classification.
Article in Genome research, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers.
What it found
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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
60 citing papers in PubMed, 132 citations in OpenAlex.
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- Identification of cell-type-specific, transcriptionally active transposable elements using long-read RNA-sequencing data-based comprehensive annotation.Genomics & informatics · 2025Article
- SLC25A48 controls mitochondrial choline import and metabolism.Cell metabolism · 2024Article
- Development and Validation of an ICU-Venous Thromboembolism Prediction Model Using Machine Learning Approaches: A Multicenter Study.International journal of general medicine · 2024Article
- CNNSplice: Robust models for splice site prediction using convolutional neural networks.Computational and structural biotechnology journal · 2023Article
- Development and internal validation of a machine-learning-developed model for predicting 1-year mortality after fragility hip fracture.BMC geriatrics · 2022Article
- Aberrant splicing events caused by insertion of genes of interest into expression vectors.International journal of biological sciences · 2022Article
- Modifying splice site usage withComputational and structural biotechnology journal · 2021Article
- A high-performance approach for predicting donor splice sites based on short window size and imbalanced large samples.Biology direct · 2019Article
- Prediction of donor splice sites using random forest with a new sequence encoding approach.BioData mining · 2016Article
- Computational Identification of Tissue-Specific Splicing Regulatory Elements in Human Genes from RNA-Seq Data.PloS one · 2016Article
- CoSREM: a graph mining algorithm for the discovery of combinatorial splicing regulatory elements.BMC bioinformatics · 2015Article
- SeqGL Identifies Context-Dependent Binding Signals in Genome-Wide Regulatory Element Maps.PLoS computational biology · 2015Article
- Identifying splicing regulatory elements with de Bruijn graphs.Journal of computational biology : a journal of computational molecular cell biology · 2014Article
- U1 snRNP-Dependent Suppression of Polyadenylation: Physiological Role and Therapeutic Opportunities in Cancer.International journal of cell biology · 2013Review
- Discovering weighted patterns in intron sequences using self-adaptive harmony search and back-propagation algorithms.TheScientificWorldJournal · 2013Article
- RNA secondary structure mediates alternative 3'ss selection in Saccharomyces cerevisiae.RNA (New York, N.Y.) · 2012Article
- Frequent gain and loss of intronic splicing regulatory elements during the evolution of vertebrates.Genome biology and evolution · 2012Article
- Efficient internal exon recognition depends on near equal contributions from the 3' and 5' splice sites.Nucleic acids research · 2011Article
- Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Vertebrate pre-mRNA transcripts contain many sequences that resemble splice sites on the basis of agreement to the consensus,yet these more numerous false splice sites are usually completely ignored by the cellular splicing machinery. Even at the level of exon definition,pseudo exons defined by such false splices sites outnumber real exons by an order of magnitude. We used a support vector machine to discover sequence information that could be used to distinguish real exons from pseudo exons. This machine learning tool led to the definition of potential branch points,an extended polypyrimidine tract,and C-rich and TG-rich motifs in a region limited to 50 nt upstream of constitutively spliced exons. C-rich sequences were also found in a region extending to 80 nt downstream of exons,along with G-triplet motifs. In addition,it was shown that combinations of three bases within the splice donor consensus sequence were more effective than consensus values in distinguishing real from pseudo splice sites; two-way base combinations were optimal for distinguishing 3' splice sites. These data also suggest that interactions between two or more of these elements may contribute to exon recognition,and provide candidate sequences for assessment as intronic splicing enhancers.
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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.