ArticleBMC genomics2008
Prediction of alternatively skipped exons and splicing enhancers from exon junction arrays.
Article in BMC genomics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 12 citations in OpenAlex.
- ARID5A RNA-binding coordinates microglial defense and ferroptosis in iPSC-derived models.Nature communications · 2026Article
- Integrated multi-omics analysis of zinc-finger proteins uncovers roles in RNA regulation.Molecular cell · 2024Article
- Silencing proline-rich coiled-coil 2C inhibit the proliferation and metastasis of liver cancer cells.Journal of gastrointestinal oncology · 2023Article
- Article
- Protein Sam68 regulates the alternative splicing of survivin DEx3.The Journal of biological chemistry · 2017Article
- Human telomerase reverse transcriptase regulation by DNA methylation, transcription factor binding and alternative splicing (Review).International journal of oncology · 2016Review
- Systematic spatial bias in DNA microarray hybridization is caused by probe spot position-dependent variability in lateral diffusion.PloS one · 2011Article
- Computational identification of tissue-specific alternative splicing elements in mouse genes from RNA-Seq.Nucleic acids research · 2010Article
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundAlternative splicing of exons in a pre-mRNA transcript is an important mechanism which contributes to protein diversity in human. Arrays for detecting alternative splicing are available using several different probe designs, including those based on exon-junctions. In this work, we introduce a new method for predicting alternatively skipped exons from exon-junction arrays. Predictions based on our method are compared against controls and their sequences are analyzed to identify motifs important for regulating alternative splicing.
resultsOur comparison of several alternative methods shows that an exon-skipping score based on neighboring junctions best discriminates between positive and negative controls. Sequence analysis of our predicted exons confirms the presence of known splicing regulatory sequences. In addition, we also derive a set of development-related alternatively spliced genes based on fetal versus adult tissue comparisons and find that our predictions are consistent with their functional annotations. Ab initio motif finding algorithms are applied to identify several motifs that may be relevant for splicing during development.
conclusionThis work describes a new method for analyzing exon-junction arrays, identifies sequence motifs that are specific for alternative and constitutive splicing and suggests a role for several known splicing factors and their motifs in developmental regulation.
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