AIMC Topic: Exons

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Improved ontology for eukaryotic single-exon coding sequences in biological databases.

Database : the journal of biological databases and curation
Efficient extraction of knowledge from biological data requires the development of structured vocabularies to unambiguously define biological terms. This paper proposes descriptions and definitions to disambiguate the term 'single-exon gene'. Eukaryo...

Predicting human splicing branchpoints by combining sequence-derived features and multi-label learning methods.

BMC bioinformatics
BACKGROUND: Alternative splicing is the critical process in a single gene coding, which removes introns and joins exons, and splicing branchpoints are indicators for the alternative splicing. Wet experiments have identified a great number of human sp...

Characterization and machine learning prediction of allele-specific DNA methylation.

Genomics
A large collection of Single Nucleotide Polymorphisms (SNPs) has been identified in the human genome. Currently, the epigenetic influences of SNPs on their neighboring CpG sites remain elusive. A growing body of evidence suggests that locus-specific ...

Machine-Learning-Based Analysis in Genome-Edited Cells Reveals the Efficiency of Clathrin-Mediated Endocytosis.

Cell reports
Cells internalize various molecules through clathrin-mediated endocytosis (CME). Previous live-cell imaging studies suggested that CME is inefficient, with about half of the events terminated. These CME efficiency estimates may have been confounded b...

Semi-supervised Learning Predicts Approximately One Third of the Alternative Splicing Isoforms as Functional Proteins.

Cell reports
Alternative splicing acts on transcripts from almost all human multi-exon genes. Notwithstanding its ubiquity, fundamental ramifications of splicing on protein expression remain unresolved. The number and identity of spliced transcripts that form sta...

An effective deep learning-based approach for splice site identification in gene expression.

Science progress
A crucial stage in eukaryote gene expression involves mRNA splicing by a protein assembly known as the spliceosome. This step significantly contributes to generating and properly operating the ultimate gene product. Since non-coding introns disrupt e...

SVPath: an accurate pipeline for predicting the pathogenicity of human exon structural variants.

Briefings in bioinformatics
Although there are a large number of structural variations in the chromosomes of each individual, there is a lack of more accurate methods for identifying clinical pathogenic variants. Here, we proposed SVPath, a machine learning-based method to pred...

eSkip-Finder: a machine learning-based web application and database to identify the optimal sequences of antisense oligonucleotides for exon skipping.

Nucleic acids research
Exon skipping using antisense oligonucleotides (ASOs) has recently proven to be a powerful tool for mRNA splicing modulation. Several exon-skipping ASOs have been approved to treat genetic diseases worldwide. However, a significant challenge is the d...

Prediction of Alzheimer's disease-specific phospholipase c gamma-1 SNV by deep learning-based approach for high-throughput screening.

Proceedings of the National Academy of Sciences of the United States of America
Exon splicing triggered by unpredicted genetic mutation can cause translational variations in neurodegenerative disorders. In this study, we discover Alzheimer's disease (AD)-specific single-nucleotide variants (SNVs) and abnormal exon splicing of ph...