Alternative splicing regulatory networks: functions, mechanisms, and evolution
J Ule, BJ Blencowe - Molecular cell, 2019 - cell.com
High-throughput sequencing-based methods and their applications in the study of
transcriptomes have revolutionized our understanding of alternative splicing. Networks of …
transcriptomes have revolutionized our understanding of alternative splicing. Networks of …
Machine learning meets omics: applications and perspectives
The innovation of biotechnologies has allowed the accumulation of omics data at an
alarming rate, thus introducing the era of 'big data'. Extracting inherent valuable knowledge …
alarming rate, thus introducing the era of 'big data'. Extracting inherent valuable knowledge …
Decoding disease: from genomes to networks to phenotypes
AK Wong, RSG Sealfon, CL Theesfeld… - Nature Reviews …, 2021 - nature.com
Interpreting the effects of genetic variants is key to understanding individual susceptibility to
disease and designing personalized therapeutic approaches. Modern experimental …
disease and designing personalized therapeutic approaches. Modern experimental …
Benchmarking deep learning splice prediction tools using functional splice assays
Hereditary disorders are frequently caused by genetic variants that affect pre‐messenger
RNA splicing. Though genetic variants in the canonical splice motifs are almost always …
RNA splicing. Though genetic variants in the canonical splice motifs are almost always …
Isoform age-splice isoform profiling using long-read technologies
Alternative splicing (AS) of RNA is a key mechanism that results in the expression of multiple
transcript isoforms from single genes and leads to an increase in the complexity of both the …
transcript isoforms from single genes and leads to an increase in the complexity of both the …
A CNN-based RNA N6-methyladenosine site predictor for multiple species using heterogeneous features representation
Post-transcriptional modification such as N6-methyladenosine (m6A) has a crucial role in
the stability and regulation of gene expression. Therefore, the identification of m6A is highly …
the stability and regulation of gene expression. Therefore, the identification of m6A is highly …
4mCCNN: Identification of N4-methylcytosine sites in prokaryotes using convolutional neural network
The epigenetic modification, DNA N4-methylcytosine (4mC) plays an important role in DNA
expression, repair, and replication. It simply plays a crucial role in restriction-modification …
expression, repair, and replication. It simply plays a crucial role in restriction-modification …
Identifying enhancers and their strength by the integration of word embedding and convolution neural network
The enhancer is a short regulatory element that plays a major role in up-regulating
eukaryotic gene expression. To identify enhancers, an experimental process takes a long …
eukaryotic gene expression. To identify enhancers, an experimental process takes a long …
Identification of functional piRNAs using a convolutional neural network
Piwi-interacting RNAs (piRNAs) are a distinct sub-class of small non-coding RNAs that are
mainly responsible for germline stem cell maintenance, gene stability, and maintaining …
mainly responsible for germline stem cell maintenance, gene stability, and maintaining …
ncRDeep: Non-coding RNA classification with convolutional neural network
A non-coding RNA (ncRNA) is a kind of RNA that is not converted into protein, however, it is
involved in many biological processes, diseases, and cancers. Numerous ncRNAs have …
involved in many biological processes, diseases, and cancers. Numerous ncRNAs have …