Learning the regulatory code of gene expression
Data-driven machine learning is the method of choice for predicting molecular phenotypes
from nucleotide sequence, modeling gene expression events including protein-DNA …
from nucleotide sequence, modeling gene expression events including protein-DNA …
Variant effect on splicing regulatory elements, branchpoint usage, and pseudoexonization: Strategies to enhance bioinformatic prediction using hereditary cancer …
It is possible to estimate the prior probability of pathogenicity for germline disease gene
variants based on bioinformatic prediction of variant effect/s. However, routinely used …
variants based on bioinformatic prediction of variant effect/s. However, routinely used …
DeePromoter: robust promoter predictor using deep learning
The promoter region is located near the transcription start sites and regulates transcription
initiation of the gene by controlling the binding of RNA polymerase. Thus, promoter region …
initiation of the gene by controlling the binding of RNA polymerase. Thus, promoter region …
iN6-Methyl (5-step): Identifying RNA N6-methyladenosine sites using deep learning mode via Chou's 5-step rules and Chou's general PseKNC
Abstract N6-methyladenosine (m 6 A) is an RNA methylation modification and it is involved
in various biological progresses such as translation, alternative splicing, degradation …
in various biological progresses such as translation, alternative splicing, degradation …
[HTML][HTML] iRNA-PseKNC (2methyl): Identify RNA 2'-O-methylation sites by convolution neural network and Chou's pseudo components
Abstract The 2'-O-methylation transferase is involved in the process of 2'-O-methylation. In
catalytic processes, the 2-hydroxy group of the ribose moiety of a nucleotide accept a methyl …
catalytic processes, the 2-hydroxy group of the ribose moiety of a nucleotide accept a methyl …
iDNA6mA (5-step rule): Identification of DNA N6-methyladenine sites in the rice genome by intelligent computational model via Chou's 5-step rule
DNA methylation is an elementary epigenetic process. The N6-methyladenine is related to a
large kind of biological processes ie, transcription, DNA replication, and repair. In genome …
large kind of biological processes ie, transcription, DNA replication, and repair. In genome …
SPiP: Splicing Prediction Pipeline, a machine learning tool for massive detection of exonic and intronic variant effects on mRNA splicing
Modeling splicing is essential for tackling the challenge of variant interpretation as each
nucleotide variation can be pathogenic by affecting pre‐mRNA splicing via …
nucleotide variation can be pathogenic by affecting pre‐mRNA splicing via …
iPseU-CNN: identifying RNA pseudouridine sites using convolutional neural networks
Pseudouridine is the most prevalent RNA modification and has been found in both
eukaryotes and prokaryotes. Currently, pseudouridine has been demonstrated in several …
eukaryotes and prokaryotes. Currently, pseudouridine has been demonstrated in several …
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 …