AIMC Topic: Gene Expression Regulation
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DeepMirTar: a deep-learning approach for predicting human miRNA targets.
Bioinformatics (Oxford, England)
Nov 15, 2018
MOTIVATION: MicroRNAs (miRNAs) are small non-coding RNAs that function in RNA silencing and post-transcriptional regulation of gene expression by targeting messenger RNAs (mRNAs). Because the underlying mechanisms associated with miRNA binding to mRN...
[Application of machine learning in the CRISPR/Cas9 system].
Yi chuan = Hereditas
Sep 20, 2018
The third generation of the CRISPR/Cas9-mediated genome fixed-point editing technology has been widely used in the field of gene editing and gene expression regulation. How to improve the on-target efficiency and specificity of this system, as well a...
DeFine: deep convolutional neural networks accurately quantify intensities of transcription factor-DNA binding and facilitate evaluation of functional non-coding variants.
Nucleic acids research
Jun 20, 2018
The complex system of gene expression is regulated by the cell type-specific binding of transcription factors (TFs) to regulatory elements. Identifying variants that disrupt TF binding and lead to human diseases remains a great challenge. To address ...
L1000FWD: fireworks visualization of drug-induced transcriptomic signatures.
Bioinformatics (Oxford, England)
Jun 15, 2018
MOTIVATION: As part of the NIH Library of Integrated Network-based Cellular Signatures program, hundreds of thousands of transcriptomic signatures were generated with the L1000 technology, profiling the response of human cell lines to over 20 000 sma...
Semi-supervised network inference using simulated gene expression dynamics.
Bioinformatics (Oxford, England)
Apr 1, 2018
MOTIVATION: Inferring the structure of gene regulatory networks from high-throughput datasets remains an important and unsolved problem. Current methods are hampered by problems such as noise, low sample size, and incomplete characterizations of regu...
Extreme learning machines for reverse engineering of gene regulatory networks from expression time series.
Bioinformatics (Oxford, England)
Apr 1, 2018
MOTIVATION: The reconstruction of gene regulatory networks (GRNs) from genes profiles has a growing interest in bioinformatics for understanding the complex regulatory mechanisms in cellular systems. GRNs explicitly represent the cause-effect of regu...
Machine-Learning Prediction of Drug-Induced Cardiac Arrhythmia: Analysis of Gene Expression and Clustering.
Critical reviews in biomedical engineering
Jan 1, 2018
A marked delay in the electrical repolarization of heart ventricles is characterized by prolongation of the Q-T wave (QT) interval on a surface electrocardiogram. Such a delay can lead to potentially life-threatening cardiac arrhythmia (torsades de p...
Female
Reproducibility of Results
Clinical Trials as Topic
Humans
False Positive Reactions
Machine Learning
Torsades de Pointes
Arrhythmias, Cardiac
Electrocardiography
MAP Kinase Signaling System
Drug Design
Drug Evaluation, Preclinical
Signal Processing, Computer-Assisted
Sensitivity and Specificity
Support Vector Machine
Mice
Gene Expression Regulation
Gene Expression Profiling
Heart Ventricles
Heart
Rats
Animals
Cluster Analysis
Male
Evaluation of luteinizing hormone regulation of maturation and apoptosis, expression of LHR and FSHR in cumulus-oocyte complexes in Lanzhou fat-tailed sheep.
Polish journal of veterinary sciences
Dec 1, 2017
The present study aimed to assess LH effects on in vitro maturation (IVM) and apoptosis and also to explore the gene expressions of LHR and FSHR in cumulus-oocyte complexes (COCs) of the sheep. COCs were in vitro matured 24h in the IVM medium supplem...
Using neural networks for reducing the dimensions of single-cell RNA-Seq data.
Nucleic acids research
Sep 29, 2017
While only recently developed, the ability to profile expression data in single cells (scRNA-Seq) has already led to several important studies and findings. However, this technology has also raised several new computational challenges. These include ...
An efficient graph kernel method for non-coding RNA functional prediction.
Bioinformatics (Oxford, England)
Sep 1, 2017
MOTIVATION: The importance of RNA protein-coding gene regulation is by now well appreciated. Non-coding RNAs (ncRNAs) are known to regulate gene expression at practically every stage, ranging from chromatin packaging to mRNA translation. However the ...
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