AIMC Topic: RNA-Seq

Clear Filters Showing 171 to 180 of 181 articles

A comprehensive overview and critical evaluation of gene regulatory network inference technologies.

Briefings in bioinformatics Sep 2, 2021
Gene regulatory network (GRN) is the important mechanism of maintaining life process, controlling biochemical reaction and regulating compound level, which plays an important role in various organisms and systems. Reconstructing GRN can help us to un...
Neoplasms Transcriptome RNA-Seq Machine Learning Biomarkers, Tumor Escherichia coli Databases, Genetic Bayes Theorem Gene Expression Regulation Gene Regulatory Networks Computational Biology Models, Genetic
View on PubMed DOI

Coupled co-clustering-based unsupervised transfer learning for the integrative analysis of single-cell genomic data.

Briefings in bioinformatics Jul 20, 2021
Unsupervised methods, such as clustering methods, are essential to the analysis of single-cell genomic data. The most current clustering methods are designed for one data type only, such as single-cell RNA sequencing (scRNA-seq), single-cell ATAC seq...
Humans Software Animals Single-Cell Analysis RNA-Seq Databases, Nucleic Acid Mice Unsupervised Machine Learning
View on PubMed DOI

Identification of pan-cancer Ras pathway activation with deep learning.

Briefings in bioinformatics Jul 20, 2021
The identification of hidden responders is often an essential challenge in precision oncology. A recent attempt based on machine learning has been proposed for classifying aberrant pathway activity from multiomic cancer data. However, we note several...
ras Proteins Deep Learning RNA-Seq Signal Transduction Programming Languages Gene Dosage Neoplasm Proteins Mutation Humans Neoplasms
View on PubMed DOI

scCancer: a package for automated processing of single-cell RNA-seq data in cancer.

Briefings in bioinformatics May 20, 2021
Molecular heterogeneities and complex microenvironments bring great challenges for cancer diagnosis and treatment. Recent advances in single-cell RNA-sequencing (scRNA-seq) technology make it possible to study cancer cell heterogeneities and microenv...
Neoplasms Single-Cell Analysis RNA-Seq Humans Machine Learning Software Gene Expression Regulation, Neoplastic Databases, Nucleic Acid RNA, Neoplasm
View on PubMed DOI

Integration and transfer learning of single-cell transcriptomes via cFIT.

Proceedings of the National Academy of Sciences of the United States of America Mar 9, 2021
Large, comprehensive collections of single-cell RNA sequencing (scRNA-seq) datasets have been generated that allow for the full transcriptional characterization of cell types across a wide variety of biological and clinical conditions. As new methods...
Animals Transcriptome Single-Cell Analysis RNA-Seq Mice Exome Sequencing Humans Machine Learning Software
View on PubMed DOI

Identification of Gene Regulatory Networks from Single-Cell Expression Data.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2021
Single-cell RNAseq is an emerging technology that allows the quantification of gene expression in individual cells. In plants, single-cell sequencing technology has been applied to generate root cell expression maps under many experimental conditions...
Programming Languages Chromatin Chromatin Immunoprecipitation Sequencing Machine Learning Software Single-Cell Analysis Computational Biology Sequence Analysis, DNA RNA-Seq Gene Regulatory Networks
View on PubMed DOI

Style transfer with variational autoencoders is a promising approach to RNA-Seq data harmonization and analysis.

Bioinformatics (Oxford, England) Dec 22, 2020
MOTIVATION: The transcriptomic data are being frequently used in the research of biomarker genes of different diseases and biological states. The most common tasks there are the data harmonization and treatment outcome prediction. Both of them can be...
Semantics Exome Sequencing Neural Networks, Computer Software RNA-Seq
View on PubMed DOI

Single-cell analyses and machine learning define hematopoietic progenitor and HSC-like cells derived from human PSCs.

Blood Dec 17, 2020
Hematopoietic stem and progenitor cells (HSPCs) develop in distinct waves at various anatomical sites during embryonic development. The in vitro differentiation of human pluripotent stem cells (hPSCs) recapitulates some of these processes; however, i...
Humans Machine Learning Single-Cell Analysis RNA-Seq Pluripotent Stem Cells Liver Hematopoietic Stem Cells Gene Expression Regulation Antigens, Differentiation Fetus
View on PubMed DOI

Machine Learning Analysis of Blood microRNA Data in Major Depression: A Case-Control Study for Biomarker Discovery.

The international journal of neuropsychopharmacology Nov 26, 2020
BACKGROUND: There is a lack of reliable biomarkers for major depressive disorder (MDD) in clinical practice. However, several studies have shown an association between alterations in microRNA levels and MDD, albeit none of them has taken advantage of...
Affect Antidepressive Agents Humans Circulating MicroRNA Biomarkers Severity of Illness Index Treatment Outcome Depressive Disorder, Major Case-Control Studies Predictive Value of Tests Unsupervised Machine Learning RNA-Seq Supervised Machine Learning
View on PubMed DOI

Prediction of condition-specific regulatory genes using machine learning.

Nucleic acids research Jun 19, 2020
Recent advances in genomic technologies have generated data on large-scale protein-DNA interactions and open chromatin regions for many eukaryotic species. How to identify condition-specific functions of transcription factors using these data has bec...
Arabidopsis Proteins Transcription Factors Arabidopsis Single-Cell Analysis Machine Learning Promoter Regions, Genetic Datasets as Topic Genes, Regulator RNA-Seq Gene Expression Profiling Gene Expression Regulation, Plant Gene Regulatory Networks Deep Learning Stress, Physiological Genes, Plant
View on PubMed DOI
Popular Topics
Recent Journals