AIMC Topic: Gene Expression Regulation

Clear Filters Showing 51 to 60 of 275 articles

Characterizing collaborative transcription regulation with a graph-based deep learning approach.

PLoS computational biology Jun 6, 2022
Human epigenome and transcription activities have been characterized by a number of sequence-based deep learning approaches which only utilize the DNA sequences. However, transcription factors interact with each other, and their collaborative regulat...
Deep Learning DNA Humans Binding Sites Gene Expression Regulation Chromatin Protein Binding Transcription Factors
View on PubMed DOI

EPI-Mind: Identifying Enhancer-Promoter Interactions Based on Transformer Mechanism.

Interdisciplinary sciences, computational life sciences May 28, 2022
MOTIVATION: Enhancer-Promoter Interactions (EPIs) is an essential step in the gene regulation process. However, the detection of EPIs by traditional wet experimental techniques is time-consuming and expensive. Thus, computational methods would be ver...
Promoter Regions, Genetic Regulatory Sequences, Nucleic Acid Neural Networks, Computer Cell Line Gene Expression Regulation
View on PubMed DOI

Chromatin interaction-aware gene regulatory modeling with graph attention networks.

Genome research Apr 8, 2022
Linking distal enhancers to genes and modeling their impact on target gene expression are longstanding unresolved problems in regulatory genomics and critical for interpreting noncoding genetic variation. Here, we present a new deep learning approach...
Gene Regulatory Networks Transcription Factors Binding Sites Neural Networks, Computer Gene Expression Regulation Regulatory Sequences, Nucleic Acid Chromatin
View on PubMed DOI

Integration of gene co-expression analysis and multi-class SVM specifies the functional players involved in determining the fate of HTLV-1 infection toward the development of cancer (ATLL) or neurological disorder (HAM/TSP).

PloS one Jan 18, 2022
Human T-cell Leukemia Virus type-1 (HTLV-1) is an oncovirus that may cause two main life-threatening diseases including a cancer type named Adult T-cell Leukemia/Lymphoma (ATLL) and a neurological and immune disturbance known as HTLV-1 Associated Mye...
HTLV-I Infections Human T-lymphotropic virus 1 Leukemia-Lymphoma, Adult T-Cell Genetic Markers Gene Expression Regulation Nervous System Diseases Humans Gene Expression Profiling Support Vector Machine
View on PubMed DOI

The use of machine learning to discover regulatory networks controlling biological systems.

Molecular cell Jan 10, 2022
Biological systems are composed of a vast web of multiscale molecular interactors and interactions. High-throughput technologies, both bulk and single cell, now allow for investigation of the properties and quantities of these interactors. Computatio...
Computational Biology Signal Transduction Models, Biological Animals Protein Interaction Maps Gene Regulatory Networks Gene Expression Regulation Humans Machine Learning Research Design
View on PubMed DOI

Discovering cell types using manifold learning and enhanced visualization of single-cell RNA-Seq data.

Scientific reports Jan 7, 2022
Identifying relevant disease modules such as target cell types is a significant step for studying diseases. High-throughput single-cell RNA-Seq (scRNA-seq) technologies have advanced in recent years, enabling researchers to investigate cells individu...
Animals Single-Cell Analysis RNA-Seq Mice Humans Machine Learning RNA Gene Expression Regulation Databases, Genetic Cluster Analysis Cell Line
View on PubMed DOI

Biological features between miRNAs and their targets are unveiled from deep learning models.

Scientific reports Dec 10, 2021
MicroRNAs (miRNAs) are ~ 22 nucleotide ubiquitous gene regulators. They modulate a broad range of essential cellular processes linked to human health and diseases. Consequently, identifying miRNA targets and understanding how they function are critic...
MicroRNAs Models, Biological Gene Expression Regulation Databases, Nucleic Acid Gene Regulatory Networks Mutagenesis RNA Interference Humans Computational Biology Base Pairing RNA, Messenger Algorithms Deep Learning
View on PubMed DOI

Establishment of a 13 genes-based molecular prediction score model to discriminate the neurotoxic potential of food relevant-chemicals.

Toxicology letters Nov 5, 2021
Although many neurotoxicity prediction studies of food additives have been developed, they are applicable in a qualitative way. We aimed to develop a novel prediction score that is described quantitatively and precisely. We examined cell viability, r...
Cell Survival Calcium Central Nervous System Diseases Gene Expression Regulation Food Additives Humans Neural Stem Cells Neural Networks, Computer Cell Line, Tumor Food Contamination Machine Learning Reactive Oxygen Species Reproducibility of Results Risk Factors
View on PubMed DOI

A Feature Fusion Predictor for RNA Pseudouridine Sites with Particle Swarm Optimizer Based Feature Selection and Ensemble Learning Approach.

Current issues in molecular biology Nov 1, 2021
RNA pseudouridine modification is particularly important in a variety of cellular biological and physiological processes. It plays a significant role in understanding RNA functions, RNA structure stabilization, translation processes, etc. To understa...
Machine Learning Gene Expression Regulation Algorithms Computational Biology Pseudouridine Databases, Genetic Reproducibility of Results RNA
View on PubMed DOI

Deep learning and alignment of spatially resolved single-cell transcriptomes with Tangram.

Nature methods Oct 28, 2021
Charting an organs' biological atlas requires us to spatially resolve the entire single-cell transcriptome, and to relate such cellular features to the anatomical scale. Single-cell and single-nucleus RNA-seq (sc/snRNA-seq) can profile cells comprehe...
Transcriptome Gene Expression Regulation Animals Regulatory Sequences, Nucleic Acid Male Software RNA-Seq Deep Learning Chromatin Gene Expression Profiling Brain Single-Cell Analysis Mice Female Mice, Inbred C57BL
View on PubMed DOI
Popular Topics
Recent Journals