AIMC Topic: Transcriptome

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Integrative transcriptomic, proteomic, and machine learning approach to identifying feature genes of atrial fibrillation using atrial samples from patients with valvular heart disease.

BMC cardiovascular disorders Jan 28, 2021
BACKGROUND: Atrial fibrillation (AF) is the most common arrhythmia with poorly understood mechanisms. We aimed to investigate the biological mechanism of AF and to discover feature genes by analyzing multi-omics data and by applying a machine learnin...
Female Male Middle Aged Gene Expression Profiling Transcriptome Case-Control Studies Protein Interaction Maps Heart Atria Humans Machine Learning Heart Valve Diseases Oligonucleotide Array Sequence Analysis Signal Transduction Databases, Genetic Bayes Theorem Atrial Fibrillation Gene Regulatory Networks Genetic Association Studies Proteomics
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Machine Learning Analysis of Longevity-Associated Gene Expression Landscapes in Mammals.

International journal of molecular sciences Jan 22, 2021
One of the important questions in aging research is how differences in transcriptomics are associated with the longevity of various species. Unfortunately, at the level of individual genes, the links between expression in different organs and maximum...
Regression Analysis Bayes Theorem Gene Expression Mammals Linear Models Tissue Distribution Longevity RNA-Seq Computational Biology Models, Genetic Liver Aging Gene Expression Profiling Transcriptome Humans Machine Learning Algorithms Brain Animals
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Mining influential genes based on deep learning.

BMC bioinformatics Jan 22, 2021
BACKGROUND: Currently, large-scale gene expression profiling has been successfully applied to the discovery of functional connections among diseases, genetic perturbation, and drug action. To address the cost of an ever-expanding gene expression prof...
Genomics Genome Gene Expression Profiling Transcriptome Deep Learning
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On transformative adaptive activation functions in neural networks for gene expression inference.

PloS one Jan 14, 2021
Gene expression profiling was made more cost-effective by the NIH LINCS program that profiles only ∼1, 000 selected landmark genes and uses them to reconstruct the whole profile. The D-GEX method employs neural networks to infer the entire profile. H...
Humans Neural Networks, Computer Gene Expression Profiling Transcriptome Gene Regulatory Networks Computational Biology
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Prediction of future gene expression profile by analyzing its past variation pattern.

Gene expression patterns : GEP Jan 12, 2021
A number of initial Hematopoietic Stem Cells (HSC) are considered in a container that are able to divide into HSCs or differentiate into various types of descendant cells. In this paper, a method is designed to predict an approximate gene expression ...
Humans Neural Networks, Computer Hematopoietic Stem Cells Gene Expression Profiling Transcriptome Hematopoiesis Gene Expression Regulation, Developmental
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Integration of human cell lines gene expression and chemical properties of drugs for Drug Induced Liver Injury prediction.

Biology direct Jan 9, 2021
MOTIVATION: Drug-induced liver injury (DILI) is one of the primary problems in drug development. Early prediction of DILI can bring a significant reduction in the cost of clinical trials. In this work we examined whether occurrence of DILI can be pre...
Drug Discovery Chemical and Drug Induced Liver Injury Humans Transcriptome Machine Learning Cell Line Algorithms Risk Assessment
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Modeling drug mechanism of action with large scale gene-expression profiles using GPAR, an artificial intelligence platform.

BMC bioinformatics Jan 7, 2021
BACKGROUND: Querying drug-induced gene expression profiles with machine learning method is an effective way for revealing drug mechanism of actions (MOAs), which is strongly supported by the growth of large scale and high-throughput gene expression d...
Pharmacology Computational Biology Databases, Genetic Pharmaceutical Preparations Artificial Intelligence Software Transcriptome
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Integrated meta-analysis and machine learning approach identifies acyl-CoA thioesterase with other novel genes responsible for biofilm development in Staphylococcus aureus.

Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases Jan 1, 2021
Biofilm forming Staphylococcus aureus is a major threat to the health-care industry. It is important to understand the differences between planktonic and biofilm growth forms in the pathogen since conventional treatments targeting the planktonic form...
Humans Algorithms Transcriptome Staphylococcal Infections Datasets as Topic Microarray Analysis Gene Expression Regulation, Bacterial Biofilms RNA-Seq Staphylococcus aureus Supervised Machine Learning
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Construction and analysis of a joint diagnosis model of random forest and artificial neural network for heart failure.

Aging Dec 26, 2020
Heart failure is a global health problem that affects approximately 26 million people worldwide. As conventional diagnostic techniques for heart failure have been in practice with various limitations, it is necessary to develop novel diagnostic model...
Lipocalins Serpins Transcriptome Humans RNA-Binding Proteins Heme Oxygenase (Decyclizing) RNA Splicing Factors Databases, Genetic Receptors, Interleukin Neural Networks, Computer Heart Failure Machine Learning
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Characterization of Antiphospholipid Syndrome Atherothrombotic Risk by Unsupervised Integrated Transcriptomic Analyses.

Arteriosclerosis, thrombosis, and vascular biology Dec 24, 2020
OBJECTIVE: Our aim was to characterize distinctive clinical antiphospholipid syndrome phenotypes and identify novel microRNA (miRNA)-mRNA-intracellular signaling regulatory networks in monocytes linked to cardiovascular disease. Approach and Results:...
Oligonucleotide Array Sequence Analysis Male Antiphospholipid Syndrome Middle Aged Unsupervised Machine Learning Monocytes Female Risk Assessment Thrombosis Signal Transduction Humans Gene Expression Regulation Risk Factors Transcriptome Gene Expression Profiling Cluster Analysis Cells, Cultured Case-Control Studies Adult MicroRNAs Protein Interaction Maps Gene Regulatory Networks
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