AIMC Topic: Gene Expression Profiling

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A Machine Learning Classifier for Assigning Individual Patients With Systemic Sclerosis to Intrinsic Molecular Subsets.

Arthritis & rheumatology (Hoboken, N.J.) Sep 2, 2019
OBJECTIVE: High-throughput gene expression profiling of tissue samples from patients with systemic sclerosis (SSc) has identified 4 "intrinsic" gene expression subsets: inflammatory, fibroproliferative, normal-like, and limited. Prior methods require...
Young Adult Adult Male Middle Aged Algorithms Female Aged Supervised Machine Learning High-Throughput Nucleotide Sequencing Datasets as Topic Humans Scleroderma, Systemic Machine Learning Gene Expression Profiling Transcriptome Gene Expression
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Machine learning enables detection of early-stage colorectal cancer by whole-genome sequencing of plasma cell-free DNA.

BMC cancer Aug 23, 2019
BACKGROUND: Blood-based methods using cell-free DNA (cfDNA) are under development as an alternative to existing screening tests. However, early-stage detection of cancer using tumor-derived cfDNA has proven challenging because of the small proportion...
Neoplasm Staging Genome, Human Circulating Tumor DNA Male Middle Aged Gene Expression Profiling Genomics Computational Biology Transcriptome ROC Curve Aged, 80 and over Colorectal Neoplasms Biomarkers, Tumor Female Reproducibility of Results Aged Humans Machine Learning
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Multigene signatures of responses to chemotherapy derived by biochemically-inspired machine learning.

Molecular genetics and metabolism Aug 19, 2019
Pharmacogenomic responses to chemotherapy drugs can be modeled by supervised machine learning of expression and copy number of relevant gene combinations. Such biochemical evidence can form the basis of derived gene signatures using cell line data, w...
Urinary Bladder Neoplasms Metabolic Networks and Pathways Supervised Machine Learning Breast Neoplasms Gene Dosage Gene Expression Profiling Drug Therapy Humans Transcriptome Female Cell Line, Tumor
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Identification of the expressome by machine learning on omics data.

Proceedings of the National Academy of Sciences of the United States of America Aug 16, 2019
Accurate annotation of plant genomes remains complex due to the presence of many pseudogenes arising from whole-genome duplication-generated redundancy or the capture and movement of gene fragments by transposable elements. Machine learning on genome...
Machine Learning Gene Expression Profiling Zea mays Databases, Nucleic Acid Genome, Plant Gene Expression Regulation, Plant
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BERMUDA: a novel deep transfer learning method for single-cell RNA sequencing batch correction reveals hidden high-resolution cellular subtypes.

Genome biology Aug 12, 2019
To fully utilize the power of single-cell RNA sequencing (scRNA-seq) technologies for identifying cell lineages and bona fide transcriptional signals, it is necessary to combine data from multiple experiments. We present BERMUDA (Batch Effect ReMoval...
Humans Algorithms T-Lymphocytes Leukocytes, Mononuclear Sequence Analysis, RNA Pancreas Gene Expression Profiling Deep Learning Single-Cell Analysis
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Artificial intelligence-directed prognostication of breast cancer.

EBioMedicine Aug 1, 2019
Artificial Intelligence Female Breast Neoplasms Biomarkers, Tumor Gene Expression Profiling Humans
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Inferring Gene Regulatory Networks of Metabolic Enzymes Using Gradient Boosted Trees.

IEEE journal of biomedical and health informatics Jul 30, 2019
Metabolic reprogramming is a hallmark of cancer. In cancer cells, transcription factors (TFs) govern metabolic reprogramming through abnormally increasing or decreasing the transcription rate of metabolic enzymes, which provides cancer cells growth a...
Gene Regulatory Networks Humans Enzymes Algorithms Lung Neoplasms Gene Expression Profiling Transcription Factors Transcriptome Machine Learning
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Differential gene expression and gene ontologies associated with increasing water-stress in leaf and root transcriptomes of perennial ryegrass (Lolium perenne).

PloS one Jul 30, 2019
Perennial ryegrass (Lolium perenne) is a forage and amenity grass species widely cultivated in temperate regions worldwide. As such, perennial ryegrass populations are exposed to a range of environmental conditions and stresses on a seasonal basis an...
Plant Proteins Gene Ontology Gene Expression Regulation, Plant Droughts Lolium Plant Leaves Gene Expression Profiling Plant Roots Transcriptome Dehydration Genotype
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scGen predicts single-cell perturbation responses.

Nature methods Jul 29, 2019
Accurately modeling cellular response to perturbations is a central goal of computational biology. While such modeling has been based on statistical, mechanistic and machine learning models in specific settings, no generalization of predictions to ph...
Phagocytes Mice Computational Biology Species Specificity Gene Expression Profiling Algorithms Transcriptome Computer Simulation Single-Cell Analysis Animals Leukocytes, Mononuclear Humans Machine Learning
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Identification of the gene signature reflecting schizophrenia's etiology by constructing artificial intelligence-based method of enhanced reproducibility.

CNS neuroscience & therapeutics Jul 27, 2019
AIMS: As one of the most fundamental questions in modern science, "what causes schizophrenia (SZ)" remains a profound mystery due to the absence of objective gene markers. The reproducibility of the gene signatures identified by independent studies i...
Humans Artificial Intelligence Databases, Genetic Schizophrenia Reproducibility of Results Gene Expression Profiling Random Allocation
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