AIMC Topic: Gene Expression Profiling

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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...
Gene Expression Regulation, Plant Droughts Lolium Plant Leaves Transcriptome Gene Expression Profiling Plant Roots Genotype Dehydration Plant Proteins Gene Ontology
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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...
Species Specificity Phagocytes Single-Cell Analysis Mice Computational Biology Leukocytes, Mononuclear Gene Expression Profiling Transcriptome Humans Computer Simulation Animals Machine Learning Algorithms
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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...
Schizophrenia Random Allocation Humans Gene Expression Profiling Databases, Genetic Artificial Intelligence Reproducibility of Results
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Wx: a neural network-based feature selection algorithm for transcriptomic data.

Scientific reports Jul 19, 2019
Next-generation sequencing (NGS), which allows the simultaneous sequencing of billions of DNA fragments simultaneously, has revolutionized how we study genomics and molecular biology by generating genome-wide molecular maps of molecules of interest. ...
Neural Networks, Computer Algorithms Biomarkers, Tumor Humans High-Throughput Nucleotide Sequencing Datasets as Topic RNA, Neoplasm Genes, Neoplasm Neoplasms Gene Expression Profiling Transcriptome
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Screening and Bioinformatics Analysis of IgA Nephropathy Gene Based on GEO Databases.

BioMed research international Jul 16, 2019
PURPOSE: To identify novel biomarkers of IgA nephropathy (IgAN) through bioinformatics analysis and elucidate the possible molecular mechanism.
Gene Ontology Computational Biology Humans Databases, Nucleic Acid Glomerulonephritis, IGA Gene Expression Profiling MAP Kinase Signaling System Gene Regulatory Networks
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Exploration of potential key pathways and genes in multiple ocular cancers through bioinformatics analysis.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie Jul 15, 2019
PURPOSE: Primary cancers of the eye are common in ocular diseases. The objective of this study was to explore the underlying mechanisms and the potential target genes in multiple ocular cancers by bioinformatics approach.
Eye Proteins Gene Ontology Computational Biology Gene Expression Regulation, Neoplastic Signal Transduction Humans Eye Neoplasms Gene Expression Profiling
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Deconvolution of autoencoders to learn biological regulatory modules from single cell mRNA sequencing data.

BMC bioinformatics Jul 8, 2019
BACKGROUND: Unsupervised machine learning methods (deep learning) have shown their usefulness with noisy single cell mRNA-sequencing data (scRNA-seq), where the models generalize well, despite the zero-inflation of the data. A class of neural network...
Cluster Analysis Unsupervised Machine Learning Neural Networks, Computer RNA, Messenger Sequence Analysis, RNA Gene Expression Profiling Single-Cell Analysis
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Machine learning approaches to predict lupus disease activity from gene expression data.

Scientific reports Jul 3, 2019
The integration of gene expression data to predict systemic lupus erythematosus (SLE) disease activity is a significant challenge because of the high degree of heterogeneity among patients and study cohorts, especially those collected on different mi...
Machine Learning Disease Progression Gene Expression Profiling Transcriptome Humans Gene Expression Lupus Erythematosus, Systemic Gene Expression Regulation Molecular Sequence Annotation ROC Curve Gene Regulatory Networks Computational Biology
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Discriminant analysis and machine learning approach for evaluating and improving the performance of immunohistochemical algorithms for COO classification of DLBCL.

Journal of translational medicine Jun 11, 2019
BACKGROUND: Diffuse large B-cell lymphoma (DLBCL) is classified into germinal center-like (GCB) and non-germinal center-like (non-GCB) cell-of-origin groups, entities driven by different oncogenic pathways with different clinical outcomes. DLBCL clas...
Machine Learning Algorithms Female Adult Lymphoma, Large B-Cell, Diffuse Aged Aged, 80 and over Humans Decision Trees Immunohistochemistry Bayes Theorem Germinal Center Male Discriminant Analysis Middle Aged B-Lymphocytes Gene Expression Profiling
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Identification of leukemia stem cell expression signatures through Monte Carlo feature selection strategy and support vector machine.

Cancer gene therapy May 29, 2019
Acute myeloid leukemia (AML) is a type of blood cancer characterized by the rapid growth of immature white blood cells from the bone marrow. Therapy resistance resulting from the persistence of leukemia stem cells (LSCs) are found in numerous patient...
Drug Resistance, Neoplasm Monte Carlo Method Neoplastic Stem Cells Feasibility Studies Datasets as Topic Humans Gene Expression Profiling Biomarkers, Tumor Computational Biology Leukemia, Myeloid, Acute Models, Genetic Support Vector Machine
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