AIMC Topic: Transcriptome

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Machine-Learning Prediction of Oral Drug-Induced Liver Injury (DILI) via Multiple Features and Endpoints.

BioMed research international May 19, 2020
Drug discovery is a costly process which usually takes more than 10 years and billions of dollars for one successful drug to enter the market. Despite all the safety tests, drugs may still cause adverse reactions and be restricted in use or even with...
Computational Biology Databases, Genetic Area Under Curve Humans Chemical and Drug Induced Liver Injury Databases, Pharmaceutical Machine Learning Computer Simulation Transcriptome ROC Curve
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Database Mining of Genes of Prognostic Value for the Prostate Adenocarcinoma Microenvironment Using the Cancer Gene Atlas.

BioMed research international May 18, 2020
BACKGROUND: Prostate adenocarcinoma (PRAD) is a common malignant tumor in elderly men. Our research uses The Cancer Gene Atlas (TCGA) database to find potential related genes for predicting the prognosis of patients with PRAD.
Transcriptome Prostatic Neoplasms Humans Adult Protein Interaction Maps Algorithms Data Mining Tumor Microenvironment Prognosis Computational Biology Gene Ontology Male Aged Adenocarcinoma Middle Aged
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Single-cell transcriptome reveals the novel role of T-bet in suppressing the immature NK gene signature.

eLife May 14, 2020
The transcriptional activation and repression during NK cell ontology are poorly understood. Here, using single-cell RNA-sequencing, we reveal a novel role for T-bet in suppressing the immature gene signature during murine NK cell development. Based ...
Cluster Analysis Mice, Inbred C57BL Mice, Knockout Proto-Oncogene Proteins c-akt Transcriptome Single-Cell Analysis RNA-Seq Genotype Mechanistic Target of Rapamycin Complex 2 Rapamycin-Insensitive Companion of mTOR Protein Regulatory-Associated Protein of mTOR T-Box Domain Proteins T-bet Transcription Factor Bone Marrow Cells Gene Expression Regulation Killer Cells, Natural Forkhead Box Protein O1 Machine Learning Phenotype Animals Gene Expression Profiling
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RadAtlas 1.0: a knowledgebase focusing on radiation-associated genes.

International journal of radiation biology May 12, 2020
Ionizing radiation has very complex biological effects, such as inducing damage to DNA and proteins, ionizing water molecules to produce toxic free radicals, and triggering genetic and somatic effects. Understanding the biomolecular response mechani...
Databases, Genetic Transcriptome Knowledge Bases Data Mining Molecular Sequence Annotation
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Sparsity-Penalized Stacked Denoising Autoencoders for Imputing Single-Cell RNA-Seq Data.

Genes May 11, 2020
Single-cell RNA-seq (scRNA-seq) is quite prevalent in studying transcriptomes, but it suffers from excessive zeros, some of which are true, but others are false. False zeros, which can be seen as missing data, obstruct the downstream analysis of sing...
Humans Computer Simulation Leukocytes, Mononuclear Transcriptome Deep Learning Datasets as Topic Fetal Blood Data Compression Single-Cell Analysis RNA-Seq Proteins RNA
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Analysis of gene expression profiles of lung cancer subtypes with machine learning algorithms.

Biochimica et biophysica acta. Molecular basis of disease Apr 28, 2020
Lung cancer is one of the most common cancer types worldwide and causes more than one million deaths annually. Lung adenocarcinoma (AC) and lung squamous cell cancer (SCC) are two major lung cancer subtypes and have different characteristics in sever...
Datasets as Topic Humans Tumor Suppressor Proteins Machine Learning Adenosine Triphosphatases Carcinoma, Squamous Cell Terminology as Topic Membrane Transport Proteins Serpins Gene Expression Profiling Gene Expression Regulation, Neoplastic Monte Carlo Method Transcriptome Transcription Factors Adenocarcinoma of Lung Lung Neoplasms Diagnosis, Differential Cadherins Cystatin A Computational Biology
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Fold-Change-Specific Enrichment Analysis (FSEA): Quantification of Transcriptional Response Magnitude for Functional Gene Groups.

Genes Apr 17, 2020
Gene expression profiling data contains more information than is routinely extracted with standard approaches. Here we present Fold-Change-Specific Enrichment Analysis (FSEA), a new method for functional annotation of differentially expressed genes f...
Humans Algorithms Biomarkers Gene Expression Profiling Transcriptome Computational Biology Databases, Genetic Gene Ontology
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Unveiling new disease, pathway, and gene associations via multi-scale neural network.

PloS one Apr 6, 2020
Diseases involve complex modifications to the cellular machinery. The gene expression profile of the affected cells contains characteristic patterns linked to a disease. Hence, new biological knowledge about a disease can be extracted from these prof...
Comorbidity Transcriptome Signal Transduction ROC Curve Humans Models, Biological Gene Regulatory Networks Disease Neural Networks, Computer Computational Biology Prognosis
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Deep learning-based cancer survival prognosis from RNA-seq data: approaches and evaluations.

BMC medical genomics Apr 3, 2020
BACKGROUND: Recent advances in kernel-based Deep Learning models have introduced a new era in medical research. Originally designed for pattern recognition and image processing, Deep Learning models are now applied to survival prognosis of cancer pat...
RNA-Seq Gene Regulatory Networks Computational Biology Gene Expression Regulation, Neoplastic Survival Rate Aged Biomarkers, Tumor Aged, 80 and over Male Young Adult Middle Aged Adult Humans Neoplasms Algorithms Transcriptome Prognosis Deep Learning Female Adolescent
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Estimating gene expression from DNA methylation and copy number variation: A deep learning regression model for multi-omics integration.

Genomics Mar 29, 2020
Gene expression analysis plays a significant role for providing molecular insights in cancer. Various genetic and epigenetic factors (being dealt under multi-omics) affect gene expression giving rise to cancer phenotypes. A recent growth in understan...
Genomics Epigenomics DNA Methylation DNA Copy Number Variations Linear Models Deep Learning Transcriptome Liver Neoplasms Carcinoma, Hepatocellular RNA-Seq
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