AIMC Topic: Transcriptome

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Gene Expression Profile Prediction in Uveal Melanoma Using Deep Learning: A Pilot Study for the Development of an Alternative Survival Prediction Tool.

Ophthalmology. Retina Jun 18, 2020
Humans Melanoma Gene Expression Regulation, Neoplastic Anterior Eye Segment Uveal Neoplasms Uveal Melanoma Biomarkers, Tumor Transcriptome Deep Learning Pilot Projects
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A Support Vector Machine Model Predicting the Risk of Duodenal Cancer in Patients with Familial Adenomatous Polyposis at the Transcript Levels.

BioMed research international Jun 16, 2020
OBJECTIVE: Familial adenomatous polyposis (FAP) is one major type of inherited duodenal cancer. The estimate of duodenal cancer risk in patients with FAP is critical for selecting the optimal treatment strategy.
Adenomatous Polyposis Coli Computational Biology Duodenal Neoplasms Support Vector Machine Humans Databases, Genetic Risk Assessment Metabolic Networks and Pathways Transcriptome
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Combining gene expression profiling and machine learning to diagnose B-cell non-Hodgkin lymphoma.

Blood cancer journal May 22, 2020
Non-Hodgkin B-cell lymphomas (B-NHLs) are a highly heterogeneous group of mature B-cell malignancies. Their classification thus requires skillful evaluation by expert hematopathologists, but the risk of error remains higher in these tumors than in ma...
Humans Machine Learning Diagnosis, Computer-Assisted Progression-Free Survival Lymphoma, B-Cell Tumor Microenvironment Biomarkers, Tumor Gene Expression Profiling 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...
Chemical and Drug Induced Liver Injury Databases, Pharmaceutical Computational Biology Databases, Genetic Area Under Curve Machine Learning Computer Simulation Transcriptome ROC Curve Humans
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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 Humans Prostatic Neoplasms Algorithms Tumor Microenvironment Data Mining Prognosis Male Protein Interaction Maps Gene Ontology Aged Middle Aged Computational Biology Adult Adenocarcinoma
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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 ...
Machine Learning T-Box Domain Proteins T-bet Transcription Factor Mechanistic Target of Rapamycin Complex 2 Cluster Analysis Bone Marrow Cells Rapamycin-Insensitive Companion of mTOR Protein Transcriptome Phenotype Mice, Inbred C57BL Gene Expression Regulation Regulatory-Associated Protein of mTOR Single-Cell Analysis Animals Mice, Knockout Killer Cells, Natural RNA-Seq Gene Expression Profiling Proto-Oncogene Proteins c-akt Genotype Forkhead Box Protein O1
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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...
Data Mining Molecular Sequence Annotation Transcriptome Databases, Genetic Knowledge Bases
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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...
Deep Learning Single-Cell Analysis RNA-Seq Proteins RNA Datasets as Topic Fetal Blood Data Compression Humans Computer Simulation Leukocytes, Mononuclear Transcriptome
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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...
Carcinoma, Squamous Cell Gene Expression Profiling Transcriptome Lung Neoplasms Computational Biology Gene Expression Regulation, Neoplastic Transcription Factors Serpins Diagnosis, Differential Adenocarcinoma of Lung Adenosine Triphosphatases Cystatin A Humans Terminology as Topic Cadherins Machine Learning Membrane Transport Proteins Datasets as Topic Monte Carlo Method Tumor Suppressor Proteins
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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...
Computational Biology Databases, Genetic Gene Ontology Humans Algorithms Biomarkers Gene Expression Profiling Transcriptome
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