AIMC Topic: Gene Expression

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A Cascade Flexible Neural Forest Model for Cancer Subtypes Classification on Gene Expression Data.

Computational intelligence and neuroscience Oct 5, 2021
The correct classification of cancer subtypes is of great significance for the in-depth study of cancer pathogenesis and the realization of accurate treatment for cancer patients. In recent years, the classification of cancer subtypes using deep neur...
Humans Neural Networks, Computer Neoplasms Sample Size Gene Expression
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Deep GONet: self-explainable deep neural network based on Gene Ontology for phenotype prediction from gene expression data.

BMC bioinformatics Sep 22, 2021
BACKGROUND: With the rapid advancement of genomic sequencing techniques, massive production of gene expression data is becoming possible, which prompts the development of precision medicine. Deep learning is a promising approach for phenotype predict...
Phenotype Neoplasms Gene Expression Gene Ontology Humans Neural Networks, Computer
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MIDGET:Detecting differential gene expression on microarray data.

Computer methods and programs in biomedicine Sep 16, 2021
Backgound and Objective: Detecting differentially expressed genes is an important step in genome wide analysis and expression profiling. There are a wide array of algorithms used in today's research based on statistical approaches. Even though the cu...
Machine Learning Algorithms Gene Expression Neural Networks, Computer Microarray Analysis
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A Hierarchical Graph Convolution Network for Representation Learning of Gene Expression Data.

IEEE journal of biomedical and health informatics Aug 5, 2021
The curse of dimensionality, which is caused by high-dimensionality and low-sample-size, is a major challenge in gene expression data analysis. However, the real situation is even worse: labelling data is laborious and time-consuming, so only a small...
Gene Expression Supervised Machine Learning Humans
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A novel approach for the analysis of time-course gene expression data based on computing with words.

Journal of biomedical informatics Jul 14, 2021
In this paper, a novel approach is proposed for the analysis of time-course gene expression data based on the path-breaking work of Zadeh, Computing with Words. This method can automatically discover the patterns of temporal gene expression profile i...
Gene Expression Data Mining Linguistics Algorithms Gene Expression Profiling Fuzzy Logic Humans
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Loop-mediated isothermal amplification (LAMP) and machine learning application for early pregnancy detection using bovine vaginal mucosal membrane.

Biochemical and biophysical research communications Jul 10, 2021
An early and accurate pregnancy diagnosis method is required to improve the reproductive performance of cows. Here we developed an easy pregnancy detection method using vaginal mucosal membrane (VMM) with application of Reverse Transcription-Loop-med...
Pregnancy Female Reproducibility of Results Sensitivity and Specificity Machine Learning Cytokines Biomarkers Adaptor Proteins, Signal Transducing Gene Expression Mucous Membrane Ubiquitins Vagina CA-125 Antigen Animals Cattle Molecular Diagnostic Techniques RNA-Binding Proteins Membrane Proteins Nucleic Acid Amplification Techniques
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Using deep learning to identify bladder cancers with FGFR-activating mutations from histology images.

Cancer medicine Jun 10, 2021
BACKGROUND: In recent years, the fibroblast growth factor receptor (FGFR) pathway has been proven to be an important therapeutic target in bladder cancer. FGFR-targeted therapies are effective for patients with FGFR mutation, which can be discovered ...
Logistic Models Lymphocytes, Tumor-Infiltrating Urinary Bladder Neoplasms Mutation Molecular Targeted Therapy Receptor, Fibroblast Growth Factor, Type 3 Gene Expression Sensitivity and Specificity Male Deep Learning Neural Networks, Computer Receptor, Fibroblast Growth Factor, Type 2 Humans Databases, Factual Receptors, Fibroblast Growth Factor Female
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Machine learning analyses of antibody somatic mutations predict immunoglobulin light chain toxicity.

Nature communications Jun 10, 2021
In systemic light chain amyloidosis (AL), pathogenic monoclonal immunoglobulin light chains (LC) form toxic aggregates and amyloid fibrils in target organs. Prompt diagnosis is crucial to avoid permanent organ damage, but delayed diagnosis is common ...
Caenorhabditis elegans Immunoglobulin Light Chains Immunoglobulin Light-chain Amyloidosis Recombinant Proteins Databases, Genetic Machine Learning Models, Molecular Algorithms Humans Antibodies Animals Gene Expression Amino Acid Sequence Mutation
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The application of artificial intelligence methods to gene expression data for differentiation of uncomplicated and complicated appendicitis in children and adolescents - a proof of concept study.

BMC pediatrics Jun 8, 2021
BACKGROUND: Genome wide gene expression analysis has revealed hints for independent immunological pathways underlying the pathophysiologies of phlegmonous (PA) and gangrenous appendicitis (GA). Methods of artificial intelligence (AI) have successfull...
Child ROC Curve Gene Expression Appendicitis Proof of Concept Study Humans Artificial Intelligence Adolescent
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Active Learning and the Potential of Neural Networks Accelerate Molecular Screening for the Design of a New Molecule Effective against SARS-CoV-2.

BioMed research international May 25, 2021
A global pandemic has emerged following the appearance of the new severe acute respiratory virus whose official name is the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), strongly affecting the health sector as well as the world econom...
COVID-19 Drug Treatment Neural Networks, Computer Catalytic Domain SARS-CoV-2 Drug Design Humans Protein Structure, Secondary Molecular Docking Simulation Antiviral Agents Substrate Specificity Protein Interaction Domains and Motifs Protein Binding Biological Products Thermodynamics Coronavirus 3C Proteases Gene Expression Protease Inhibitors Kinetics Small Molecule Libraries
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