AIMC Topic: Gene Expression

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Optimal Deep Learning Enabled Prostate Cancer Detection Using Microarray Gene Expression.

Journal of healthcare engineering Mar 10, 2022
Prostate cancer is the main cause of death over the globe. Earlier detection and classification of cancer is highly important to improve patient health. Previous studies utilized statistical and machine learning (ML) techniques for prostate cancer de...
Gene Expression Prostatic Neoplasms Male Deep Learning Artificial Intelligence Algorithms Humans
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Performance Analysis of Deep Learning Models for Binary Classification of Cancer Gene Expression Data.

Journal of healthcare engineering Mar 9, 2022
The classification of patients as cancer and normal patients by applying the computational methods on their gene expression profiles is an extremely important task. Recently, deep learning models, mainly multilayer perceptron and convolutional neural...
Neoplasms Deep Learning Gene Expression Humans Neural Networks, Computer
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Deep-Learning-Based Cancer Profiles Classification Using Gene Expression Data Profile.

Journal of healthcare engineering Jan 7, 2022
The quantity of data required to give a valid analysis grows exponentially as machine learning dimensionality increases. In a single experiment, microarrays or gene expression profiling assesses and determines gene expression levels and patterns in v...
Deep Learning Gene Expression Oligonucleotide Array Sequence Analysis Neoplasms Gene Expression Profiling Humans Algorithms
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Interpretable generative deep learning: an illustration with single cell gene expression data.

Human genetics Jan 6, 2022
Deep generative models can learn the underlying structure, such as pathways or gene programs, from omics data. We provide an introduction as well as an overview of such techniques, specifically illustrating their use with single-cell gene expression ...
Neural Networks, Computer Deep Learning Gene Expression
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PanClassif: Improving pan cancer classification of single cell RNA-seq gene expression data using machine learning.

Genomics Jan 6, 2022
Cancer is one of the major causes of human death per year. In recent years, cancer identification and classification using machine learning have gained momentum due to the availability of high throughput sequencing data. Using RNA-seq, cancer researc...
Neoplasms Gene Expression Profiling RNA-Seq Software Algorithms Sequence Analysis, RNA Gene Expression Humans Machine Learning
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Optical Biopsy Using a Neural Network to Predict Gene Expression From Photos of Wounds.

The Journal of surgical research Nov 23, 2021
BACKGROUND: The clinical characterization of the biological status of complex wounds remains a considerable challenge. Digital photography provides a non-invasive means of obtaining wound information and is currently employed to assess wounds qualita...
Neural Networks, Computer Dogs Animals Gene Expression Pilot Projects Biopsy Image Processing, Computer-Assisted
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Identification of diagnostic signatures in ulcerative colitis patients via bioinformatic analysis integrated with machine learning.

Human cell Nov 3, 2021
Ulcerative colitis (UC) is an immune-related disorder with enhanced prevalence globally. Early diagnosis is critical for the effective treatment of UC. However, it still lacks specific diagnostic signatures. The aim of our study was to explore effici...
alpha-Defensins Pancreatitis-Associated Proteins Gene Expression Lithostathine Logistic Models Colitis, Ulcerative Humans Genetic Association Studies Computational Biology Machine Learning
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DeepFlu: a deep learning approach for forecasting symptomatic influenza A infection based on pre-exposure gene expression.

Computer methods and programs in biomedicine Oct 25, 2021
BACKGROUND AND OBJECTIVE: Not everyone gets sick after an exposure to influenza A viruses (IAV). Although KLRD1 has been identified as a potential biomarker for influenza susceptibility, it remains unclear whether forecasting symptomatic flu infectio...
Influenza A Virus, H1N1 Subtype Gene Expression Influenza A Virus, H3N2 Subtype Humans Deep Learning Influenza, Human
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DUBStepR is a scalable correlation-based feature selection method for accurately clustering single-cell data.

Nature communications Oct 6, 2021
Feature selection (marker gene selection) is widely believed to improve clustering accuracy, and is thus a key component of single cell clustering pipelines. Existing feature selection methods perform inconsistently across datasets, occasionally even...
Single-Cell Analysis Machine Learning Chromatin Immunoprecipitation Sequencing Cluster Analysis RNA-Seq Humans Software Gene Expression Algorithms Genes, Mitochondrial Arthritis, Rheumatoid Research Design Sequence Analysis, RNA
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Framework for classification of cancer gene expression data using Bayesian hyper-parameter optimization.

Medical & biological engineering & computing Oct 5, 2021
Computational classification of cancers is an important research problem. Gene expression data has 1000s of features, very few samples, and a class imbalance problem. In this paper, we have proposed a framework for the classification of cancer gene e...
Support Vector Machine Bayes Theorem Algorithms Humans Gene Expression Neoplasms
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