AIMC Topic: Oligonucleotide Array Sequence Analysis

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Analysis of defective pathways and drug repositioning in Multiple Sclerosis via machine learning approaches.

Computers in biology and medicine Oct 9, 2019
BACKGROUND: Although some studies show that there could be a genetic predisposition to develop Multiple Sclerosis (MS), attempts to find genetic signatures related to MS diagnosis and development are extremely rare.
Gene Expression Regulation Oligonucleotide Array Sequence Analysis Databases, Nucleic Acid Humans Models, Immunological Machine Learning Drug Repositioning Metabolic Networks and Pathways Male Multiple Sclerosis Signal Transduction Retrospective Studies Female
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Compendiums of cancer transcriptomes for machine learning applications.

Scientific data Oct 8, 2019
There are massive transcriptome profiles in the form of microarray. The challenge is that they are processed using diverse platforms and preprocessing tools, requiring considerable time and informatics expertise for cross-dataset analyses. If there e...
Neoplasms Transcriptome RNA-Seq Oligonucleotide Array Sequence Analysis Humans Machine Learning Algorithms
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C-HMOSHSSA: Gene selection for cancer classification using multi-objective meta-heuristic and machine learning methods.

Computer methods and programs in biomedicine Jun 29, 2019
BACKGROUND AND OBJECTIVE: Over the last two decades, DNA microarray technology has emerged as a powerful tool for early cancer detection and prevention. It helps to provide a detailed overview of disease complex microenvironment. Moreover, online ava...
Algorithms Databases, Factual Computer Simulation Female Humans Machine Learning Software Biomarkers, Tumor Animals Male Neoplasms Reproducibility of Results Sensitivity and Specificity Tumor Microenvironment Social Behavior Gene Expression Heuristics Oligonucleotide Array Sequence Analysis Predatory Behavior Computational Biology Support Vector Machine Early Detection of Cancer
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Gene shaving using a sensitivity analysis of kernel based machine learning approach, with applications to cancer data.

PloS one May 23, 2019
BACKGROUND: Gene shaving (GS) is an essential and challenging tools for biomedical researchers due to the large number of genes in human genome and the complex nature of biological networks. Most GS methods are not applicable to non-linear and multi-...
False Positive Reactions Oligonucleotide Array Sequence Analysis Genetic Techniques Area Under Curve Colonic Neoplasms Nonlinear Dynamics Computer Simulation Gene Expression Profiling Computational Biology Artificial Intelligence Software Machine Learning Algorithms Humans
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Analysis of differentially expressed genes in rheumatoid arthritis and osteoarthritis by integrated microarray analysis.

Journal of cellular biochemistry Mar 4, 2019
BACKGROUND: Rheumatoid arthritis (RA) and osteoarthritis (OA) were two major types of joint diseases. This study aimed to explore the mechanism underlying OA and RA and analyze their difference by integrated analysis of multiple gene expression data ...
Gene Expression Regulation Chemokines Ubiquitin-Protein Ligases Oxidative Phosphorylation Inhibitor of Apoptosis Proteins Gene Ontology Oligonucleotide Array Sequence Analysis Signal Transduction Synovial Membrane Protein Interaction Maps Osteoarthritis Humans Gene Regulatory Networks Gene Expression Profiling Arthritis, Rheumatoid
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ClinTAD: a tool for copy number variant interpretation in the context of topologically associated domains.

Journal of human genetics Feb 14, 2019
Standard clinical interpretation of DNA copy number variants (CNVs) identified by cytogenomic microarray involves examining protein-coding genes within the region and comparison to other CNVs. Emerging basic research suggests that CNVs can also exert...
Polymorphism, Single Nucleotide Humans Gene Ontology Sequence Analysis, DNA Male Female Oligonucleotide Array Sequence Analysis DNA Copy Number Variations User-Computer Interface
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A novel gene selection algorithm for cancer classification using microarray datasets.

BMC medical genomics Jan 15, 2019
BACKGROUND: Microarray datasets are an important medical diagnostic tool as they represent the states of a cell at the molecular level. Available microarray datasets for classifying cancer types generally have a fairly small sample size compared to t...
Computational Biology Support Vector Machine Neoplasms Gene Expression Profiling Mutation Oligonucleotide Array Sequence Analysis Genes, Neoplasm
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Feature selection and tumor classification for microarray data using relaxed Lasso and generalized multi-class support vector machine.

Journal of theoretical biology Dec 8, 2018
At present, the study of gene expression data provides a reference for tumor diagnosis at the molecular level. It is a challenging task to select the feature genes related to the classification from the high-dimensional and small-sample gene expressi...
Datasets as Topic Oligonucleotide Array Sequence Analysis Humans Gene Expression Profiling Software Support Vector Machine Neoplasms
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Neuroevolution as a tool for microarray gene expression pattern identification in cancer research.

Journal of biomedical informatics Dec 3, 2018
Microarrays are still one of the major techniques employed to study cancer biology. However, the identification of expression patterns from microarray datasets is still a significant challenge to overcome. In this work, a new approach using Neuroevol...
Neural Networks, Computer Machine Learning Algorithms Biomarkers, Tumor Neoplasms Humans Oligonucleotide Array Sequence Analysis
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Incorporating EBO-HSIC with SVM for Gene Selection Associated with Cervical Cancer Classification.

Journal of medical systems Oct 6, 2018
Microarray technology is utilized by the biologists, in order to compute the expression levels of thousands of genes. Cervical cancer classification utilizing gene expression data depends upon conventional supervised learning methods, wherein only la...
Gene Expression Oligonucleotide Array Sequence Analysis Humans Uterine Cervical Neoplasms Algorithms Support Vector Machine Female Fuzzy Logic
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