AI Medical Compendium Topic

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Oligonucleotide Array Sequence Analysis

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Gene expression based survival prediction for cancer patients-A topic modeling approach.

PloS one
Cancer is one of the leading cause of death, worldwide. Many believe that genomic data will enable us to better predict the survival time of these patients, which will lead to better, more personalized treatment options and patient care. As standard ...

Gene shaving using a sensitivity analysis of kernel based machine learning approach, with applications to cancer data.

PloS one
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-...

A novel gene selection algorithm for cancer classification using microarray datasets.

BMC medical genomics
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...

ClinTAD: a tool for copy number variant interpretation in the context of topologically associated domains.

Journal of human genetics
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...

Analysis of differentially expressed genes in rheumatoid arthritis and osteoarthritis by integrated microarray analysis.

Journal of cellular biochemistry
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 ...

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

Computers in biology and medicine
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.

A machine learning approach for the identification of population-informative markers from high-throughput genotyping data: application to several pig breeds.

Animal : an international journal of animal bioscience
Single nucleotide polymorphisms (SNPs) able to describe population differences can be used for important applications in livestock, including breed assignment of individual animals, authentication of mono-breed products and parentage verification amo...

Compendiums of cancer transcriptomes for machine learning applications.

Scientific data
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...