AIMC Topic: Gene Expression Profiling

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Tuning parameter estimation in SCAD-support vector machine using firefly algorithm with application in gene selection and cancer classification.

Computers in biology and medicine
In cancer classification, gene selection is one of the most important bioinformatics related topics. The selection of genes can be considered to be a variable selection problem, which aims to find a small subset of genes that has the most discriminat...

A neural network based model effectively predicts enhancers from clinical ATAC-seq samples.

Scientific reports
Enhancers are cis-acting sequences that regulate transcription rates of their target genes in a cell-specific manner and harbor disease-associated sequence variants in cognate cell types. Many complex diseases are associated with enhancer malfunction...

Deep learning-based transcriptome data classification for drug-target interaction prediction.

BMC genomics
BACKGROUND: The ability to predict the interaction of drugs with target proteins is essential to research and development of drug. However, the traditional experimental paradigm is costly, and previous in silico prediction paradigms have been impeded...

G2Vec: Distributed gene representations for identification of cancer prognostic genes.

Scientific reports
Identification of cancer prognostic genes is important in that it can lead to accurate outcome prediction and better therapeutic trials for cancer patients. Many computational approaches have been proposed to achieve this goal; however, there is room...

Universal method for robust detection of circadian state from gene expression.

Proceedings of the National Academy of Sciences of the United States of America
Circadian clocks play a key role in regulating a vast array of biological processes, with significant implications for human health. Accurate assessment of physiological time using transcriptional biomarkers found in human blood can significantly imp...

Novel symmetry-based gene-gene dissimilarity measures utilizing Gene Ontology: Application in gene clustering.

Gene
In recent years DNA microarray technology, leading to the generation of high-volume biological data, has gained significant attention. To analyze this high volume gene-expression data, one such powerful tool is Clustering. For any clustering algorith...

An Efficient Feature Selection Strategy Based on Multiple Support Vector Machine Technology with Gene Expression Data.

BioMed research international
The application of gene expression data to the diagnosis and classification of cancer has become a hot issue in the field of cancer classification. Gene expression data usually contains a large number of tumor-free data and has the characteristics of...

Identification of novel immune-relevant drug target genes for Alzheimer's Disease by combining ontology inference with network analysis.

CNS neuroscience & therapeutics
AIMS: Alzheimer's disease (AD) is one of the leading causes of death in elderly people. Its pathogenesis is greatly associated with the abnormality of immune system. However, only a few immune-relevant AD drug target genes have been discovered up to ...

Gene Ontology Enrichment Improves Performances of Functional Similarity of Genes.

Scientific reports
There exists a plethora of measures to evaluate functional similarity (FS) between genes, which is a widely used in many bioinformatics applications including detecting molecular pathways, identifying co-expressed genes, predicting protein-protein in...

Integration of Gene Expression Profile Data to Screen and Verify Hub Genes Involved in Osteoarthritis.

BioMed research international
Osteoarthritis (OA) is one of the most common diseases worldwide, but the pathogenic genes and pathways are largely unclear. The aim of this study was to screen and verify hub genes involved in OA and explore potential molecular mechanisms. The expre...