AIMC Topic: Gene Expression Profiling

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NeuroRDF: semantic integration of highly curated data to prioritize biomarker candidates in Alzheimer's disease.

Journal of biomedical semantics
BACKGROUND: Neurodegenerative diseases are incurable and debilitating indications with huge social and economic impact, where much is still to be learnt about the underlying molecular events. Mechanistic disease models could offer a knowledge framewo...

Integrated gene set analysis for microRNA studies.

Bioinformatics (Oxford, England)
MOTIVATION: Functional interpretation of miRNA expression data is currently done in a three step procedure: select differentially expressed miRNAs, find their target genes, and carry out gene set overrepresentation analysis Nevertheless, major limita...

Ensemble Feature Learning of Genomic Data Using Support Vector Machine.

PloS one
The identification of a subset of genes having the ability to capture the necessary information to distinguish classes of patients is crucial in bioinformatics applications. Ensemble and bagging methods have been shown to work effectively in the proc...

A knowledge-based approach for predicting gene-disease associations.

Bioinformatics (Oxford, England)
MOTIVATION: Recent advances of next-generation sequence technologies have made it possible to rapidly and inexpensively identify gene variations. Knowing the disease association of these gene variations is important for early intervention to treat de...

A kernel-based clustering method for gene selection with gene expression data.

Journal of biomedical informatics
Gene selection is important for cancer classification based on gene expression data, because of high dimensionality and small sample size. In this paper, we present a new gene selection method based on clustering, in which dissimilarity measures are ...

Integrated Analysis of Expression Profile Based on Differentially Expressed Genes in Middle Cerebral Artery Occlusion Animal Models.

International journal of molecular sciences
Stroke is one of the most common causes of death, only second to heart disease. Molecular investigations about stroke are in acute shortage nowadays. This study is intended to explore a gene expression profile after brain ischemia reperfusion. Meta-a...

Clustering Single-Cell Expression Data Using Random Forest Graphs.

IEEE journal of biomedical and health informatics
Complex tissues such as brain and bone marrow are made up of multiple cell types. As the study of biological tissue structure progresses, the role of cell-type-specific research becomes increasingly important. Novel sequencing technology such as sing...

Enrichr: a comprehensive gene set enrichment analysis web server 2016 update.

Nucleic acids research
Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gen...

g:Profiler-a web server for functional interpretation of gene lists (2016 update).

Nucleic acids research
Functional enrichment analysis is a key step in interpreting gene lists discovered in diverse high-throughput experiments. g:Profiler studies flat and ranked gene lists and finds statistically significant Gene Ontology terms, pathways and other gene ...

Exploring information from the topology beneath the Gene Ontology terms to improve semantic similarity measures.

Gene
Measuring the similarity between pairs of biological entities is important in molecular biology. The introduction of Gene Ontology (GO) provides us with a promising approach to quantifying the semantic similarity between two genes or gene products. T...