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Gene Expression Regulation, Neoplastic

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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...

Network stratification analysis for identifying function-specific network layers.

Molecular bioSystems
A major challenge of systems biology is to capture the rewiring of biological functions (e.g. signaling pathways) in a molecular network. To address this problem, we proposed a novel computational framework, namely network stratification analysis (Ne...

Drug repositioning for non-small cell lung cancer by using machine learning algorithms and topological graph theory.

BMC bioinformatics
BACKGROUND: Non-small cell lung cancer (NSCLC) is one of the leading causes of death globally, and research into NSCLC has been accumulating steadily over several years. Drug repositioning is the current trend in the pharmaceutical industry for ident...

Serum Dickkopf-1 levels as a clinical and prognostic factor in patients with bladder cancer.

Genetics and molecular research : GMR
Dickkopf-1 (DKK-1) is a secreted protein that inhibits Wnt signaling. However, the clinical significance and prognostic value of serum DKK-1 levels have not been previously investigated in bladder cancer in Chinese patients. Blood samples were taken ...

Cancer classification based on gene expression using neural networks.

Genetics and molecular research : GMR
Based on gene expression, we have classified 53 colon cancer patients with UICC II into two groups: relapse and no relapse. Samples were taken from each patient, and gene information was extracted. Of the 53 samples examined, 500 genes were considere...

Predicting target proteins for drug candidate compounds based on drug-induced gene expression data in a chemical structure-independent manner.

BMC medical genomics
BACKGROUND: Phenotype-based high-throughput screening is a useful technique for identifying drug candidate compounds that have a desired phenotype. However, the molecular mechanisms of the hit compounds remain unknown, and substantial effort is requi...

The feature selection bias problem in relation to high-dimensional gene data.

Artificial intelligence in medicine
OBJECTIVE: Feature selection is a technique widely used in data mining. The aim is to select the best subset of features relevant to the problem being considered. In this paper, we consider feature selection for the classification of gene datasets. G...

Multi-class BCGA-ELM based classifier that identifies biomarkers associated with hallmarks of cancer.

BMC bioinformatics
BACKGROUND: Traditional cancer treatments have centered on cytotoxic drugs and general purpose chemotherapy that may not be tailored to treat specific cancers. Identification of molecular markers that are related to different types of cancers might l...