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Gene Expression

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Applying Cost-Sensitive Extreme Learning Machine and Dissimilarity Integration to Gene Expression Data Classification.

Computational intelligence and neuroscience
Embedding cost-sensitive factors into the classifiers increases the classification stability and reduces the classification costs for classifying high-scale, redundant, and imbalanced datasets, such as the gene expression data. In this study, we exte...

Support vector machine model of developmental brain gene expression data for prioritization of Autism risk gene candidates.

Bioinformatics (Oxford, England)
MOTIVATION: Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders with clinical heterogeneity and a substantial polygenic component. High-throughput methods for ASD risk gene identification produce numerous candidate genes that ...

Logic Learning Machine and standard supervised methods for Hodgkin's lymphoma prognosis using gene expression data and clinical variables.

Health informatics journal
This study evaluates the performance of a set of machine learning techniques in predicting the prognosis of Hodgkin's lymphoma using clinical factors and gene expression data. Analysed samples from 130 Hodgkin's lymphoma patients included a small set...

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 ...

Expression of rabies virus glycoprotein in the methylotrophic yeast Pichia pastoris.

Biotechnology and applied biochemistry
Rabies is a fatal disease that can be prevented by vaccination. Different approaches were investigated to develop novel human rabies vaccines with improved features compared to the current available vaccines, among them is the use of heterologous gen...

REGene: a literature-based knowledgebase of animal regeneration that bridge tissue regeneration and cancer.

Scientific reports
Regeneration is a common phenomenon across multiple animal phyla. Regeneration-related genes (REGs) are critical for fundamental cellular processes such as proliferation and differentiation. Identification of REGs and elucidating their functions may ...

Improving Protein Expression Prediction Using Extra Features and Ensemble Averaging.

PloS one
The article focus is the improvement of machine learning models capable of predicting protein expression levels based on their codon encoding. Support vector regression (SVR) and partial least squares (PLS) were used to create the models. SVR yields ...

Construction and characterization of recombinant adenovirus carrying a mouse TIGIT-GFP gene.

Genetics and molecular research : GMR
Recombinant adenovirus vector systems have been used extensively in protein research and gene therapy. However, the construction and characterization of recombinant adenovirus is a tedious and time-consuming process. TIGIT is a recently discovered im...

canSAR: an updated cancer research and drug discovery knowledgebase.

Nucleic acids research
canSAR (http://cansar.icr.ac.uk) is a publicly available, multidisciplinary, cancer-focused knowledgebase developed to support cancer translational research and drug discovery. canSAR integrates genomic, protein, pharmacological, drug and chemical da...