AIMC Topic: Gene Expression

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Improved pan-specific prediction of MHC class I peptide binding using a novel receptor clustering data partitioning strategy.

HLA Oct 20, 2016
Pan-specific prediction of receptor-ligand interaction is conventionally done using machine-learning methods that integrates information about both receptor and ligand primary sequences. To achieve optimal performance using machine learning, dealing ...
Epitopes Alleles Histocompatibility Antigens Class I Ligands Protein Binding Mice Gene Expression Structural Homology, Protein Macaca Gorilla gorilla Pan troglodytes Software Humans Oligopeptides Animals Machine Learning Binding Sites Protein Interaction Domains and Motifs
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Brief isoflurane anaesthesia affects differential gene expression, gene ontology and gene networks in rat brain.

Behavioural brain research Sep 19, 2016
Much is still unknown about the mechanisms of effects of even brief anaesthesia on the brain and previous studies have simply compared differential expression profiles with and without anaesthesia. We hypothesised that network analysis, in addition t...
Brain Animals Male Microarray Analysis Gene Ontology Anesthetics, Inhalation Cluster Analysis Gene Expression Isoflurane Gene Regulatory Networks Rats Rats, Sprague-Dawley
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Applying Cost-Sensitive Extreme Learning Machine and Dissimilarity Integration to Gene Expression Data Classification.

Computational intelligence and neuroscience Aug 23, 2016
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...
Humans Artificial Intelligence Machine Learning Databases, Genetic Gene Expression Algorithms Animals
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Support vector machine model of developmental brain gene expression data for prioritization of Autism risk gene candidates.

Bioinformatics (Oxford, England) Aug 9, 2016
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 ...
Humans Algorithms Autism Spectrum Disorder Gene Expression Brain Risk Factors Support Vector Machine
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Logic Learning Machine and standard supervised methods for Hodgkin's lymphoma prognosis using gene expression data and clinical variables.

Health informatics journal Jun 27, 2016
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...
Hodgkin Disease Cluster Analysis Decision Trees Gene Expression Machine Learning Prognosis Humans
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A kernel-based clustering method for gene selection with gene expression data.

Journal of biomedical informatics May 20, 2016
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 ...
Gene Expression Profiling Support Vector Machine Cluster Analysis Gene Expression Humans Algorithms
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Expression of rabies virus glycoprotein in the methylotrophic yeast Pichia pastoris.

Biotechnology and applied biochemistry Apr 14, 2016
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...
Viral Proteins Humans Recombinant Proteins Membrane Glycoproteins Gene Expression Pichia Rabies virus
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REGene: a literature-based knowledgebase of animal regeneration that bridge tissue regeneration and cancer.

Scientific reports Mar 15, 2016
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 ...
Regeneration Humans Databases, Genetic Transcriptome Gene Expression Epigenesis, Genetic Knowledge Bases Animals Neoplasms
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Improving Protein Expression Prediction Using Extra Features and Ensemble Averaging.

PloS one Mar 2, 2016
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 ...
Base Sequence Codon Escherichia coli Proteomics Least-Squares Analysis Gene Expression Models, Genetic Escherichia coli Proteins Support Vector Machine
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Downregulation of serum DKK-1 predicts poor prognosis in patients with papillary thyroid cancer.

Genetics and molecular research : GMR Dec 29, 2015
The Wnt inhibitor dickkopf-1 (DKK-1) has been shown to be closely correlated with tumor initiation and progression in various types of cancers. However, the serum level of DKK-1 in patients with papillary thyroid cancer (PTC) and its potential clinic...
Down-Regulation Carcinoma, Papillary Thyroid Cancer, Papillary Case-Control Studies Survival Analysis Adolescent Tumor Burden Humans Thyroid Gland Intercellular Signaling Peptides and Proteins Prognosis Biomarkers, Tumor Aged Male Adult Gene Expression Middle Aged Female Neoplasm Staging Risk Factors Carcinoma Thyroid Neoplasms Neoplasm Recurrence, Local Enzyme-Linked Immunosorbent Assay Lymphatic Metastasis
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