AIMC Topic: Oligonucleotide Array Sequence Analysis

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Finding disagreement pathway signatures and constructing an ensemble model for cancer classification.

Scientific reports Aug 30, 2017
Cancer classification based on molecular level is a relatively routine research procedure with advances in high-throughput molecular profiling techniques. However, the number of genes typically far exceeds the number of the sample size in gene expres...
Taxoids Atlases as Topic Anthracyclines Neoplasm Proteins Datasets as Topic Oligonucleotide Array Sequence Analysis Humans Neoplasms Antineoplastic Agents Gene Expression Regulation, Neoplastic Gene Expression Profiling Signal Transduction Gene Regulatory Networks Support Vector Machine
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A comparison of machine learning and Bayesian modelling for molecular serotyping.

BMC genomics Aug 11, 2017
BACKGROUND: Streptococcus pneumoniae is a human pathogen that is a major cause of infant mortality. Identifying the pneumococcal serotype is an important step in monitoring the impact of vaccines used to protect against disease. Genomic microarrays p...
Serotyping Streptococcus pneumoniae Machine Learning Oligonucleotide Array Sequence Analysis Models, Statistical Bayes Theorem
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Development of a two-stage gene selection method that incorporates a novel hybrid approach using the cuckoo optimization algorithm and harmony search for cancer classification.

Journal of biomedical informatics Feb 3, 2017
For each cancer type, only a few genes are informative. Due to the so-called 'curse of dimensionality' problem, the gene selection task remains a challenge. To overcome this problem, we propose a two-stage gene selection method called MRMR-COA-HS. In...
Algorithms Neoplasms Gene Expression Profiling Humans Support Vector Machine Oligonucleotide Array Sequence Analysis Genetic Techniques
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Gene selection for microarray cancer classification using a new evolutionary method employing artificial intelligence concepts.

Genomics Feb 1, 2017
Gene selection is a demanding task for microarray data analysis. The diverse complexity of different cancers makes this issue still challenging. In this study, a novel evolutionary method based on genetic algorithms and artificial intelligence is pro...
Humans Artificial Intelligence Female Genes, Neoplasm Male Neoplasms Oligonucleotide Array Sequence Analysis
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Automated Detection of Cancer Associated Genes Using a Combined Fuzzy-Rough-Set-Based F-Information and Water Swirl Algorithm of Human Gene Expression Data.

PloS one Dec 9, 2016
This study describes a novel approach to reducing the challenges of highly nonlinear multiclass gene expression values for cancer diagnosis. To build a fruitful system for cancer diagnosis, in this study, we introduced two levels of gene selection su...
ROC Curve Oligonucleotide Array Sequence Analysis Genetic Predisposition to Disease Reproducibility of Results Humans Fuzzy Logic Gene Expression Regulation, Neoplastic Neoplasms Genetic Testing Algorithms Gene Expression Profiling Monte Carlo Method
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Introducing a Stable Bootstrap Validation Framework for Reliable Genomic Signature Extraction.

IEEE/ACM transactions on computational biology and bioinformatics Nov 29, 2016
The application of machine learning methods for the identification of candidate genes responsible for phenotypes of interest, such as cancer, is a major challenge in the field of bioinformatics. These lists of genes are often called genomic signature...
Oligonucleotide Array Sequence Analysis Genome Reproducibility of Results Gene Expression Profiling Genomics Support Vector Machine Databases, Genetic Cluster Analysis Humans Machine Learning
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Protein-protein interaction network construction for cancer using a new L1/2-penalized Net-SVM model.

Genetics and molecular research : GMR Jul 25, 2016
Identifying biomarker genes and characterizing interaction pathways with high-dimensional and low-sample size microarray data is a major challenge in computational biology. In this field, the construction of protein-protein interaction (PPI) networks...
Protein Interaction Domains and Motifs Models, Biological Oligonucleotide Array Sequence Analysis Gene Expression Profiling Protein Interaction Maps Gene Regulatory Networks Computational Biology Support Vector Machine Genetic Markers Humans Algorithms Neoplasms
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Integrated Analysis of Expression Profile Based on Differentially Expressed Genes in Middle Cerebral Artery Occlusion Animal Models.

International journal of molecular sciences May 20, 2016
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...
Gene Ontology Oligonucleotide Array Sequence Analysis Disease Models, Animal Infarction, Middle Cerebral Artery Gene Expression Regulation Mice Humans Rats Animals Gene Expression Profiling
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A hybrid gene selection approach for microarray data classification using cellular learning automata and ant colony optimization.

Genomics May 3, 2016
This paper proposes an approach for gene selection in microarray data. The proposed approach consists of a primary filter approach using Fisher criterion which reduces the initial genes and hence the search space and time complexity. Then, a wrapper ...
Humans Machine Learning Algorithms Cluster Analysis Support Vector Machine Data Interpretation, Statistical Oligonucleotide Array Sequence Analysis
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Missing value imputation for microRNA expression data by using a GO-based similarity measure.

BMC bioinformatics Jan 11, 2016
BACKGROUND: Missing values are commonly present in microarray data profiles. Instead of discarding genes or samples with incomplete expression level, missing values need to be properly imputed for accurate data analysis. The imputation methods can be...
Gene Expression Profiling Computational Biology MicroRNAs Humans Algorithms Models, Statistical Gene Ontology Oligonucleotide Array Sequence Analysis
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