AIMC Topic: Models, Genetic

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LncRNA ontology: inferring lncRNA functions based on chromatin states and expression patterns.

Oncotarget Nov 24, 2015
Accumulating evidences suggest that long non-coding RNAs (lncRNAs) perform important functions. Genome-wide chromatin-states area rich source of information about cellular state, yielding insights beyond what is typically obtained by transcriptome pr...
Humans Algorithms Gene Expression Profiling Cell Line, Tumor Cells, Cultured Neoplasms Lysine K562 Cells Methylation Promoter Regions, Genetic Chromatin Transcription Initiation Site Histones Gene Ontology Hep G2 Cells Cell Line RNA, Long Noncoding HeLa Cells RNA, Messenger Models, Genetic Gene Regulatory Networks
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[Detecting gene-gene/environment interactions by model-based multifactor dimensionality reduction].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi Nov 1, 2015
This paper introduces a method called model-based multifactor dimensionality reduction (MB-MDR), which was firstly proposed by Calle et al., and can be applied for detecting gene-gene or gene-environment interactions in genetic studies. The basic pri...
Gene-Environment Interaction Phenotype Genotype Models, Genetic Multifactor Dimensionality Reduction
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Classification of imbalanced bioinformatics data by using boundary movement-based ELM.

Bio-medical materials and engineering Jan 1, 2015
To address the imbalanced classification problem emerging in Bioinformatics, a boundary movement-based extreme learning machine (ELM) algorithm called BM-ELM was proposed. BM-ELM tries to firstly explore the prior information about data distribution ...
High-Throughput Nucleotide Sequencing Pattern Recognition, Automated Data Mining Sequence Alignment Sequence Analysis Models, Genetic Support Vector Machine Databases, Genetic Models, Statistical Algorithms Computer Simulation Machine Learning
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Epistasis analysis using artificial intelligence.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2015
Here we introduce artificial intelligence (AI) methodology for detecting and characterizing epistasis in genetic association studies. The ultimate goal of our AI strategy is to analyze genome-wide genetics data as a human would using sources of exper...
Models, Genetic Prostatic Neoplasms Mutation Alzheimer Disease Software Male Artificial Intelligence Epistasis, Genetic Humans Glaucoma
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Identification of hepatocellular carcinoma-related genes with a machine learning and network analysis.

Journal of computational biology : a journal of computational molecular cell biology Jan 1, 2015
Liver cancer is one of the leading causes of cancer mortality worldwide. Hepatocellular carcinoma (HCC) is the main type of liver cancer. We applied a machine learning approach with maximum-relevance-minimum-redundancy (mRMR) algorithm followed by in...
Gene Ontology Genes, Neoplasm Databases, Genetic Liver Neoplasms Carcinoma, Hepatocellular Gene Regulatory Networks Models, Genetic Humans Artificial Intelligence
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