AIMC Topic: Models, Genetic

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Inferring MicroRNA Targets Based on Restricted Boltzmann Machines.

IEEE journal of biomedical and health informatics Mar 9, 2018
Predicting the miRNA-target interactions (MTIs) is a critical task for elucidating mechanistic roles of miRNAs in pathophysiology. However, most existing techniques have a higher false positive because the precise miRNA target mechanisms are poorly k...
Stochastic Processes Humans Neural Networks, Computer Software Computational Biology Models, Genetic MicroRNAs
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Brain-specific functional relationship networks inform autism spectrum disorder gene prediction.

Translational psychiatry Mar 6, 2018
Autism spectrum disorder (ASD) is a neuropsychiatric disorder with strong evidence of genetic contribution, and increased research efforts have resulted in an ever-growing list of ASD candidate genes. However, only a fraction of the hundreds of nomin...
Phenotype Autism Spectrum Disorder Animals Humans Machine Learning Rats Models, Genetic Databases, Genetic Genome Mice Genomics Genetic Predisposition to Disease
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Risk-Predicting Model for Incident of Essential Hypertension Based on Environmental and Genetic Factors with Support Vector Machine.

Interdisciplinary sciences, computational life sciences Jan 29, 2018
Essential hypertension (EH) has become a major chronic disease around the world. To build a risk-predicting model for EH can help to interpose people's lifestyle and dietary habit to decrease the risk of getting EH. In this study, we constructed a EH...
Humans Risk Factors Support Vector Machine Environment Essential Hypertension ROC Curve Genetic Predisposition to Disease Models, Genetic
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Predicting enhancers with deep convolutional neural networks.

BMC bioinformatics Dec 1, 2017
BACKGROUND: With the rapid development of deep sequencing techniques in the recent years, enhancers have been systematically identified in such projects as FANTOM and ENCODE, forming genome-wide landscapes in a series of human cell lines. Nevertheles...
Algorithms Databases, Factual Genomics Humans Neural Networks, Computer Machine Learning Genome, Human Enhancer Elements, Genetic Computational Biology Models, Genetic DNA
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Computational Intelligence for Medical Imaging Simulations.

Journal of medical systems Nov 25, 2017
This paper describes how to simulate medical imaging by computational intelligence to explore areas that cannot be easily achieved by traditional ways, including genes and proteins simulations related to cancer development and immunity. This paper ha...
Models, Biological Models, Immunological Models, Genetic Artificial Intelligence Proteins Humans Algorithms Diagnostic Imaging Computer Simulation
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From word models to executable models of signaling networks using automated assembly.

Molecular systems biology Nov 24, 2017
Word models (natural language descriptions of molecular mechanisms) are a common currency in spoken and written communication in biomedicine but are of limited use in predicting the behavior of complex biological networks. We present an approach to b...
Vemurafenib Neural Networks, Computer Computer Simulation Language Melanoma Skin Neoplasms Antineoplastic Agents Humans Sulfonamides Indoles Proto-Oncogene Proteins p21(ras) Signal Transduction Enzyme Inhibitors Cell Line, Tumor Drug Resistance, Neoplasm Natural Language Processing Tumor Suppressor Protein p53 Gene Expression Regulation, Neoplastic Proto-Oncogene Proteins B-raf DNA Damage Models, Genetic
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A deep auto-encoder model for gene expression prediction.

BMC genomics Nov 17, 2017
BACKGROUND: Gene expression is a key intermediate level that genotypes lead to a particular trait. Gene expression is affected by various factors including genotypes of genetic variants. With an aim of delineating the genetic impact on gene expressio...
Gene Expression Profiling Polymorphism, Single Nucleotide Models, Genetic Neural Networks, Computer Yeasts Fungal Proteins
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Cell cycle time series gene expression data encoded as cyclic attractors in Hopfield systems.

PLoS computational biology Nov 17, 2017
Modern time series gene expression and other omics data sets have enabled unprecedented resolution of the dynamics of cellular processes such as cell cycle and response to pharmaceutical compounds. In anticipation of the proliferation of time series ...
Computational Biology Models, Genetic HeLa Cells Saccharomyces cerevisiae Cell Cycle Gene Silencing Algorithms Gene Expression Profiling Transcriptome Humans Neural Networks, Computer
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Unified Deep Learning Architecture for Modeling Biology Sequence.

IEEE/ACM transactions on computational biology and bioinformatics Oct 9, 2017
Prediction of the spatial structure or function of biological macromolecules based on their sequences remains an important challenge in bioinformatics. When modeling biological sequences using traditional sequencing models, long-range interaction, co...
Models, Statistical Deep Learning Sequence Analysis Computational Biology Models, Genetic
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Multiobjective differential evolution-based multifactor dimensionality reduction for detecting gene-gene interactions.

Scientific reports Oct 9, 2017
Epistasis within disease-related genes (gene-gene interactions) was determined through contingency table measures based on multifactor dimensionality reduction (MDR) using single-nucleotide polymorphisms (SNPs). Most MDR-based methods use the single ...
Models, Genetic Humans Coronary Artery Disease Computer Simulation Genetic Loci Polymorphism, Single Nucleotide Gene Frequency Epistasis, Genetic Multifactor Dimensionality Reduction
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