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Models, Genetic

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Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk.

Nature genetics Jul 16, 2018
Key challenges for human genetics, precision medicine and evolutionary biology include deciphering the regulatory code of gene expression and understanding the transcriptional effects of genome variation. However, this is extremely difficult because ...
Algorithms Computer Simulation Deep Learning Genome-Wide Association Study Humans Gene Expression Mutation Genetic Predisposition to Disease Promoter Regions, Genetic Polymorphism, Single Nucleotide Quantitative Trait Loci Models, Genetic
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Deep learning models for bacteria taxonomic classification of metagenomic data.

BMC bioinformatics Jul 9, 2018
BACKGROUND: An open challenge in translational bioinformatics is the analysis of sequenced metagenomes from various environmental samples. Of course, several studies demonstrated the 16S ribosomal RNA could be considered as a barcode for bacteria cla...
Metagenomics Reproducibility of Results Metagenome Deep Learning Time Factors RNA, Ribosomal, 16S Databases, Genetic Bacteria Models, Genetic Neural Networks, Computer Algorithms
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Machine learning identifies a core gene set predictive of acquired resistance to EGFR tyrosine kinase inhibitor.

Journal of cancer research and clinical oncology May 25, 2018
PURPOSE: Acquired resistance (AR) to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) is a major issue worldwide, for both patients and healthcare providers. However, precise prediction is currently infeasible due to the lack o...
Algorithms Reproducibility of Results Neoplasms Transcriptome Humans Machine Learning ErbB Receptors Protein Kinase Inhibitors Cell Line, Tumor Models, Genetic Drug Resistance, Neoplasm
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Control of Gene Regulatory Networks Using Bayesian Inverse Reinforcement Learning.

IEEE/ACM transactions on computational biology and bioinformatics Apr 26, 2018
Control of gene regulatory networks (GRNs) to shift gene expression from undesirable states to desirable ones has received much attention in recent years. Most of the existing methods assume that the cost of intervention at each state and time point,...
Humans Algorithms Melanoma Machine Learning Software Models, Biological Tumor Suppressor Protein p53 Proto-Oncogene Proteins c-mdm2 Wnt-5a Protein Computational Biology Gene Expression Regulation, Neoplastic Models, Genetic Bayes Theorem Skin Neoplasms Gene Expression Profiling Gene Regulatory Networks
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Supervised machine learning reveals introgressed loci in the genomes of Drosophila simulans and D. sechellia.

PLoS genetics Apr 23, 2018
Hybridization and gene flow between species appears to be common. Even though it is clear that hybridization is widespread across all surveyed taxonomic groups, the magnitude and consequences of introgression are still largely unknown. Thus it is cru...
Drosophila Hybridization, Genetic Genetics, Population Genetic Variation Drosophila simulans Haplotypes Gene Flow Models, Genetic Species Specificity Genome, Insect Evolution, Molecular Genetic Speciation Supervised Machine Learning Computer Simulation Software Animals
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A hierarchical clustering method for dimension reduction in joint analysis of multiple phenotypes.

Genetic epidemiology Apr 22, 2018
Genome-wide association studies (GWAS) have become a very effective research tool to identify genetic variants of underlying various complex diseases. In spite of the success of GWAS in identifying thousands of reproducible associations between genet...
Pulmonary Disease, Chronic Obstructive Genome-Wide Association Study Models, Genetic Cluster Analysis Humans Phenotype Computer Simulation Multifactor Dimensionality Reduction
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Statistics versus machine learning.

Nature methods Apr 3, 2018
Data Interpretation, Statistical Gene Expression Regulation Machine Learning Models, Genetic
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PCLPred: A Bioinformatics Method for Predicting Protein-Protein Interactions by Combining Relevance Vector Machine Model with Low-Rank Matrix Approximation.

International journal of molecular sciences Mar 29, 2018
Protein-protein interactions (PPI) are key to protein functions and regulations within the cell cycle, DNA replication, and cellular signaling. Therefore, detecting whether a pair of proteins interact is of great importance for the study of molecular...
Databases, Protein Software Saccharomyces cerevisiae Models, Genetic Saccharomyces cerevisiae Proteins Support Vector Machine
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Sequential regulatory activity prediction across chromosomes with convolutional neural networks.

Genome research Mar 27, 2018
Models for predicting phenotypic outcomes from genotypes have important applications to understanding genomic function and improving human health. Here, we develop a machine-learning system to predict cell-type-specific epigenetic and transcriptional...
Gene Expression Regulation Promoter Regions, Genetic Chromosomes Regulatory Sequences, Nucleic Acid Computational Biology Genomics Animals Humans Epigenomics Polymorphism, Single Nucleotide Gene Expression Profiling Neural Networks, Computer Models, Genetic Machine Learning
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A hidden Markov tree model for testing multiple hypotheses corresponding to Gene Ontology gene sets.

BMC bioinformatics Mar 27, 2018
BACKGROUND: Testing predefined gene categories has become a common practice for scientists analyzing high throughput transcriptome data. A systematic way of testing gene categories leads to testing hundreds of null hypotheses that correspond to nodes...
Quantitative Trait Loci Bayes Theorem Markov Chains Gene Ontology Transcriptome ROC Curve Humans Models, Genetic Algorithms Models, Theoretical Computer Simulation
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