AIMC Topic: Models, Genetic

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Localizing and Classifying Adaptive Targets with Trend Filtered Regression.

Molecular biology and evolution Feb 1, 2019
Identifying genomic locations of natural selection from sequence data is an ongoing challenge in population genetics. Current methods utilizing information combined from several summary statistics typically assume no correlation of summary statistics...
Humans Machine Learning Software Genome, Human Genetic Techniques Genetics, Population Models, Genetic Regression Analysis Computer Simulation
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Quantitative Modelling of the Waddington Epigenetic Landscape.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2019
C.H. Waddington introduced the epigenetic landscape as a metaphor to represent cellular decision-making during development. Like a population of balls rolling down a rough hillside, developing cells follow specific trajectories (valleys) and eventual...
Cell Lineage Stem Cells Cell Differentiation Neural Networks, Computer Phenotype Epigenomics Models, Genetic Gene Regulatory Networks Humans
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Res2s2aM: Deep residual network-based model for identifying functional noncoding SNPs in trait-associated regions.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2019
Noncoding single nucleotide polymorphisms (SNPs) and their target genes are important components of the heritability of diseases and other polygenic traits. Identifying these SNPs and target genes could potentially reveal new molecular mechanisms and...
Molecular Sequence Annotation Databases, Nucleic Acid Models, Genetic Sequence Analysis, DNA Algorithms Deep Learning Polymorphism, Single Nucleotide Computational Biology Genome-Wide Association Study Humans Neural Networks, Computer
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Unsupervised GRN Ensemble.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2019
Inferring gene regulatory networks from expression data is a very challenging problem that has raised the interest of the scientific community. Different algorithms have been proposed to try to solve this issue, but it has been shown that different m...
Gene Regulatory Networks Unsupervised Machine Learning Datasets as Topic Systems Biology Models, Genetic
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Tree-Based Learning of Regulatory Network Topologies and Dynamics with Jump3.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2019
Inference of gene regulatory networks (GRNs) from time series data is a well-established field in computational systems biology. Most approaches can be broadly divided in two families: model-based and model-free methods. These two families are highly...
Machine Learning Statistics, Nonparametric Systems Biology Models, Genetic Software Decision Trees Gene Regulatory Networks
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Unsupervised Gene Network Inference with Decision Trees and Random Forests.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2019
In this chapter, we introduce the reader to a popular family of machine learning algorithms, called decision trees. We then review several approaches based on decision trees that have been developed for the inference of gene regulatory networks (GRNs...
Unsupervised Machine Learning Gene Expression Regulation Gene Regulatory Networks Models, Genetic Decision Trees Computational Biology
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Towards an accurate and efficient heuristic for species/gene tree co-estimation.

Bioinformatics (Oxford, England) Sep 1, 2018
MOTIVATION: Species and gene trees represent how species and individual loci within their genomes evolve from their most recent common ancestors. These trees are central to addressing several questions in biology relating to, among other issues, spec...
Models, Genetic Bayes Theorem Computer Simulation Machine Learning Genomics
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Applications of Machine Learning Methods to Genomic Selection in Breeding Wheat for Rust Resistance.

The plant genome Jul 1, 2018
New methods and algorithms are being developed for predicting untested phenotypes in schemes commonly used in genomic selection (GS). The prediction of disease resistance in GS has its own peculiarities: a) there is consensus about the additive natur...
Genome, Plant Triticum Genomics Plant Breeding Plant Diseases Basidiomycota Neural Networks, Computer Models, Genetic Linear Models Disease Resistance Machine Learning Support Vector Machine
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COSSMO: predicting competitive alternative splice site selection using deep learning.

Bioinformatics (Oxford, England) Jul 1, 2018
MOTIVATION: Alternative splice site selection is inherently competitive and the probability of a given splice site to be used also depends on the strength of neighboring sites. Here, we present a new model named the competitive splice site model (COS...
Humans Alternative Splicing Software Models, Genetic Computational Biology Deep Learning Probability Sequence Analysis, RNA RNA Splice Sites
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Multiobjective multifactor dimensionality reduction to detect SNP-SNP interactions.

Bioinformatics (Oxford, England) Jul 1, 2018
MOTIVATION: Single-nucleotide polymorphism (SNP)-SNP interactions (SSIs) are popular markers for understanding disease susceptibility. Multifactor dimensionality reduction (MDR) can successfully detect considerable SSIs. Currently, MDR-based methods ...
Models, Genetic Coronary Artery Disease Multifactor Dimensionality Reduction Epistasis, Genetic Case-Control Studies Genetic Predisposition to Disease Polymorphism, Single Nucleotide Humans
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