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Models, Genetic

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Deep learning for population size history inference: Design, comparison and combination with approximate Bayesian computation.

Molecular ecology resources
For the past decades, simulation-based likelihood-free inference methods have enabled researchers to address numerous population genetics problems. As the richness and amount of simulated and real genetic data keep increasing, the field has a strong ...

An enhanced machine learning tool for cis-eQTL mapping with regularization and confounder adjustments.

Genetic epidemiology
Many expression quantitative trait loci (eQTL) studies have been conducted to investigate the biological effects of variants in gene regulation. However, these eQTL studies may suffer from low or moderate statistical power and overly conservative fal...

LogicNet: probabilistic continuous logics in reconstructing gene regulatory networks.

BMC bioinformatics
BACKGROUND: Gene Regulatory Networks (GRNs) have been previously studied by using Boolean/multi-state logics. While the gene expression values are usually scaled into the range [0, 1], these GRN inference methods apply a threshold to discretize the d...

Cross-species regulatory sequence activity prediction.

PLoS computational biology
Machine learning algorithms trained to predict the regulatory activity of nucleic acid sequences have revealed principles of gene regulation and guided genetic variation analysis. While the human genome has been extensively annotated and studied, mod...

Association study based on topological constraints of protein-protein interaction networks.

Scientific reports
The non-random interaction pattern of a protein-protein interaction network (PIN) is biologically informative, but its potentials have not been fully utilized in omics studies. Here, we propose a network-permutation-based association study (NetPAS) m...

KAML: improving genomic prediction accuracy of complex traits using machine learning determined parameters.

Genome biology
Advances in high-throughput sequencing technologies have reduced the cost of genotyping dramatically and led to genomic prediction being widely used in animal and plant breeding, and increasingly in human genetics. Inspired by the efficient computing...

Prediction of miRNA targets by learning from interaction sequences.

PloS one
MicroRNAs (miRNAs) are involved in a diverse variety of biological processes through regulating the expression of target genes in the post-transcriptional level. So, it is of great importance to discover the targets of miRNAs in biological research. ...

Photosynthetic protein classification using genome neighborhood-based machine learning feature.

Scientific reports
Identification of novel photosynthetic proteins is important for understanding and improving photosynthetic efficiency. Synergistically, genome neighborhood can provide additional useful information to identify photosynthetic proteins. We, therefore,...

Automatically Designing CNN Architectures Using the Genetic Algorithm for Image Classification.

IEEE transactions on cybernetics
Convolutional neural networks (CNNs) have gained remarkable success on many image classification tasks in recent years. However, the performance of CNNs highly relies upon their architectures. For the most state-of-the-art CNNs, their architectures a...

gammaBOriS: Identification and Taxonomic Classification of Origins of Replication in Gammaproteobacteria using Motif-based Machine Learning.

Scientific reports
The biology of bacterial cells is, in general, based on information encoded on circular chromosomes. Regulation of chromosome replication is an essential process that mostly takes place at the origin of replication (oriC), a locus unique per chromoso...