AIMC Topic: Recombination, Genetic

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The Prediction of Recombination Hotspot Based on Automated Machine Learning.

Journal of molecular biology Jun 12, 2024
Meiotic recombination plays a pivotal role in genetic evolution. Genetic variation induced by recombination is a crucial factor in generating biodiversity and a driving force for evolution. At present, the development of recombination hotspot predict...
Computational Biology Models, Genetic Recombination, Genetic Humans Machine Learning Algorithms
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Generation of Molecular Counterfactuals for Explainable Machine Learning Based on Core-Substituent Recombination.

ChemMedChem Dec 6, 2023
The use of black box machine learning models whose decisions cannot be understood limits the acceptance of predictions in interdisciplinary research and camouflages artificial learning characteristics leading to predictions for other than anticipated...
Machine Learning Chemistry, Pharmaceutical Recombination, Genetic Artificial Intelligence
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Charge Recombination Dynamics in a Metal Halide Perovskite Simulated by Nonadiabatic Molecular Dynamics Combined with Machine Learning.

The journal of physical chemistry letters Nov 11, 2022
Nonadiabatic coupling (NAC) plays a central role in driving nonadiabatic dynamics in various photophysical and photochemical processes. However, the high computational cost of NAC limits the time scale and system size of quantum dynamics simulation. ...
Machine Learning Recombination, Genetic Metals Molecular Dynamics Simulation Calcium Compounds
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Pseudocell Tracer-A method for inferring dynamic trajectories using scRNAseq and its application to B cells undergoing immunoglobulin class switch recombination.

PLoS computational biology May 3, 2021
Single cell RNA sequencing (scRNAseq) can be used to infer a temporal ordering of cellular states. Current methods for the inference of cellular trajectories rely on unbiased dimensionality reduction techniques. However, such biologically agnostic or...
Signal Transduction Mice, Inbred C57BL Gene Expression Mice Computational Biology Models, Immunological Receptors, Cytokine Recombination, Genetic B-Lymphocytes Supervised Machine Learning Databases, Nucleic Acid Interleukin-4 Immunoglobulin G Computer Simulation Animals Single-Cell Analysis RNA-Seq Neural Networks, Computer NF-kappa B p50 Subunit Basic-Leucine Zipper Transcription Factors STAT6 Transcription Factor Immunoglobulin Class Switching
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diploS/HIC: An Updated Approach to Classifying Selective Sweeps.

G3 (Bethesda, Md.) May 31, 2018
Identifying selective sweeps in populations that have complex demographic histories remains a difficult problem in population genetics. We previously introduced a supervised machine learning approach, S/HIC, for finding both hard and soft selective s...
Recombination, Genetic Anopheles Chromosomes Genome, Insect Animals Neural Networks, Computer ROC Curve Machine Learning Image Processing, Computer-Assisted Genotype Base Sequence Selection, Genetic
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iRSpot-PDI: Identification of recombination spots by incorporating dinucleotide property diversity information into Chou's pseudo components.

Genomics Mar 13, 2018
Recombination spot identification plays an important role in revealing genome evolution and developing DNA function study. Although some computational methods have been proposed, extracting discriminatory information embedded in DNA properties has no...
Software Genomics Computational Biology Support Vector Machine Recombination, Genetic Sequence Analysis, DNA
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Enhanced prediction of recombination hotspots using input features extracted by class specific autoencoders.

Journal of theoretical biology Feb 17, 2018
In yeast and in some mammals the frequencies of recombination are high in some genomic locations which are known as recombination hotspots and in the locations where the recombination is below average are consequently known as coldspots. Knowledge of...
Classification Saccharomyces cerevisiae Recombination, Genetic Algorithms Neural Networks, Computer Deep Learning Base Sequence
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Identifying targets of selection in mosaic genomes with machine learning: applications in Anopheles gambiae for detecting sites within locally adapted chromosomal inversions.

Molecular ecology Apr 20, 2016
Chromosomal inversions are important structural changes that may facilitate divergent selection when they capture co-adaptive loci in the face of gene flow. However, identifying selection targets within inversions can be challenging. The high degrees...
Cameroon Polymorphism, Single Nucleotide Chromosome Inversion Models, Genetic Animals Genome, Insect Machine Learning Ecosystem Recombination, Genetic Selection, Genetic Anopheles Adaptation, Physiological Insect Vectors
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Recombination spot identification Based on gapped k-mers.

Scientific reports Mar 31, 2016
Recombination is crucial for biological evolution, which provides many new combinations of genetic diversity. Accurate identification of recombination spots is useful for DNA function study. To improve the prediction accuracy, researchers have propos...
DNA Computational Biology Base Sequence Humans Benchmarking Support Vector Machine Software Recombination, Genetic Sequence Analysis, DNA
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Deep learning identifies and quantifies recombination hotspot determinants.

Bioinformatics (Oxford, England) May 13, 2022
MOTIVATION: Recombination is one of the essential genetic processes for sexually reproducing organisms, which can happen more frequently in some regions, called recombination hotspots. Although several factors, such as PRDM9 binding motifs, are known...
Meiosis Recombination, Genetic Deep Learning
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