AIMC Topic: Models, Genetic

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Using machine learning and big data to explore the drug resistance landscape in HIV.

PLoS computational biology Aug 26, 2021
Drug resistance mutations (DRMs) appear in HIV under treatment pressure. DRMs are commonly transmitted to naive patients. The standard approach to reveal new DRMs is to test for significant frequency differences of mutations between treated and naive...
Africa Big Data HIV Infections Anti-HIV Agents Computational Biology Humans United Kingdom Epistasis, Genetic HIV Reverse Transcriptase Genes, Viral Bayes Theorem Logistic Models Mutation Models, Genetic Supervised Machine Learning Databases, Genetic HIV-1 Decision Trees Drug Resistance, Viral
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Bidirectional deep neural networks to integrate RNA and DNA data for predicting outcome for patients with hepatocellular carcinoma.

Future oncology (London, England) Aug 10, 2021
Individualized patient profiling is instrumental for personalized management in hepatocellular carcinoma (HCC). This study built a model based on bidirectional deep neural networks (BiDNNs), an unsupervised machine-learning approach, to integrate mu...
Deep Learning Cohort Studies Liver Neoplasms Carcinoma, Hepatocellular RNA-Seq Biomarkers, Tumor Male Middle Aged Risk Assessment Gene Regulatory Networks RNA, Messenger DNA Methylation Epigenesis, Genetic Liver Gene Expression Regulation, Neoplastic Humans Neoplasm Recurrence, Local Models, Genetic Disease-Free Survival Prognosis Datasets as Topic Female Aged Adult
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In silico saturation mutagenesis of cancer genes.

Nature Jul 28, 2021
Despite the existence of good catalogues of cancer genes, identifying the specific mutations of those genes that drive tumorigenesis across tumour types is still a largely unsolved problem. As a result, most mutations identified in cancer genes acros...
Probability Mutagenesis Organ Specificity Oncogenes Reproducibility of Results Neoplasms Models, Genetic Humans Mutation Machine Learning Cell Transformation, Neoplastic Computer Simulation Precision Medicine
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Prioritizing and characterizing functionally relevant genes across human tissues.

PLoS computational biology Jul 16, 2021
Knowledge of genes that are critical to a tissue's function remains difficult to ascertain and presents a major bottleneck toward a mechanistic understanding of genotype-phenotype links. Here, we present the first machine learning model-FUGUE-combini...
Gene Regulatory Networks Genetic Association Studies Computational Biology Models, Genetic Transcription Factors Neoplasms Transcriptome Genome-Wide Association Study Protein Interaction Maps Multigene Family Genome, Human Tissue Distribution Gene Expression Regulation, Developmental Humans Machine Learning Software Female Male
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Genetic architecture of 11 organ traits derived from abdominal MRI using deep learning.

eLife Jun 15, 2021
Cardiometabolic diseases are an increasing global health burden. While socioeconomic, environmental, behavioural, and genetic risk factors have been identified, a better understanding of the underlying mechanisms is required to develop more effective...
Models, Genetic Magnetic Resonance Imaging Adipose Tissue Iron Body Composition Digestive System Male Middle Aged Deep Learning Image Processing, Computer-Assisted Abdomen Humans Phenotype Female Aged
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Machine-learning predicts genomic determinants of meiosis-driven structural variation in a eukaryotic pathogen.

Nature communications Jun 10, 2021
Species harbor extensive structural variation underpinning recent adaptive evolution. However, the causality between genomic features and the induction of new rearrangements is poorly established. Here, we analyze a global set of telomere-to-telomere...
Machine Learning Computer Simulation Meiosis Phylogeny Eukaryota Genome INDEL Mutation Chromosomes Arabidopsis Retroelements Evolution, Molecular Crossing Over, Genetic Genome-Wide Association Study Genes, Duplicate Genetic Variation Genomics Sequence Inversion Polymorphism, Genetic Polymorphism, Single Nucleotide Ascomycota Models, Genetic Pedigree
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Finding gene network topologies for given biological function with recurrent neural network.

Nature communications May 25, 2021
Searching for possible biochemical networks that perform a certain function is a challenge in systems biology. For simple functions and small networks, this can be achieved through an exhaustive search of the network topology space. However, it is di...
Models, Genetic Gene Expression Regulation Computer Simulation Reproducibility of Results Animals Humans Gene Regulatory Networks Neural Networks, Computer Computational Biology Software Algorithms
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Feasibility of predicting allele specific expression from DNA sequencing using machine learning.

Scientific reports May 19, 2021
Allele specific expression (ASE) concerns divergent expression quantity of alternative alleles and is measured by RNA sequencing. Multiple studies show that ASE plays a role in hereditary diseases by modulating penetrance or phenotype severity. Howev...
Humans Feasibility Studies ROC Curve Machine Learning Alleles Polymorphism, Single Nucleotide Gene Expression Regulation Models, Genetic Genome, Human Sequence Analysis, DNA Bias
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Neural network aided approximation and parameter inference of non-Markovian models of gene expression.

Nature communications May 11, 2021
Non-Markovian models of stochastic biochemical kinetics often incorporate explicit time delays to effectively model large numbers of intermediate biochemical processes. Analysis and simulation of these models, as well as the inference of their parame...
Neural Networks, Computer Computer Simulation Models, Genetic Kinetics Gene Expression Regulation Transcription, Genetic Stochastic Processes Feedback, Physiological
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The Translational Machine: A novel machine-learning approach to illuminate complex genetic architectures.

Genetic epidemiology May 3, 2021
The Translational Machine (TM) is a machine learning (ML)-based analytic pipeline that translates genotypic/variant call data into biologically contextualized features that richly characterize complex variant architectures and permit greater interpre...
Machine Learning Algorithms Genomics Humans Genotype Models, Genetic
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