AIMC Topic: Phenotype

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Epistasis Detection Based on Epi-GTBN.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2021
Epistasis detection is a hot topic in bioinformatics due to its relevance to the detection of specific phenotypic traits and gene-gene interactions. Here, we present a step-by-step protocol to apply Epi-GTBN, a machine learning-based method based on ...
Phenotype Gene Regulatory Networks Polymorphism, Single Nucleotide Genotype Models, Genetic Humans Machine Learning Software Bayes Theorem Genetic Loci Data Mining Datasets as Topic Epistasis, Genetic
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Protocol for Epistasis Detection with Machine Learning Using GenEpi Package.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2021
To develop medical treatments and prevention, the association between disease and genetic variants needs to be identified. The main goal of genome-wide association study (GWAS) is to discover the underlying reason for vulnerability to disease and uti...
Humans Machine Learning Software Phenotype Genome-Wide Association Study Databases, Genetic Genome, Human Polymorphism, Single Nucleotide Epistasis, Genetic Genotype Genetic Association Studies Computational Biology
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Brief Survey on Machine Learning in Epistasis.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2021
In biology, the term "epistasis" indicates the effect of the interaction of a gene with another gene. A gene can interact with an independently sorted gene, located far away on the chromosome or on an entirely different chromosome, and this interacti...
Phenotype Genome, Human Neoplasms Epistasis, Genetic Quantitative Trait, Heritable Humans Genome-Wide Association Study Inheritance Patterns Machine Learning Crohn Disease Polymorphism, Single Nucleotide Computational Biology Plants Macular Degeneration Data Mining Alzheimer Disease
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Deep learning model for the prediction of microsatellite instability in colorectal cancer: a diagnostic study.

The Lancet. Oncology Jan 1, 2021
BACKGROUND: Detecting microsatellite instability (MSI) in colorectal cancer is crucial for clinical decision making, as it identifies patients with differential treatment response and prognosis. Universal MSI testing is recommended, but many patients...
Humans Phenotype Reproducibility of Results Colorectal Neoplasms Diagnosis, Computer-Assisted Coloring Agents Microscopy Image Interpretation, Computer-Assisted Eosine Yellowish-(YS) Hematoxylin Deep Learning Genetic Predisposition to Disease Staining and Labeling Predictive Value of Tests Microsatellite Instability
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PheMap: a multi-resource knowledge base for high-throughput phenotyping within electronic health records.

Journal of the American Medical Informatics Association : JAMIA Nov 1, 2020
OBJECTIVE: Developing algorithms to extract phenotypes from electronic health records (EHRs) can be challenging and time-consuming. We developed PheMap, a high-throughput phenotyping approach that leverages multiple independent, online resources to s...
Knowledge Bases Information Storage and Retrieval Terminology as Topic Diabetes Mellitus, Type 2 Polymorphism, Single Nucleotide Hypothyroidism Natural Language Processing Humans Algorithms Phenotype Electronic Health Records Adult Dementia Genome-Wide Association Study
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Artificial intelligence in medical imaging: A radiomic guide to precision phenotyping of cardiovascular disease.

Cardiovascular research Nov 1, 2020
Rapid technological advances in non-invasive imaging, coupled with the availability of large data sets and the expansion of computational models and power, have revolutionized the role of imaging in medicine. Non-invasive imaging is the pillar of mod...
Radiographic Image Interpretation, Computer-Assisted Phenotype Prognosis Tomography, X-Ray Computed Clinical Decision-Making Reproducibility of Results Cardiovascular Diseases Diagnosis, Computer-Assisted Big Data Predictive Value of Tests Humans Machine Learning
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Machine Learning Classifier Models Can Identify Acute Respiratory Distress Syndrome Phenotypes Using Readily Available Clinical Data.

American journal of respiratory and critical care medicine Oct 1, 2020
Two distinct phenotypes of acute respiratory distress syndrome (ARDS) with differential clinical outcomes and responses to randomly assigned treatment have consistently been identified in randomized controlled trial cohorts using latent class analys...
Tidal Volume Blood Pressure Area Under Curve Interleukin-8 Oxygen Intercellular Adhesion Molecule-1 Receptors, Tumor Necrosis Factor, Type I Vital Signs Creatinine Latent Class Analysis Partial Pressure Serum Albumin Vasoconstrictor Agents Plasminogen Activator Inhibitor 1 Humans Inflammation Carbon Dioxide Mortality Protein C Platelet Count Phenotype Age Factors Machine Learning Bicarbonates Bilirubin Interleukin-6 Leukocyte Count Respiratory Distress Syndrome Pulmonary Ventilation Prognosis Randomized Controlled Trials as Topic Biomarkers, Tumor
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Comparison of data analytics strategies in computer vision systems to predict pig body composition traits from 3D images.

Journal of animal science Aug 1, 2020
Computer vision systems (CVS) have been shown to be a powerful tool for the measurement of live pig body weight (BW) with no animal stress. With advances in precision farming, it is now possible to evaluate the growth performance of individual pigs m...
Machine Learning Algorithms Phenotype Tomography, X-Ray Computed Body Weight Swine Humans Animals Linear Models Data Science Neural Networks, Computer Muscles Ultrasonography Image Processing, Computer-Assisted Body Composition
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Genome-wide prediction for complex traits under the presence of dominance effects in simulated populations using GBLUP and machine learning methods.

Journal of animal science Jun 1, 2020
The aim of this study was to compare the predictive performance of the Genomic Best Linear Unbiased Predictor (GBLUP) and machine learning methods (Random Forest, RF; Support Vector Machine, SVM; Artificial Neural Network, ANN) in simulated populatio...
Multifactorial Inheritance Phenotype Machine Learning Genes, Dominant Computer Simulation Male Female Genomics Animals Genotype Breeding Genome
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Multi-dimensional machine learning approaches for fruit shape phenotyping in strawberry.

GigaScience May 1, 2020
BACKGROUND: Shape is a critical element of the visual appeal of strawberry fruit and is influenced by both genetic and non-genetic determinants. Current fruit phenotyping approaches for external characteristics in strawberry often rely on the human e...
Models, Theoretical Machine Learning Fruit Algorithms Fragaria Phenotype Inheritance Patterns Genetic Association Studies
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