AIMC Topic: Phenotype

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Symptom phenotyping in people with cystic fibrosis during acute pulmonary exacerbations using machine-learning K-means clustering analysis.

Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society Jun 8, 2024
INTRODUCTION: People with cystic fibrosis (PwCF) experience frequent symptoms associated with chronic lung disease. A complication of CF is a pulmonary exacerbation (PEx), which is often preceded by an increase in symptoms and a decline in lung funct...
Adult Male Disease Progression Severity of Illness Index Phenotype Machine Learning Female Adolescent Anti-Bacterial Agents Young Adult Child Longitudinal Studies United States Cluster Analysis Humans Cystic Fibrosis Symptom Assessment
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Functional Neural Networks for High-Dimensional Genetic Data Analysis.

IEEE/ACM transactions on computational biology and bioinformatics Jun 5, 2024
Artificial intelligence (AI) is a thriving research field with many successful applications in areas such as computer vision and speech recognition. Machine learning methods, such as artificial neural networks (ANN), play a central role in modern AI ...
Algorithms Phenotype Computational Biology Databases, Genetic Humans Neural Networks, Computer Machine Learning
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Phenotype clustering of hospitalized high-risk patients with COVID-19 - a machine learning approach within the multicentre, multinational PCHF-COVICAV registry.

Cardiology journal Jun 4, 2024
IMTRODUCTION: The high-risk population of patients with cardiovascular (CV) disease or risk factors (RF) suffering from COVID-19 is heterogeneous. Several predictors for impaired prognosis have been identified. However, with machine learning (ML) app...
Registries Cardiovascular Diseases Risk Assessment Cluster Analysis Humans Hospitalization Phenotype Female Aged, 80 and over Machine Learning Aged Prospective Studies SARS-CoV-2 Male COVID-19 Risk Factors Prognosis
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Machine learning models for predicting blood pressure phenotypes by combining multiple polygenic risk scores.

Scientific reports May 30, 2024
We construct non-linear machine learning (ML) prediction models for systolic and diastolic blood pressure (SBP, DBP) using demographic and clinical variables and polygenic risk scores (PRSs). We developed a two-model ensemble, consisting of a baselin...
Phenotype Female Humans Machine Learning Blood Pressure Multifactorial Inheritance Genetic Risk Score Genome-Wide Association Study Models, Genetic Risk Factors Genetic Predisposition to Disease Hypertension Male Middle Aged
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Integrating Bioinformatics and Machine Learning for Genomic Prediction in Chickens.

Genes May 26, 2024
Genomic prediction plays an increasingly important role in modern animal breeding, with predictive accuracy being a crucial aspect. The classical linear mixed model is gradually unable to accommodate the growing number of target traits and the increa...
Machine Learning Phenotype Female Polymorphism, Single Nucleotide Genotype Breeding Computational Biology Animals Quantitative Trait Loci Chickens Genome-Wide Association Study Genomics
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Bagging Improves the Performance of Deep Learning-Based Semantic Segmentation with Limited Labeled Images: A Case Study of Crop Segmentation for High-Throughput Plant Phenotyping.

Sensors (Basel, Switzerland) May 26, 2024
Advancements in imaging, computer vision, and automation have revolutionized various fields, including field-based high-throughput plant phenotyping (FHTPP). This integration allows for the rapid and accurate measurement of plant traits. Deep Convolu...
Zea mays Crops, Agricultural Semantics Phenotype Neural Networks, Computer Deep Learning Image Processing, Computer-Assisted
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Residual networks without pooling layers improve the accuracy of genomic predictions.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik May 21, 2024
Residual neural network genomic selection is the first GS algorithm to reach 35 layers, and its prediction accuracy surpasses previous algorithms. With the decrease in DNA sequencing costs and the development of deep learning, phenotype prediction ac...
Gene-Environment Interaction Genomics Models, Genetic Selection, Genetic Phenotype Neural Networks, Computer Deep Learning Algorithms
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TrG2P: A transfer-learning-based tool integrating multi-trait data for accurate prediction of crop yield.

Plant communications May 15, 2024
Yield prediction is the primary goal of genomic selection (GS)-assisted crop breeding. Because yield is a complex quantitative trait, making predictions from genotypic data is challenging. Transfer learning can produce an effective model for a target...
Phenotype Genotype Zea mays Triticum Neural Networks, Computer Machine Learning Oryza Crops, Agricultural Plant Breeding
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Machine Learning Strategies in MicroRNA Research: Bridging Genome to Phenome.

Omics : a journal of integrative biology May 15, 2024
MicroRNAs (miRNAs) have emerged as a prominent layer of regulation of gene expression. This article offers the salient and current aspects of machine learning (ML) tools and approaches from genome to phenome in miRNA research. First, we underline tha...
Gene Expression Regulation Phenotype Gene Expression Profiling Gene Regulatory Networks MicroRNAs RNA, Long Noncoding Computational Biology RNA, Messenger Humans Machine Learning
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Enhancing genome-wide populus trait prediction through deep convolutional neural networks.

The Plant journal : for cell and molecular biology May 13, 2024
As a promising model, genome-based plant breeding has greatly promoted the improvement of agronomic traits. Traditional methods typically adopt linear regression models with clear assumptions, neither obtaining the linkage between phenotype and genot...
Neural Networks, Computer Phenotype Deep Learning Genotype Populus Bayes Theorem Genome, Plant Plant Breeding
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