AIMC Topic: Phenotype

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A Knowledge-Guided Graph Learning Approach Bridging Phenotype- and Target-Based Drug Discovery.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Mar 6, 2025
Discovering therapeutic molecules requires the integration of both phenotype-based drug discovery (PDD) and target-based drug discovery (TDD). However, this integration remains challenging due to the inherent heterogeneity, noise, and bias present in...
Humans Phenotype SARS-CoV-2 Drug Discovery COVID-19 Drug Treatment Neural Networks, Computer Machine Learning COVID-19
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NPENN: A Noise Perturbation Ensemble Neural Network for Microbiome Disease Phenotype Prediction.

IEEE journal of biomedical and health informatics Mar 6, 2025
With advances in microbiomics, the crucial role of microbes in disease progression is increasingly recognized. However, predicting disease phenotypes using microbiome data remains challenging due to data complexity, heterogeneity, and limited model g...
Computational Biology Humans Microbiota Neural Networks, Computer Phenotype
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Multi-Omics Deep-Learning Prediction of Homologous Recombination Deficiency-Like Phenotype Improved Risk Stratification and Guided Therapeutic Decisions in Gynecological Cancers.

IEEE journal of biomedical and health informatics Mar 6, 2025
Homologous recombination deficiency (HRD) is a well-recognized important biomarker in determining the clinical benefits of platinum-based chemotherapy and PARP inhibitor therapy for patients diagnosed with gynecologic cancers. Accurate prediction of ...
Autoencoder Homologous Recombination Phenotype DNA Methylation Female Ovarian Neoplasms Biomarkers, Tumor Genital Neoplasms, Female Humans Risk Assessment Genomics Multiomics
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Intelligent larval zebrafish phenotype recognition via attention mechanism for high-throughput screening.

Computers in biology and medicine Feb 25, 2025
BACKGROUND: Larval zebrafish phenotypes serve as critical research indicators in fields such as ecotoxicology and safety assessment since phenotypic defects are closely related to alterations of underlying pathway. However, identifying these defects ...
Zebrafish High-Throughput Screening Assays Phenotype Deep Learning Animals Larva Image Processing, Computer-Assisted
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Evaluating feature extraction in ovarian cancer cell line co-cultures using deep neural networks.

Communications biology Feb 25, 2025
Single-cell image analysis is crucial for studying drug effects on cellular morphology and phenotypic changes. Most studies focus on single cell types, overlooking the complexity of cellular interactions. Here, we establish an analysis pipeline to ex...
Humans Ovarian Neoplasms Coculture Techniques Antineoplastic Agents Neural Networks, Computer Single-Cell Analysis Cell Line, Tumor Phenotype Fibroblasts Female
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Genetic association studies using disease liabilities from deep neural networks.

American journal of human genetics Feb 21, 2025
The case-control study is a widely used method for investigating the genetic underpinnings of binary traits. However, long-term, prospective cohort studies often grapple with absent or evolving health-related outcomes. Here, we propose two methods, l...
Male Case-Control Studies Genome-Wide Association Study Genetic Predisposition to Disease Polymorphism, Single Nucleotide Genetic Association Studies Neural Networks, Computer Phenotype Female Humans Multifactorial Inheritance
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Comparing statistical learning methods for complex trait prediction from gene expression.

PloS one Feb 11, 2025
Accurate prediction of complex traits is an important task in quantitative genetics. Genotypes have been used for trait prediction using a variety of methods such as mixed models, Bayesian methods, penalized regression methods, dimension reduction me...
Models, Genetic Animals Machine Learning Reflex, Startle Drosophila melanogaster Male Phenotype Drosophila Genotype Female
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Association Between Aortic Imaging Features and Impaired Glucose Metabolism: A Deep Learning Population Phenotyping Approach.

Academic radiology Feb 10, 2025
RATIONALE AND OBJECTIVES: Type 2 diabetes is a known risk factor for vascular disease with an impact on the aorta. The aim of this study was to develop a deep learning framework for quantification of aortic phenotypes from magnetic resonance imaging ...
Aged Male Middle Aged Prospective Studies Magnetic Resonance Imaging Humans Deep Learning Female Aorta Phenotype Diabetes Mellitus, Type 2 Risk Factors
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Comparing Phenotypes for Acute and Long-Term Response to Atrial Fibrillation Ablation Using Machine Learning.

Circulation. Arrhythmia and electrophysiology Feb 10, 2025
BACKGROUND: It is difficult to identify patients with atrial fibrillation (AF) most likely to respond to ablation. While any arrhythmia patient may recur after acutely successful ablation, AF is unusual in that patients may have long-term arrhythmia ...
Catheter Ablation Electrophysiologic Techniques, Cardiac Registries Atrial Fibrillation Heart Rate Middle Aged Time Factors Electrocardiography Treatment Outcome Action Potentials Predictive Value of Tests Female Aged Male Humans Machine Learning Phenotype
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Learning Phenotype Associated Signature in Spatial Transcriptomics with PASSAGE.

Small methods Feb 4, 2025
Spatially resolved transcriptomics (SRT) is poised to advance the understanding of cellular organization within complex tissues under various physiological and pathological conditions at unprecedented resolution. Despite the development of numerous c...
Humans Gene Expression Profiling Transcriptome Software Deep Learning Algorithms Computational Biology Phenotype
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