AIMC Topic: Phenotype

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EmbryoNet: using deep learning to link embryonic phenotypes to signaling pathways.

Nature methods May 8, 2023
Evolutionarily conserved signaling pathways are essential for early embryogenesis, and reducing or abolishing their activity leads to characteristic developmental defects. Classification of phenotypic defects can identify the underlying signaling mec...
Algorithms Phenotype Neural Networks, Computer Signal Transduction Zebrafish Deep Learning Animals
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Characterizing Patient Representations for Computational Phenotyping.

AMIA ... Annual Symposium proceedings. AMIA Symposium Apr 29, 2023
Patient representation learning methods create rich representations of complex data and have potential to further advance the development of computational phenotypes (CP). Currently, these methods are either applied to small predefined concept sets o...
Rare Diseases Humans Phenotype Machine Learning
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Relating enhancer genetic variation across mammals to complex phenotypes using machine learning.

Science (New York, N.Y.) Apr 28, 2023
Protein-coding differences between species often fail to explain phenotypic diversity, suggesting the involvement of genomic elements that regulate gene expression such as enhancers. Identifying associations between enhancers and phenotypes is challe...
Enhancer Elements, Genetic Animals Machine Learning Genetic Variation Phenotype Mammals
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The Ontology of Biological Attributes (OBA)-computational traits for the life sciences.

Mammalian genome : official journal of the International Mammalian Genome Society Apr 19, 2023
Existing phenotype ontologies were originally developed to represent phenotypes that manifest as a character state in relation to a wild-type or other reference. However, these do not include the phenotypic trait or attribute categories required for ...
Biological Ontologies Biological Science Disciplines Phenotype Genome-Wide Association Study
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Automatic extraction of ranked SNP-phenotype associations from text using a BERT-LSTM-based method.

BMC bioinformatics Apr 12, 2023
Extraction of associations of singular nucleotide polymorphism (SNP) and phenotypes from biomedical literature is a vital task in BioNLP. Recently, some methods have been developed to extract mutation-diseases affiliations. However, no accessible met...
Polymorphism, Single Nucleotide Mutation Phenotype Machine Learning Random Forest
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Semiquantitative Fingerprinting Based on Pseudotargeted Metabolomics and Deep Learning for the Identification of and Its Major Serotypes.

Analytical chemistry Apr 4, 2023
The rapid identification of pathogenic microorganism serotypes is still a bottleneck problem to be solved urgently. Compared with proteomics technology, metabolomics technology is directly related to phenotypes and has higher specificity in identifyi...
Phenotype Metabolomics Deep Learning Listeria monocytogenes Serogroup
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PhenoBERT: A Combined Deep Learning Method for Automated Recognition of Human Phenotype Ontology.

IEEE/ACM transactions on computational biology and bioinformatics Apr 3, 2023
Automated recognition of Human Phenotype Ontology (HPO) terms from clinical texts is of significant interest to the field of clinical data mining. In this study, we develop a combined deep learning method named PhenoBERT for this purpose. PhenoBERT u...
Phenotype Benchmarking Deep Learning Humans Family Data Mining
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A Multi-Attention Approach for Person Re-Identification Using Deep Learning.

Sensors (Basel, Switzerland) Apr 2, 2023
Person re-identification (Re-ID) is a method for identifying the same individual via several non-interfering cameras. Person Re-ID has been felicitously applied to an assortment of computer vision applications. Due to the emergence of deep learning a...
Phenotype Deep Learning Algorithms Humans
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Label-free macrophage phenotype classification using machine learning methods.

Scientific reports Mar 30, 2023
Macrophages are heterogeneous innate immune cells that are functionally shaped by their surrounding microenvironment. Diverse macrophage populations have multifaceted differences related to their morphology, metabolism, expressed markers, and functio...
Phenotype Macrophages Machine Learning
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Automated prioritization of sick newborns for whole genome sequencing using clinical natural language processing and machine learning.

Genome medicine Mar 16, 2023
BACKGROUND: Rapidly and efficiently identifying critically ill infants for whole genome sequencing (WGS) is a costly and challenging task currently performed by scarce, highly trained experts and is a major bottleneck for application of WGS in the NI...
Intensive Care Units, Neonatal Humans Whole Genome Sequencing Machine Learning Infant, Newborn Natural Language Processing Phenotype
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