AIMC Topic: Phenotype
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A platform for artificial intelligence based identification of the extravasation potential of cancer cells into the brain metastatic niche.
Lab on a chip
Mar 27, 2019
Brain metastases are the most lethal complication of advanced cancer; therefore, it is critical to identify when a tumor has the potential to metastasize to the brain. There are currently no interventions that shed light on the potential of primary t...
Machine learning approaches to decipher hormone and HER2 receptor status phenotypes in breast cancer.
Briefings in bioinformatics
Mar 22, 2019
Breast cancer prognosis and administration of therapies are aided by knowledge of hormonal and HER2 receptor status. Breast cancer lacking estrogen receptors, progesterone receptors and HER2 receptors are difficult to treat. Regarding large data repo...
Discovery of Distinct Immune Phenotypes Using Machine Learning in Pulmonary Arterial Hypertension.
Circulation research
Mar 15, 2019
RATIONALE: Accumulating evidence implicates inflammation in pulmonary arterial hypertension (PAH) and therapies targeting immunity are under investigation, although it remains unknown if distinct immune phenotypes exist.
Integrating ontologies of human diseases, phenotypes, and radiological diagnosis.
Journal of the American Medical Informatics Association : JAMIA
Feb 1, 2019
Mappings between ontologies enable reuse and interoperability of biomedical knowledge. The Radiology Gamuts Ontology (RGO)-an ontology of 16 918 diseases, interventions, and imaging observations-provides a resource for differential diagnosis and auto...
Towards rapid prediction of drug-resistant cancer cell phenotypes: single cell mass spectrometry combined with machine learning.
Chemical communications (Cambridge, England)
Jan 10, 2019
Combined single cell mass spectrometry and machine learning methods is demonstrated for the first time to achieve rapid and reliable prediction of the phenotype of unknown single cells based on their metabolomic profiles, with experimental validation...
Expansion of the Human Phenotype Ontology (HPO) knowledge base and resources.
Nucleic acids research
Jan 8, 2019
The Human Phenotype Ontology (HPO)-a standardized vocabulary of phenotypic abnormalities associated with 7000+ diseases-is used by thousands of researchers, clinicians, informaticians and electronic health record systems around the world. Its detaile...
Predicting Influenza A Tropism with End-to-End Learning of Deep Networks.
Health security
Jan 1, 2019
The type of host that a virus can infect, referred to as host specificity or tropism, influences infectivity and thus is important for disease diagnosis, epidemic response, and prevention. Advances in DNA sequencing technology have enabled rapid meta...
The Sickle Cell Disease Ontology: enabling universal sickle cell-based knowledge representation.
Database : the journal of biological databases and curation
Jan 1, 2019
Sickle cell disease (SCD) is one of the most common monogenic diseases in humans with multiple phenotypic expressions that can manifest as both acute and chronic complications. Although described more than a century ago, challenges in comprehensive d...
A Phenotypic Description of Congenital Myotonic Dystrophy using PhenoStacks.
Journal of neuromuscular diseases
Jan 1, 2019
BACKGROUND: Congenital Myotonic Dystrophy (CDM1) is a rare neuromuscular condition caused by a triplet repeat expansion in the DMPK gene. Despite there being a well-recognized clinical syndrome, there has not been an effort to use a standardized onto...
Quantitative Modelling of the Waddington Epigenetic Landscape.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2019
C.H. Waddington introduced the epigenetic landscape as a metaphor to represent cellular decision-making during development. Like a population of balls rolling down a rough hillside, developing cells follow specific trajectories (valleys) and eventual...
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