AIMC Topic: Phenotype
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Semi-supervised learning of the electronic health record for phenotype stratification.
Journal of biomedical informatics
Oct 12, 2016
Patient interactions with health care providers result in entries to electronic health records (EHRs). EHRs were built for clinical and billing purposes but contain many data points about an individual. Mining these records provides opportunities to ...
phenoSeeder - A Robot System for Automated Handling and Phenotyping of Individual Seeds.
Plant physiology
Sep 23, 2016
The enormous diversity of seed traits is an intriguing feature and critical for the overwhelming success of higher plants. In particular, seed mass is generally regarded to be key for seedling development but is mostly approximated by using scanning ...
Mapping Phenotypic Information in Heterogeneous Textual Sources to a Domain-Specific Terminological Resource.
PloS one
Sep 19, 2016
Biomedical literature articles and narrative content from Electronic Health Records (EHRs) both constitute rich sources of disease-phenotype information. Phenotype concepts may be mentioned in text in multiple ways, using phrases with a variety of st...
Single Molecule Fluorescence Microscopy and Machine Learning for Rhesus D Antigen Classification.
Scientific reports
Sep 1, 2016
In transfusion medicine, the identification of the Rhesus D type is important to prevent anti-D immunisation in Rhesus D negative recipients. In particular, the detection of the very low expressed DEL phenotype is crucial and hence constitutes the bo...
Using the Generalized Index of Dissimilarity to Detect Gene-Gene Interactions in Multi-Class Phenotypes.
PloS one
Aug 24, 2016
To find genetic association between complex diseases and phenotypic traits, one important procedure is conducting a joint analysis. Multifactor dimensionality reduction (MDR) is an efficient method of examining the interactions between genes in genet...
Evaluating electronic health record data sources and algorithmic approaches to identify hypertensive individuals.
Journal of the American Medical Informatics Association : JAMIA
Aug 7, 2016
OBJECTIVE: Phenotyping algorithms applied to electronic health record (EHR) data enable investigators to identify large cohorts for clinical and genomic research. Algorithm development is often iterative, depends on fallible investigator intuition, a...
Design of Biomedical Robots for Phenotype Prediction Problems.
Journal of computational biology : a journal of computational molecular cell biology
Jun 27, 2016
Genomics has been used with varying degrees of success in the context of drug discovery and in defining mechanisms of action for diseases like cancer and neurodegenerative and rare diseases in the quest for orphan drugs. To improve its utility, accur...
Machine learning based methodology to identify cell shape phenotypes associated with microenvironmental cues.
Biomaterials
Jun 25, 2016
Cell morphology has been identified as a potential indicator of stem cell response to biomaterials. However, determination of cell shape phenotype in biomaterials is complicated by heterogeneous cell populations, microenvironment heterogeneity, and m...
Clinical phenotyping in selected national networks: demonstrating the need for high-throughput, portable, and computational methods.
Artificial intelligence in medicine
Jun 25, 2016
OBJECTIVE: The combination of phenomic data from electronic health records (EHR) and clinical data repositories with dense biological data has enabled genomic and pharmacogenomic discovery, a first step toward precision medicine. Computational method...
Genomic Prediction for Quantitative Traits Is Improved by Mapping Variants to Gene Ontology Categories in Drosophila melanogaster.
Genetics
May 27, 2016
Predicting individual quantitative trait phenotypes from high-resolution genomic polymorphism data is important for personalized medicine in humans, plant and animal breeding, and adaptive evolution. However, this is difficult for populations of unre...
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