AIMC Topic: Phenotype
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Ontology-based semantic mapping of chemical toxicities.
Toxicology
Nov 20, 2018
This study was undertaken to evaluate the use of ontology-based semantic mapping (OS-Mapping) in chemical toxicity assessment. Nineteen chemical-species phenotypic profiles (CSPPs) were constructed by ontologically annotating the toxicity responses r...
Deep Analysis of Mitochondria and Cell Health Using Machine Learning.
Scientific reports
Nov 5, 2018
There is a critical need for better analytical methods to study mitochondria in normal and diseased states. Mitochondrial image analysis is typically done on still images using slow manual methods or automated methods of limited types of features. Mi...
Generalized multifactor dimensionality reduction approaches to identification of genetic interactions underlying ordinal traits.
Genetic epidemiology
Nov 2, 2018
The manifestation of complex traits is influenced by gene-gene and gene-environment interactions, and the identification of multifactor interactions is an important but challenging undertaking for genetic studies. Many complex phenotypes such as dise...
Potential identification of vitamin B6 responsiveness in autism spectrum disorder utilizing phenotype variables and machine learning methods.
Scientific reports
Oct 4, 2018
We investigated whether machine learning methods could potentially identify a subgroup of persons with autism spectrum disorder (ASD) who show vitamin B6 responsiveness by selected phenotype variables. We analyzed the existing data from our intervent...
PISTON: Predicting drug indications and side effects using topic modeling and natural language processing.
Journal of biomedical informatics
Sep 27, 2018
The process of discovering novel drugs to treat diseases requires a long time and high cost. It is important to understand side effects of drugs as well as their therapeutic effects, because these can seriously damage the patients due to unexpected a...
Automatic glomerular identification and quantification of histological phenotypes using image analysis and machine learning.
American journal of physiology. Renal physiology
Sep 26, 2018
Current methods of scoring histological kidney samples, specifically glomeruli, do not allow for collection of quantitative data in a high-throughput and consistent manner. Neither untrained individuals nor computers are presently capable of identify...
Machine Learning
Software
Automation, Laboratory
Phenotype
Female
Reproducibility of Results
Animals
Male
Humans
Kidney Glomerulus
Microscopy
Image Interpretation, Computer-Assisted
Pattern Recognition, Automated
Species Specificity
Mice, Transgenic
Diagnosis, Computer-Assisted
Kidney Diseases
Rats
Predictive Value of Tests
Disease Models, Animal
Biopsy
Mice, Inbred C57BL
Workflow
Gene ontology enrichment analysis of congenital diaphragmatic hernia-associated genes.
Pediatric research
Sep 25, 2018
Congenital diaphragmatic hernia (CDH) is a commonly occurring major congenital anomaly with a profound impact on neonatal mortality. The etiology of CDH is poorly understood and is complicated by multiple clinical presentations, reflecting the locati...
A Convolutional Neural Network Uses Microscopic Images to Differentiate between Mouse and Human Cell Lines and Their Radioresistant Clones.
Cancer research
Sep 25, 2018
: Artificial intelligence (AI) trained with a convolutional neural network (CNN) is a recent technological advancement. Previously, several attempts have been made to train AI using medical images for clinical applications. However, whether AI can di...
Deep learning-based quantification of abdominal fat on magnetic resonance images.
PloS one
Sep 20, 2018
Obesity is increasingly prevalent and associated with increased risk of developing type 2 diabetes, cardiovascular diseases, and cancer. Magnetic resonance imaging (MRI) is an accurate method for determination of body fat volume and distribution. How...
Detecting gene-gene interactions for complex quantitative traits using generalized fuzzy classification.
BMC bioinformatics
Sep 18, 2018
BACKGROUND: Quantitative traits or continuous outcomes related to complex diseases can provide more information and therefore more accurate analysis for identifying gene-gene and gene- environment interactions associated with complex diseases. Multif...
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