AIMC Topic: Gene-Environment Interaction
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Gene-environment interaction analysis via deep learning.
Genetic epidemiology
Feb 19, 2023
Gene-environment (G-E) interaction analysis plays an important role in studying complex diseases. Extensive methodological research has been conducted on G-E interaction analysis, and the existing methods are mostly based on regression techniques. In...
Neural Networks Enhanced Optimal Admittance Control of Robot-Environment Interaction Using Reinforcement Learning.
IEEE transactions on neural networks and learning systems
Aug 31, 2022
In this paper, an adaptive admittance control scheme is developed for robots to interact with time-varying environments. Admittance control is adopted to achieve a compliant physical robot-environment interaction, and the uncertain environment with t...
AsthmaKGxE: An asthma-environment interaction knowledge graph leveraging public databases and scientific literature.
Computers in biology and medicine
Aug 2, 2022
MOTIVATION: Asthma is a complex heterogeneous disease resulting from intricate interactions between genetic and non-genetic factors related to environmental and psychosocial aspects. Discovery of such interactions can provide insights into the pathop...
Interpretable modeling of genotype-phenotype landscapes with state-of-the-art predictive power.
Proceedings of the National Academy of Sciences of the United States of America
Jun 21, 2022
Large-scale measurements linking genetic background to biological function have driven a need for models that can incorporate these data for reliable predictions and insight into the underlying biophysical system. Recent modeling efforts, however, pr...
Identification of Autistic Risk Candidate Genes and Toxic Chemicals via Multilabel Learning.
IEEE transactions on neural networks and learning systems
Aug 31, 2021
As a group of complex neurodevelopmental disorders, autism spectrum disorder (ASD) has been reported to have a high overall prevalence, showing an unprecedented spurt since 2000. Due to the unclear pathomechanism of ASD, it is challenging to diagnose...
HapFIC: An Adaptive Force/Position Controller for Safe Environment Interaction in Articulated Systems.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jul 27, 2021
Haptic interaction is essential for the dynamic dexterity of animals, which seamlessly switch from an impedance to an admittance behaviour using the force feedback from their proprioception. However, this ability is extremely challenging to reproduce...
Transforming the study of organisms: Phenomic data models and knowledge bases.
PLoS computational biology
Nov 24, 2020
The rapidly decreasing cost of gene sequencing has resulted in a deluge of genomic data from across the tree of life; however, outside a few model organism databases, genomic data are limited in their scientific impact because they are not accompanie...
Robust optimization through neuroevolution.
PloS one
Mar 1, 2019
We propose a method for evolving neural network controllers robust with respect to variations of the environmental conditions (i.e. that can operate effectively in new conditions immediately, without the need to adapt to variations). The method speci...
Multi-trait, Multi-environment Deep Learning Modeling for Genomic-Enabled Prediction of Plant Traits.
G3 (Bethesda, Md.)
Dec 10, 2018
Multi-trait and multi-environment data are common in animal and plant breeding programs. However, what is lacking are more powerful statistical models that can exploit the correlation between traits to improve prediction accuracy in the context of ge...
Multi-environment Genomic Prediction of Plant Traits Using Deep Learners With Dense Architecture.
G3 (Bethesda, Md.)
Dec 10, 2018
Genomic selection is revolutionizing plant breeding and therefore methods that improve prediction accuracy are useful. For this reason, active research is being conducted to build and test methods from other areas and adapt them to the context of gen...
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