AIMC Topic: Computer Simulation
Clear Filters Showing 3521 to 3530 of 3881 articles
BioNet: a large-scale and heterogeneous biological network model for interaction prediction with graph convolution.
Briefings in bioinformatics
Jan 17, 2022
MOTIVATION: Understanding chemical-gene interactions (CGIs) is crucial for screening drugs. Wet experiments are usually costly and laborious, which limits relevant studies to a small scale. On the contrary, computational studies enable efficient in-s...
Learning representation for multiple biological networks via a robust graph regularized integration approach.
Briefings in bioinformatics
Jan 17, 2022
Learning node representation is a fundamental problem in biological network analysis, as compact representation features reveal complicated network structures and carry useful information for downstream tasks such as link prediction and node classifi...
The machine as a partner: Human-machine teaming design using the PRODEC method.
Work (Reading, Mass.)
Jan 1, 2022
BACKGROUND: Human-machine teaming (HMT) typically combines perspectives from systems engineering, artificial intelligence (AI) and human-centered design (HCD), to achieve human systems integration (HSI) through the development of an integrative syste...
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Journal of biosciences
Jan 1, 2022
Network biology finds application in interpreting molecular interaction networks and providing insightful inferences using graph theoretical analysis of biological systems. The integration of computational biomodelling approaches with different hybri...
GRNUlar: A Deep Learning Framework for Recovering Single-Cell Gene Regulatory Networks.
Journal of computational biology : a journal of computational molecular cell biology
Jan 1, 2022
We propose GRNUlar, a novel deep learning framework for supervised learning of gene regulatory networks (GRNs) from single-cell RNA-Sequencing (scRNA-Seq) data. Our framework incorporates two intertwined models. First, we leverage the expressive abil...
[Improvement of Motion Artifacts in Brain MRI Using Deep Learning by Simulation Training Data].
Nihon Hoshasen Gijutsu Gakkai zasshi
Jan 1, 2022
PURPOSE: To test whether deep learning can be used to effectively reduce artifacts in MR images of the brain.
Trial Approach for Biomedical Products: A Regulatory Perspective.
Combinatorial chemistry & high throughput screening
Jan 1, 2022
The modern pharmaceutical industry is transitioning from traditional methods to advanced technologies like artificial intelligence. In the current scenario, continuous efforts are being made to incorporate computational modeling and simulation in dru...
Machine Learning for In Silico ADMET Prediction.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2022
ADMET (absorption, distribution, metabolism, excretion, and toxicity) describes a drug molecule's pharmacokinetics and pharmacodynamics properties. ADMET profile of a bioactive compound can impact its efficacy and safety. Moreover, efficacy and safet...
Validation of a Simulation Model for Robotic Sacrocolpopexy.
Female pelvic medicine & reconstructive surgery
Jan 1, 2022
OBJECTIVE: We sought to validate a simulation model for robotic sacrocolpopexy (RSCP) that includes multiple steps: presacral dissection/mesh attachment, vaginal mesh attachment, and peritoneal closure.
Predicting Proteome-Scale Protein Structure with Artificial Intelligence.
The New England journal of medicine
Dec 2, 2021
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