AIMC Topic: Data Visualization
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Dissection of gene expression datasets into clinically relevant interaction signatures via high-dimensional correlation maximization.
Nature communications
Nov 28, 2019
Gene expression is controlled by many simultaneous interactions, frequently measured collectively in biology and medicine by high-throughput technologies. It is a highly challenging task to infer from these data the generating effects and cooperating...
GAIL: An interactive webserver for inference and dynamic visualization of gene-gene associations based on gene ontology guided mining of biomedical literature.
PloS one
Jul 1, 2019
In systems biology, inference of functional associations among genes is compelling because the construction of functional association networks facilitates biomarker discovery. Specifically, such gene associations in human can help identify putative b...
How Knowledge Emerges From Artificial Intelligence Algorithm and Data Visualization for Diabetes Management.
Journal of diabetes science and technology
May 21, 2019
BACKGROUND: Self-monitoring blood glucose (SMBG) is facilitated by application available to analyze these data. They are mainly based on descriptive statistical analyses. In this study, we are proposing a method inspired by artificial intelligence al...
Sparse Generative Topographic Mapping for Both Data Visualization and Clustering.
Journal of chemical information and modeling
Oct 31, 2018
To achieve simultaneous data visualization and clustering, the method of sparse generative topographic mapping (SGTM) is developed by modifying the conventional GTM algorithm. While the weight of each grid point is constant in the original GTM, it be...
Differential Data Augmentation Techniques for Medical Imaging Classification Tasks.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Apr 16, 2018
Data augmentation is an essential part of training discriminative Convolutional Neural Networks (CNNs). A variety of augmentation strategies, including horizontal flips, random crops, and principal component analysis (PCA), have been proposed and sho...
A Novel Early Warning Model for Hand, Foot and Mouth Disease Prediction Based on a Graph Convolutional Network.
Biomedical and environmental sciences : BES
Jun 20, 2022
OBJECTIVES: Hand, foot and mouth disease (HFMD) is a widespread infectious disease that causes a significant disease burden on society. To achieve early intervention and to prevent outbreaks of disease, we propose a novel warning model that can accur...
Why can deep convolutional neural networks improve protein fold recognition? A visual explanation by interpretation.
Briefings in bioinformatics
Sep 2, 2021
As an essential task in protein structure and function prediction, protein fold recognition has attracted increasing attention. The majority of the existing machine learning-based protein fold recognition approaches strongly rely on handcrafted featu...
Modeling polypharmacy side effects with graph convolutional networks.
Bioinformatics (Oxford, England)
Jul 1, 2018
MOTIVATION: The use of drug combinations, termed polypharmacy, is common to treat patients with complex diseases or co-existing conditions. However, a major consequence of polypharmacy is a much higher risk of adverse side effects for the patient. Po...
L1000FWD: fireworks visualization of drug-induced transcriptomic signatures.
Bioinformatics (Oxford, England)
Jun 15, 2018
MOTIVATION: As part of the NIH Library of Integrated Network-based Cellular Signatures program, hundreds of thousands of transcriptomic signatures were generated with the L1000 technology, profiling the response of human cell lines to over 20 000 sma...
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