AIMC Topic:
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Correlation Network Analysis Provides Important Modules and Pathways for Human Hyperlipidemia.
Critical reviews in eukaryotic gene expression
Jan 1, 2019
Hyperlipidemia casts great threats to humans around the world. The systemic co-expression and function enrichment analysis for this disease is limited to date. This study was to identify co-expression modules to explore hyperlipidemia-associated func...
Recognition of Lung Adenocarcinoma-specific Gene Pairs Based on Genetic Algorithm and Establishment of a Deep Learning Prediction Model.
Combinatorial chemistry & high throughput screening
Jan 1, 2019
AIM AND OBJECTIVE: Lung cancer is a disease with a dismal prognosis and is the major cause of cancer deaths in many countries. Nonetheless, rapid technological developments in genome science guarantees more effective prevention and treatment strategi...
A Drug Repurposing Method Based on Drug-Drug Interaction Networks and Using Energy Model Layouts.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2019
Complex network representations of reported drug-drug interactions foster computational strategies that can infer pharmacological functions which, in turn, create incentives for drug repositioning. Here, we use Gephi (a platform for complex network v...
EBIC: an evolutionary-based parallel biclustering algorithm for pattern discovery.
Bioinformatics (Oxford, England)
Nov 1, 2018
MOTIVATION: Biclustering algorithms are commonly used for gene expression data analysis. However, accurate identification of meaningful structures is very challenging and state-of-the-art methods are incapable of discovering with high accuracy differ...
Chaos versus noise as drivers of multistability in neural networks.
Chaos (Woodbury, N.Y.)
Oct 1, 2018
The multistable behavior of neural networks is actively being studied as a landmark of ongoing cerebral activity, reported in both functional Magnetic Resonance Imaging (fMRI) and electro- or magnetoencephalography recordings. This consists of a cont...
Classification of Cardiovascular Disease via A New SoftMax Model.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2018
Cardiovascular disease clinical diagnosis is an essentially problem of pattern recognition. In the traditional intelligent diagnosis, the evaluation of classification algorithm is based on the final accuracy of the disease diagnosis. In this paper, a...
Convolutional neural networks for classification of alignments of non-coding RNA sequences.
Bioinformatics (Oxford, England)
Jul 1, 2018
MOTIVATION: The convolutional neural network (CNN) has been applied to the classification problem of DNA sequences, with the additional purpose of motif discovery. The training of CNNs with distributed representations of four nucleotides has successf...
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...
Texture Analysis and Machine Learning for Detecting Myocardial Infarction in Noncontrast Low-Dose Computed Tomography: Unveiling the Invisible.
Investigative radiology
Jun 1, 2018
OBJECTIVES: The aim of this study was to test whether texture analysis and machine learning enable the detection of myocardial infarction (MI) on non-contrast-enhanced low radiation dose cardiac computed tomography (CCT) images.
Machine learning to detect signatures of disease in liquid biopsies - a user's guide.
Lab on a chip
Jan 30, 2018
New technologies that measure sparse molecular biomarkers from easily accessible bodily fluids (e.g. blood, urine, and saliva) are revolutionizing disease diagnostics and precision medicine. Microchip devices can measure more disease biomarkers with ...
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