AI Medical Compendium Topic

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Gene Expression Regulation

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Identification of candidate drugs using tensor-decomposition-based unsupervised feature extraction in integrated analysis of gene expression between diseases and DrugMatrix datasets.

Scientific reports
Identifying drug target genes in gene expression profiles is not straightforward. Because a drug targets proteins and not mRNAs, the mRNA expression of drug target genes is not always altered. In addition, the interaction between a drug and protein c...

EMQIT: a machine learning approach for energy based PWM matrix quality improvement.

Biology direct
BACKGROUND: Transcription factor binding affinities to DNA play a key role for the gene regulation. Learning the specificity of the mechanisms of binding TFs to DNA is important both to experimentalists and theoreticians. With the development of high...

Unsupervised Extraction of Stable Expression Signatures from Public Compendia with an Ensemble of Neural Networks.

Cell systems
Cross-experiment comparisons in public data compendia are challenged by unmatched conditions and technical noise. The ADAGE method, which performs unsupervised integration with denoising autoencoder neural networks, can identify biological patterns, ...

Defining and characterizing the critical transition state prior to the type 2 diabetes disease.

PloS one
BACKGROUND: Type 2 diabetes mellitus (T2DM), with increased risk of serious long-term complications, currently represents 8.3% of the adult population. We hypothesized that a critical transition state prior to the new onset T2DM can be revealed throu...

Machine learning workflow to enhance predictions of Adverse Drug Reactions (ADRs) through drug-gene interactions: application to drugs for cutaneous diseases.

Scientific reports
Adverse drug reactions (ADRs) pose critical public health issues, affecting over 6% of hospitalized patients. While knowledge of potential drug-drug interactions (DDI) is necessary to prevent ADR, the rapid pace of drug discovery makes it challenging...

Prediction of marker genes associated with hypertension by bioinformatics analyses.

International journal of molecular medicine
This study aimed to explore the underlying marker genes associated with hypertension by bioinformatics analyses. A gene expression profile (GSE54015) was downloaded. The differentially expressed genes (DEGs) between the normotensive female (NF) and h...

Resistance gene identification from Larimichthys crocea with machine learning techniques.

Scientific reports
The research on resistance genes (R-gene) plays a vital role in bioinformatics as it has the capability of coping with adverse changes in the external environment, which can form the corresponding resistance protein by transcription and translation. ...

Apoptosis of rat hepatic stellate cells induced by diallyl trisulfide and proteomics profiling in vitro.

Canadian journal of physiology and pharmacology
Diallyl trisulfide (DATS), a major garlic derivative, inhibits cell proliferation and triggers apoptosis in a variety of cancer cell lines. However, the effects of DATS on hepatic stellate cells (HSCs) remain unknown. The aim of this study was to ana...