AIMC Topic: Signal Transduction

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Predicting Residence Time of GPCR Ligands with Machine Learning.

Methods in molecular biology (Clifton, N.J.)
Drug-target residence time, the duration of binding at a given protein target, has been shown in some protein families to be more significant for conferring efficacy than binding affinity. To carry out efficient optimization of residence time in drug...

Detection of subtype-specific breast cancer surface protein biomarkers via a novel transcriptomics approach.

Bioscience reports
BACKGROUND: Cell-surface proteins have been widely used as diagnostic and prognostic markers in cancer research and as targets for the development of anticancer agents. So far, very few attempts have been made to characterize the surfaceome of patien...

XOmiVAE: an interpretable deep learning model for cancer classification using high-dimensional omics data.

Briefings in bioinformatics
The lack of explainability is one of the most prominent disadvantages of deep learning applications in omics. This 'black box' problem can undermine the credibility and limit the practical implementation of biomedical deep learning models. Here we pr...

Identification of pan-cancer Ras pathway activation with deep learning.

Briefings in bioinformatics
The identification of hidden responders is often an essential challenge in precision oncology. A recent attempt based on machine learning has been proposed for classifying aberrant pathway activity from multiomic cancer data. However, we note several...

[Consensus ensemble neural network multitarget model of RAGE inhibitory activity of chemical compounds].

Biomeditsinskaia khimiia
RAGE signal transduction via the RAGE-NF-κB signaling pathway is one of the mechanisms of inflammatory reactions that cause severe complications in diabetes mellitus. RAGE inhibitors are promising pharmacological compounds that require the developmen...

Deep neural networks identify signaling mechanisms of ErbB-family drug resistance from a continuous cell morphology space.

Cell reports
It is well known that the development of drug resistance in cancer cells can lead to changes in cell morphology. Here, we describe the use of deep neural networks to analyze this relationship, demonstrating that complex cell morphologies can encode s...

Determining Cell Death Pathway and Regulation by Enrichment Analysis.

Methods in molecular biology (Clifton, N.J.)
Bioinformatics tools and resources are valuable for the analysis of data sets focusing on programmed cell death. This chapter discusses methods for the generation of gene sets as well as enrichment analysis using publicly available databases.