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Adaptor Proteins, Signal Transducing

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Cross-disease transcriptomic analysis reveals DOK3 and PAPOLA as therapeutic targets for neuroinflammatory and tumorigenic processes.

Frontiers in immunology
OBJECTIVE: Subarachnoid hemorrhage (SAH) and tumorigenesis share numerous biological complexities; nevertheless, the specific gene expression profiles and underlying mechanisms remain poorly understood. This study aims to identify differentially expr...

Loop-mediated isothermal amplification (LAMP) and machine learning application for early pregnancy detection using bovine vaginal mucosal membrane.

Biochemical and biophysical research communications
An early and accurate pregnancy diagnosis method is required to improve the reproductive performance of cows. Here we developed an easy pregnancy detection method using vaginal mucosal membrane (VMM) with application of Reverse Transcription-Loop-med...

Identification of biomarkers for acute leukemia via machine learning-based stemness index.

Gene
Traditional methods to understand leukemia stem cell (LSC)'s biological characteristics include constructing LSC-like cells and mouse models by transgenic or knock-in methods. However, there are some potential pitfalls in using this method, such as r...

Phenotypic screening with deep learning identifies HDAC6 inhibitors as cardioprotective in a BAG3 mouse model of dilated cardiomyopathy.

Science translational medicine
Dilated cardiomyopathy (DCM) is characterized by reduced cardiac output, as well as thinning and enlargement of left ventricular chambers. These characteristics eventually lead to heart failure. Current standards of care do not target the underlying ...

Identification of adaptor proteins by incorporating deep learning and PSSM profiles.

Methods (San Diego, Calif.)
Adaptor proteins, also known as signal transduction adaptor proteins, are important proteins in signal transduction pathways, and play a role in connecting signal proteins for signal transduction between cells. Studies have shown that adaptor protein...

A lightweight classification of adaptor proteins using transformer networks.

BMC bioinformatics
BACKGROUND: Adaptor proteins play a key role in intercellular signal transduction, and dysfunctional adaptor proteins result in diseases. Understanding its structure is the first step to tackling the associated conditions, spurring ongoing interest i...

An Improved Clinical and Genetics-Based Prediction Model for Diabetic Foot Ulcer Healing.

Advances in wound care
The goal of this investigation was to use comprehensive prediction modeling tools and available genetic information to try to improve upon the performance of simple clinical models in predicting whether a diabetic foot ulcer (DFU) will heal. We uti...

Combining bioinformatics and machine learning to identify diagnostic biomarkers of TB associated with immune cell infiltration.

Tuberculosis (Edinburgh, Scotland)
OBJECTIVE: The asymptomatic nature of tuberculosis (TB) during its latent phase, combined with limitations in current diagnostic methods, makes accurate diagnosis challenging. This study aims to identify TB diagnostic biomarkers by integrating gene e...

Feature gene selection and functional validation of SH3KBP1 in infantile hemangioma using machine learning.

Biochemical and biophysical research communications
BACKGROUND: Infantile hemangioma (IH) is a prevalent vascular tumor in infancy with a complex pathogenesis that remains unclear. This study aimed to investigate the underlying mechanisms of IH using comprehensive bioinformatics analyses and in vitro ...