AIMC Topic: Amino Acids

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Rapid evaluation of Pixian Douban meju in the tank fermentor Based on the image features and multi-model analysis.

Journal of food science
Pixian Douban (PXDB) meju is a crucial intermediate product in the PXDB production. In this study, a machine vision system was employed to monitor and evaluate the meju quality quickly to replace the time-consuming chemical methods. The results of co...

SAMP: Identifying antimicrobial peptides by an ensemble learning model based on proportionalized split amino acid composition.

Briefings in functional genomics
It is projected that 10 million deaths could be attributed to drug-resistant bacteria infections in 2050. To address this concern, identifying new-generation antibiotics is an effective way. Antimicrobial peptides (AMPs), a class of innate immune eff...

TP-LMMSG: a peptide prediction graph neural network incorporating flexible amino acid property representation.

Briefings in bioinformatics
Bioactive peptide therapeutics has been a long-standing research topic. Notably, the antimicrobial peptides (AMPs) have been extensively studied for its therapeutic potential. Meanwhile, the demand for annotating other therapeutic peptides, such as a...

KCD: A prediction web server of knowledge-based circular dichroism.

Protein science : a publication of the Protein Society
We present a web server that predicts the far-UV circular dichroism (CD) spectra of proteins by utilizing their three-dimensional (3D) structures from the Protein Data Bank (PDB). The main algorithm is based on the classical theory of optical activit...

Insights into the inner workings of transformer models for protein function prediction.

Bioinformatics (Oxford, England)
MOTIVATION: We explored how explainable artificial intelligence (XAI) can help to shed light into the inner workings of neural networks for protein function prediction, by extending the widely used XAI method of integrated gradients such that latent ...

Protein structure accuracy estimation using geometry-complete perceptron networks.

Protein science : a publication of the Protein Society
Estimating the accuracy of protein structural models is a critical task in protein bioinformatics. The need for robust methods in the estimation of protein model accuracy (EMA) is prevalent in the field of protein structure prediction, where computat...

StructuralDPPIV: a novel deep learning model based on atom structure for predicting dipeptidyl peptidase-IV inhibitory peptides.

Bioinformatics (Oxford, England)
MOTIVATION: Diabetes is a chronic metabolic disorder that has been a major cause of blindness, kidney failure, heart attacks, stroke, and lower limb amputation across the world. To alleviate the impact of diabetes, researchers have developed the next...

Multi-indicator comparative evaluation for deep learning-based protein sequence design methods.

Bioinformatics (Oxford, England)
MOTIVATION: Proteins found in nature represent only a fraction of the vast space of possible proteins. Protein design presents an opportunity to explore and expand this protein landscape. Within protein design, protein sequence design plays a crucial...

Add-on treatment with Cerebrolysin improves clinical symptoms in patients with ALS: results from a prospective, single-center, placebo-controlled, randomized, double-blind, phase II study.

Journal of medicine and life
Amyotrophic lateral sclerosis (ALS) is a devastating and progressive neurodegenerative disease with limited treatment options available. Cerebrolysin is a drug candidate for the treatment of ALS because of its neuroprotective and neuroregenerative ef...