AIMC Topic: Amino Acids

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HN-PPISP: a hybrid network based on MLP-Mixer for protein-protein interaction site prediction.

Briefings in bioinformatics
MOTIVATION: Biological experimental approaches to protein-protein interaction (PPI) site prediction are critical for understanding the mechanisms of biochemical processes but are time-consuming and laborious. With the development of Deep Learning (DL...

PiTE: TCR-epitope Binding Affinity Prediction Pipeline using Transformer-based Sequence Encoder.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Accurate prediction of TCR binding affinity to a target antigen is important for development of immunotherapy strategies. Recent computational methods were built on various deep neural networks and used the evolutionary-based distance matrix BLOSUM t...

E-SNPs&GO: embedding of protein sequence and function improves the annotation of human pathogenic variants.

Bioinformatics (Oxford, England)
MOTIVATION: The advent of massive DNA sequencing technologies is producing a huge number of human single-nucleotide polymorphisms occurring in protein-coding regions and possibly changing their sequences. Discriminating harmful protein variations fro...

[Upgrading microbial strains for fermentation industry].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology
Fermentation is a green, low-carbon and sustainable process for the production of food, chemicals, fuels, and materials by using microbial strains as biocatalysts and renewable resources such as starch and biomass as feedstocks. China has the world's...

FCCCSR_Glu: a semi-supervised learning model based on FCCCSR algorithm for prediction of glutarylation sites.

Briefings in bioinformatics
Glutarylation is a post-translational modification which plays an irreplaceable role in various functions of the cell. Therefore, it is very important to accurately identify the glutarylation substrates and its corresponding glutarylation sites. In r...

DLF-Sul: a multi-module deep learning framework for prediction of S-sulfinylation sites in proteins.

Briefings in bioinformatics
Protein S-sulfinylation is an important posttranslational modification that regulates a variety of cell and protein functions. This modification has been linked to signal transduction, redox homeostasis and neuronal transmission in studies. Therefore...

DistilProtBert: a distilled protein language model used to distinguish between real proteins and their randomly shuffled counterparts.

Bioinformatics (Oxford, England)
SUMMARY: Recently, deep learning models, initially developed in the field of natural language processing (NLP), were applied successfully to analyze protein sequences. A major drawback of these models is their size in terms of the number of parameter...

deepHPI: a comprehensive deep learning platform for accurate prediction and visualization of host-pathogen protein-protein interactions.

Briefings in bioinformatics
Host-pathogen protein interactions (HPPIs) play vital roles in many biological processes and are directly involved in infectious diseases. With the outbreak of more frequent pandemics in the last couple of decades, such as the recent outburst of Covi...

Predicting protein-membrane interfaces of peripheral membrane proteins using ensemble machine learning.

Briefings in bioinformatics
Abnormal protein-membrane attachment is involved in deregulated cellular pathways and in disease. Therefore, the possibility to modulate protein-membrane interactions represents a new promising therapeutic strategy for peripheral membrane proteins th...

Comprehensive Prediction of Lipocalin Proteins Using Artificial Intelligence Strategy.

Frontiers in bioscience (Landmark edition)
BACKGROUND: Lipocalin belongs to the calcyin family, and its sequence length is generally between 165 and 200 residues. They are mainly stable and multifunctional extracellular proteins. Lipocalin plays an important role in several stress responses a...