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Amino Acids

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CProMG: controllable protein-oriented molecule generation with desired binding affinity and drug-like properties.

Bioinformatics (Oxford, England)
MOTIVATION: Deep learning-based molecule generation becomes a new paradigm of de novo molecule design since it enables fast and directional exploration in the vast chemical space. However, it is still an open issue to generate molecules, which bind t...

High-accuracy protein model quality assessment using attention graph neural networks.

Briefings in bioinformatics
Great improvement has been brought to protein tertiary structure prediction through deep learning. It is important but very challenging to accurately rank and score decoy structures predicted by different models. CASP14 results show that existing qua...

ExamPle: explainable deep learning framework for the prediction of plant small secreted peptides.

Bioinformatics (Oxford, England)
MOTIVATION: Plant Small Secreted Peptides (SSPs) play an important role in plant growth, development, and plant-microbe interactions. Therefore, the identification of SSPs is essential for revealing the functional mechanisms. Over the last few decade...

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...