AI Medical Compendium Topic:
Amino Acid Sequence

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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...

UniProt: the Universal Protein Knowledgebase in 2023.

Nucleic acids research
The aim of the UniProt Knowledgebase is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this publication we describe enhancements made to our data processing...

Prediction of Bacterial Immunogenicity by Machine Learning Methods.

Methods in molecular biology (Clifton, N.J.)
Prediction of bacterial immunogens is a prerequisite for the process of vaccine development through reverse vaccinology. The application of in silico methods allows significant reduction in time and cost for the discovery of potential vaccine candida...

[Method to Generate Complex Predictive Features for Machine Learning-Based Prediction of the Local Structure and Functions of Proteins].

Molekuliarnaia biologiia
Recently, prediction of the structure and function of a protein from its sequence underwent a rapid increase in performance. It is primarily due to the application of machine learning methods, many of which rely on the predictive features supplied to...

Discovering misannotated lncRNAs using deep learning training dynamics.

Bioinformatics (Oxford, England)
MOTIVATION: Recent experimental evidence has shown that some long non-coding RNAs (lncRNAs) contain small open reading frames (sORFs) that are translated into functional micropeptides, suggesting that these lncRNAs are misannotated as non-coding. Cur...

Annotation of biologically relevant ligands in UniProtKB using ChEBI.

Bioinformatics (Oxford, England)
MOTIVATION: To provide high quality, computationally tractable annotation of binding sites for biologically relevant (cognate) ligands in UniProtKB using the chemical ontology ChEBI (Chemical Entities of Biological Interest), to better support effort...

DeepCellEss: cell line-specific essential protein prediction with attention-based interpretable deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: Protein essentiality is usually accepted to be a conditional trait and strongly affected by cellular environments. However, existing computational methods often do not take such characteristics into account, preferring to incorporate all ...

LambdaPP: Fast and accessible protein-specific phenotype predictions.

Protein science : a publication of the Protein Society
The availability of accurate and fast artificial intelligence (AI) solutions predicting aspects of proteins are revolutionizing experimental and computational molecular biology. The webserver LambdaPP aspires to supersede PredictProtein, the first in...

Deep learning of protein sequence design of protein-protein interactions.

Bioinformatics (Oxford, England)
MOTIVATION: As more data of experimentally determined protein structures are becoming available, data-driven models to describe protein sequence-structure relationships become more feasible. Within this space, the amino acid sequence design of protei...