AIMC Topic: Proteins

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CryoTransformer: a transformer model for picking protein particles from cryo-EM micrographs.

Bioinformatics (Oxford, England)
MOTIVATION: Cryo-electron microscopy (cryo-EM) is a powerful technique for determining the structures of large protein complexes. Picking single protein particles from cryo-EM micrographs (images) is a crucial step in reconstructing protein structure...

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...

De novo protein design-From new structures to programmable functions.

Cell
Methods from artificial intelligence (AI) trained on large datasets of sequences and structures can now "write" proteins with new shapes and molecular functions de novo, without starting from proteins found in nature. In this Perspective, I will disc...

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...

TIMED-Design: flexible and accessible protein sequence design with convolutional neural networks.

Protein engineering, design & selection : PEDS
Sequence design is a crucial step in the process of designing or engineering proteins. Traditionally, physics-based methods have been used to solve for optimal sequences, with the main disadvantages being that they are computationally intensive for t...

A comprehensive computational benchmark for evaluating deep learning-based protein function prediction approaches.

Briefings in bioinformatics
Proteins play an important role in life activities and are the basic units for performing functions. Accurately annotating functions to proteins is crucial for understanding the intricate mechanisms of life and developing effective treatments for com...

Analysis and review of techniques and tools based on machine learning and deep learning for prediction of lysine malonylation sites in protein sequences.

Database : the journal of biological databases and curation
The post-translational modifications occur as crucial molecular regulatory mechanisms utilized to regulate diverse cellular processes. Malonylation of proteins, a reversible post-translational modification of lysine/k residues, is linked to a variety...

Multiple sequence alignment-based RNA language model and its application to structural inference.

Nucleic acids research
Compared with proteins, DNA and RNA are more difficult languages to interpret because four-letter coded DNA/RNA sequences have less information content than 20-letter coded protein sequences. While BERT (Bidirectional Encoder Representations from Tra...

MEG-PPIS: a fast protein-protein interaction site prediction method based on multi-scale graph information and equivariant graph neural network.

Bioinformatics (Oxford, England)
MOTIVATION: Protein-protein interaction sites (PPIS) are crucial for deciphering protein action mechanisms and related medical research, which is the key issue in protein action research. Recent studies have shown that graph neural networks have achi...

AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences.

Nucleic acids research
The AlphaFold Database Protein Structure Database (AlphaFold DB, https://alphafold.ebi.ac.uk) has significantly impacted structural biology by amassing over 214 million predicted protein structures, expanding from the initial 300k structures released...