AIMC Topic: Proteins

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Application of deep learning methods in biological networks.

Briefings in bioinformatics
The increase in biological data and the formation of various biomolecule interaction databases enable us to obtain diverse biological networks. These biological networks provide a wealth of raw materials for further understanding of biological system...

GPS-Palm: a deep learning-based graphic presentation system for the prediction of S-palmitoylation sites in proteins.

Briefings in bioinformatics
As an important reversible lipid modification, S-palmitoylation mainly occurs at specific cysteine residues in proteins, participates in regulating various biological processes and is associated with human diseases. Besides experimental assays, compu...

Protein sequence design by conformational landscape optimization.

Proceedings of the National Academy of Sciences of the United States of America
The protein design problem is to identify an amino acid sequence that folds to a desired structure. Given Anfinsen's thermodynamic hypothesis of folding, this can be recast as finding an amino acid sequence for which the desired structure is the lowe...

Sequence representation approaches for sequence-based protein prediction tasks that use deep learning.

Briefings in functional genomics
Deep learning has been increasingly used in bioinformatics, especially in sequence-based protein prediction tasks, as large amounts of biological data are available and deep learning techniques have been developed rapidly in recent years. For sequenc...

Prediction of bio-sequence modifications and the associations with diseases.

Briefings in functional genomics
Modifications of protein, RNA and DNA play an important role in many biological processes and are related to some diseases. Therefore, accurate identification and comprehensive understanding of protein, RNA and DNA modification sites can promote rese...

MB-GAN: Microbiome Simulation via Generative Adversarial Network.

GigaScience
BACKGROUND: Trillions of microbes inhabit the human body and have a profound effect on human health. The recent development of metagenome-wide association studies and other quantitative analysis methods accelerate the discovery of the associations be...

ToxDL: deep learning using primary structure and domain embeddings for assessing protein toxicity.

Bioinformatics (Oxford, England)
MOTIVATION: Genetically engineering food crops involves introducing proteins from other species into crop plant species or modifying already existing proteins with gene editing techniques. In addition, newly synthesized proteins can be used as therap...

FireProtDB: database of manually curated protein stability data.

Nucleic acids research
The majority of naturally occurring proteins have evolved to function under mild conditions inside the living organisms. One of the critical obstacles for the use of proteins in biotechnological applications is their insufficient stability at elevate...

Deep Learning for Protein-Protein Interaction Site Prediction.

Methods in molecular biology (Clifton, N.J.)
Protein-protein interactions (PPIs) are central to cellular functions. Experimental methods for predicting PPIs are well developed but are time and resource expensive and suffer from high false-positive error rates at scale. Computational prediction ...

Machine and Deep Learning for Prediction of Subcellular Localization.

Methods in molecular biology (Clifton, N.J.)
Protein subcellular localization prediction (PSLP), which plays an important role in the field of computational biology, identifies the position and function of proteins in cells without expensive cost and laborious effort. In the past few decades, v...