AIMC Topic: Proteins

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UPCLASS: a deep learning-based classifier for UniProtKB entry publications.

Database : the journal of biological databases and curation
In the UniProt Knowledgebase (UniProtKB), publications providing evidence for a specific protein annotation entry are organized across different categories, such as function, interaction and expression, based on the type of data they contain. To prov...

Recognizing Proteins with Binding Function in Elymus nutans Based on Machine Learning Methods.

Combinatorial chemistry & high throughput screening
BACKGROUND: We research the binding function proteins in Elymus nutans. Recognition for proteins is essential for study of biology. Machine learning methods have been widely used for the prediction of proteins.

Antioxidant Proteins' Identification Based on Support Vector Machine.

Combinatorial chemistry & high throughput screening
BACKGROUND: Evidence have increasingly indicated that for human disease, cell metabolism are deeply associated with proteins. Structural mutations and dysregulations of these proteins contribute to the development of the complex disease. Free radical...

Automated sample preparation with SP3 for low-input clinical proteomics.

Molecular systems biology
High-throughput and streamlined workflows are essential in clinical proteomics for standardized processing of samples from a variety of sources, including fresh-frozen tissue, FFPE tissue, or blood. To reach this goal, we have implemented single-pot ...

Computational Models for Self-Interacting Proteins Prediction.

Protein and peptide letters
Self-Interacting Proteins (SIPs), whose two or more copies can interact with each other, have significant roles in cellular functions and evolution of Protein Interaction Networks (PINs). Knowing whether a protein can act on itself is important to un...

Recent Advances on the Semi-Supervised Learning for Long Non-Coding RNA-Protein Interactions Prediction: A Review.

Protein and peptide letters
In recent years, more and more evidence indicates that long non-coding RNA (lncRNA) plays a significant role in the development of complex biological processes, especially in RNA progressing, chromatin modification, and cell differentiation, as well ...

A Web-Based Protocol for Interprotein Contact Prediction by Deep Learning.

Methods in molecular biology (Clifton, N.J.)
Identifying residue-residue contacts in protein-protein interactions or complex is crucial for understanding protein and cell functions. DCA (direct-coupling analysis) methods shed some light on this, but they need many sequence homologs to yield acc...

Deep Learning in the Study of Protein-Related Interactions.

Protein and peptide letters
Protein-related interaction prediction is critical to understanding life processes, biological functions, and mechanisms of drug action. Experimental methods used to determine proteinrelated interactions have always been costly and inefficient. In re...

Deep learning on chaos game representation for proteins.

Bioinformatics (Oxford, England)
MOTIVATION: Classification of protein sequences is one big task in bioinformatics and has many applications. Different machine learning methods exist and are applied on these problems, such as support vector machines (SVM), random forests (RF) and ne...