AIMC Topic: Databases, Protein

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Redundancy-weighting the PDB for detailed secondary structure prediction using deep-learning models.

Bioinformatics (Oxford, England)
MOTIVATION: The Protein Data Bank (PDB), the ultimate source for data in structural biology, is inherently imbalanced. To alleviate biases, virtually all structural biology studies use nonredundant (NR) subsets of the PDB, which include only a fracti...

The neXtProt knowledgebase in 2020: data, tools and usability improvements.

Nucleic acids research
The neXtProt knowledgebase (https://www.nextprot.org) is an integrative resource providing both data on human protein and the tools to explore these. In order to provide comprehensive and up-to-date data, we evaluate and add new data sets. We describ...

VacPred: Sequence-based prediction of plant vacuole proteins using machine-learning techniques.

Journal of biosciences
Subcellular localization prediction of the proteome is one of major goals of large-scale genome or proteome sequencing projects to define the gene functions that could be possible with the help of computational modeling techniques. Previously, differ...

A Coordinated Approach by Public Domain Bioinformatics Resources to Aid the Fight Against Alzheimer's Disease Through Expert Curation of Key Protein Targets.

Journal of Alzheimer's disease : JAD
BACKGROUND: The analysis and interpretation of data generated from patient-derived clinical samples relies on access to high-quality bioinformatics resources. These are maintained and updated by expert curators extracting knowledge from unstructured ...

Identification of Cancer Biomarkers in Human Body Fluids by Using Enhanced Physicochemical-incorporated Evolutionary Conservation Scheme.

Current topics in medicinal chemistry
OBJECTIVE: Cancer is one of the most serious diseases affecting human health. Among all current cancer treatments, early diagnosis and control significantly help increase the chances of cure. Detecting cancer biomarkers in body fluids now is attracti...

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...

Methods of Computational Interactomics for Investigating Interactions of Human Proteoforms.

Biochemistry. Biokhimiia
Human genome contains ca. 20,000 protein-coding genes that could be translated into millions of unique protein species (proteoforms). Proteoforms coded by a single gene often have different functions, which implies different protein partners. By inte...

Evolution of Machine Learning Algorithms in the Prediction and Design of Anticancer Peptides.

Current protein & peptide science
Peptides act as promising anticancer agents due to their ease of synthesis and modifications, enhanced tumor penetration, and less systemic toxicity. However, only limited success has been achieved so far, as experimental design and synthesis of anti...