Can I predict protein structures using this skill?

Yes, gget includes a module for AlphaFold2 structure prediction and can also retrieve existing structures and metadata from the PDB.

How does gget handle database updates?

gget modules are automatically tested on a biweekly basis and updated to ensure compatibility with changes in underlying database structures.

Does gget support single-cell RNA-seq data?

Yes, through the cellxgene module, gget can query the CZ CELLxGENE Discover Census for specific cell types, tissues, and gene expression data.

Which databases can gget access?

gget provides a unified interface for over 20 databases, including Ensembl, UniProt, NCBI, the Protein Data Bank (PDB), and ARCHS4.

Is gget suitable for large-scale batch processing?

gget is optimized for interactive exploration and quick lookups. For massive batch processing tasks, the tool recommends using Biopython or bioservices.

Bioinformatic Data Retrieval (gget)

Name: Bioinformatic Data Retrieval (gget)
Author: henriquescastilho

byhenriquescastilho

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Ciencia de Datos y ML

Queries over 20 genomic databases to provide instant access to gene information, sequence alignments, and protein structures.

gget is a specialized bioinformatics capability that provides a unified interface for accessing high-quality biological data from sources like Ensembl, UniProt, and NCBI. It enables developers and researchers to perform complex biological tasks—such as BLAST searches, AlphaFold protein structure predictions, and single-cell RNA-seq queries—directly through a consistent command-line or Pythonic interface. By automating the retrieval and formatting of genomic metadata, gget significantly accelerates the initial exploration phase of biological research and data pipeline development.

Características Principales

01Automated 3D protein structure prediction powered by AlphaFold2.

021 GitHub stars

03Unified access to 20+ bioinformatics databases including Ensembl, UniProt, and NCBI.

04Direct querying of single-cell RNA-seq data via CZ CELLxGENE Census.

05Integrated sequence alignment tools including BLAST, BLAT, and Muscle5.

06Fast retrieval of reference genome download links and gene metadata.

Casos de Uso

01Predicting protein structures and identifying eukaryotic linear motifs for structural biology research.

02Running sequence similarity searches and multiple sequence alignments for evolutionary analysis.

03Searching for gene functions, synonyms, and genomic locations across different species.

Características Principales

01Automated 3D protein structure prediction powered by AlphaFold2.

021 GitHub stars

03Unified access to 20+ bioinformatics databases including Ensembl, UniProt, and NCBI.

04Direct querying of single-cell RNA-seq data via CZ CELLxGENE Census.

05Integrated sequence alignment tools including BLAST, BLAT, and Muscle5.

06Fast retrieval of reference genome download links and gene metadata.

Casos de Uso

01Predicting protein structures and identifying eukaryotic linear motifs for structural biology research.

02Running sequence similarity searches and multiple sequence alignments for evolutionary analysis.

03Searching for gene functions, synonyms, and genomic locations across different species.