UPIMAPI

UPIMAPI performs sequence homology-based annotation of omics and meta-omics datasets by aligning input sequences to UniProtKB to derive functional information for microbial function exploration.


Key Features:

  • Sequence homology-based annotation: Aligns input sequences to UniProtKB entries to infer functional annotations from homologous proteins.
  • Integration with UniProtKB: Extracts protein names, Enzyme Commission (EC) numbers, Gene Ontology (GO) terms, taxonomy data, and cross-references to external databases from UniProtKB entries.
  • Scalability for omics and meta-omics datasets: Processes large-scale metagenomic, metatranscriptomic, and metaproteomic sequence files for comprehensive annotation.

Scientific Applications:

  • Metagenomics annotation: Provides functional annotation of metagenomic sequences via homology to UniProtKB entries.
  • Metatranscriptomics annotation: Enables assignment of functional terms to metatranscriptomic sequences using UniProtKB-derived annotations.
  • Metaproteomics annotation: Facilitates mapping of peptide or protein sequences from metaproteomics datasets to UniProtKB functions.
  • Microbial functional interpretation: Supports interpretation of microbial activities in natural environments and biotechnological processes through comprehensive functional annotations.

Methodology:

Aligns input sequences against UniProtKB entries using sequence homology to derive functional annotations and extract protein names, EC numbers, GO terms, taxonomy data, and cross-references.

Topics

Details

License:
BSD-3-Clause
Maturity:
Emerging
Cost:
Free of charge
Tool Type:
command-line tool
Operating Systems:
Mac, Linux
Programming Languages:
Python
Added:
4/27/2021
Last Updated:
11/24/2024

Operations

Data Inputs & Outputs

Gene functional annotation

Publications

Sequeira JC, Rocha M, Alves MM, Salvador AF. UPIMAPI, reCOGnizer and KEGGCharter: Bioinformatics tools for functional annotation and visualization of (meta)-omics datasets. Computational and Structural Biotechnology Journal. 2022;20:1798-1810. doi:10.1016/j.csbj.2022.03.042. PMID:35495109. PMCID:PMC9034014.

PMID: 35495109
PMCID: PMC9034014
Funding: - Fundação para a Ciência e a Tecnologia: SFRH/BD/147271/2019, UIDB/04469/2020 - Horizon 2020: 952908

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