AGONOTES
AGONOTES annotates Argonaute (Ago) proteins across all domains of life by identifying and classifying Ago sequences and annotating their functional domains for comparative and functional analysis.
Key Features:
- Identification Across Domains: Classifies proteins into prokaryotic Argonaute (pAgo), eukaryotic Argonaute (eAgo), or non-Argonaute (non-Ago) categories.
- BLASTP similarity search: Performs initial protein categorization using the BLASTP algorithm.
- Multiple Sequence Alignment (MUSCLE): Aligns identified Argonaute proteins to a standard set of Ago sequences using MUSCLE for comparative analysis.
- Domain Annotation and Visualization: Curates functional domains from alignment results and generates visualizations using Bio::Graphic modules within the BioPerl bundle.
- Comparative Performance: Demonstrates superior domain annotation performance compared to CD-Search and UniProt.
Scientific Applications:
- Gene Regulation Studies: Supports investigation of Ago-mediated gene expression regulation in eukaryotes by providing detailed annotations.
- Prokaryotic Defense Mechanisms: Enables study of prokaryotic defense systems mediated by Ago proteins against foreign genomes.
- Genome Editing and Gene Silencing: Supports research on Ago-based genome editing and gene silencing applications.
Methodology:
Uses BLASTP for initial protein categorization, MUSCLE for multiple sequence alignment against a standard Ago sequence set, and performs domain curation and visualization via Bio::Graphic modules within the BioPerl bundle.
Topics
Details
- Added:
- 1/14/2020
- Last Updated:
- 12/1/2020
Operations
Publications
Jiang L, Yu M, Zhou Y, Tang Z, Li N, Kang J, He B, Huang J. AGONOTES: A Robot Annotator for Argonaute Proteins. Interdisciplinary Sciences: Computational Life Sciences. 2019;12(1):109-116. doi:10.1007/s12539-019-00349-4. PMID:31741225.
PMID: 31741225
Funding: - National Natural Science Foundation of China: 61571095
- Fundamental Research Funds for the Central Universities: ZYGX2015Z006
- China Postdoctoral Science Foundation: 2019M653369
- Sichuan Province Science and Technology Support Program: 2018HH0154