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A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

CABRA: Cluster and Annotate Blast Results Algorithm.

Pablo Mier^1,2, Miguel A Andrade-Navarro^3,4

¹Faculty of Biology, JGU Mainz, Gresemundweg, 2, 55128, Mainz, Germany. munoz@uni-mainz.com.

BMC Research Notes

|May 1, 2016

Summary

This summary is machine-generated.

This study introduces the Cluster and Annotate Blast Results Algorithm (CABRA), a web tool simplifying the analysis of large BLAST search results. CABRA clusters and annotates homologous sequences, offering a clearer overview for researchers.

Keywords:

BLAST search Clustering Computational biology Web tool

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Basic Local Alignment Search Tool (BLAST) searches are crucial for identifying homologous sequences and annotating proteins.
The expanding size of protein databases presents challenges in reviewing extensive BLAST search results.

Purpose of the Study:

To develop a novel web tool for efficient analysis of large-scale BLAST results.
To provide a streamlined method for functional evaluation of protein similarity searches.

Main Methods:

Developed the Cluster and Annotate Blast Results Algorithm (CABRA) web tool.
Integrated rapid BLAST searching against updated reference proteomes.
Implemented clustering of BLAST hits and annotation of these clusters for functional evaluation.

Main Results:

CABRA facilitates rapid BLAST searches across diverse and updated proteomes.
The tool enables functional evaluation through clustering and annotation of search results.
Provides a user-friendly interface for iterative modification of annotation clusters.

Conclusions:

CABRA simplifies the interpretation of BLAST search outcomes.
Offers a consolidated overview of annotations organized into manageable, user-adjustable clusters.
Enhances the efficiency of analyzing homologous sequences in large biological datasets.