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Proteinortho : Detection of (Co-)orthologs in large-scale analysis

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TLDR
Proteinortho significantly reduces the required amount of memory for orthology analysis compared to existing tools, allowing such computations to be performed on off-the-shelf hardware.
Abstract
Orthology analysis is an important part of data analysis in many areas of bioinformatics such as comparative genomics and molecular phylogenetics. The ever-increasing flood of sequence data, and hence the rapidly increasing number of genomes that can be compared simultaneously, calls for efficient software tools as brute-force approaches with quadratic memory requirements become infeasible in practise. The rapid pace at which new data become available, furthermore, makes it desirable to compute genome-wide orthology relations for a given dataset rather than relying on relations listed in databases. The program Proteinortho described here is a stand-alone tool that is geared towards large datasets and makes use of distributed computing techniques when run on multi-core hardware. It implements an extended version of the reciprocal best alignment heuristic. We apply Proteinortho to compute orthologous proteins in the complete set of all 717 eubacterial genomes available at NCBI at the beginning of 2009. We identified thirty proteins present in 99% of all bacterial proteomes. Proteinortho significantly reduces the required amount of memory for orthology analysis compared to existing tools, allowing such computations to be performed on off-the-shelf hardware.

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OrthoVenn: a web server for genome wide comparison and annotation of orthologous clusters across multiple species

TL;DR: A web platform named OrthoVenn that is useful for genome wide comparisons and visualization of orthologous clusters and allows for a customized search of clusters of specific genes through key words or BLAST is reported.
Journal ArticleDOI

Genomic characterization of the uncultured Bacteroidales family S24-7 inhabiting the guts of homeothermic animals

TL;DR: The first whole genome exploration of the Bacteroidales family S24-7 is provided, for which the name “Candidatus Homeothermaceae” is proposed, using 30 population genomes extracted from fecal samples of four different animal hosts.
Journal ArticleDOI

Comparative genomics reveals high biological diversity and specific adaptations in the industrially and medically important fungal genus Aspergillus

Ronald P. de Vries, +132 more
- 14 Feb 2017 - 
TL;DR: In this article, a comparative genomics and experimental study of the aspergilli genus is presented, which allows for the first time a genus-wide view of the biological diversity of the Aspergillus and in many, but not all, cases linked genome differences to phenotype.
References
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Journal ArticleDOI

Database resources of the National Center for Biotechnology Information

TL;DR: In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI’s website.
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SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB

TL;DR: SILVA (from Latin silva, forest), was implemented to provide a central comprehensive web resource for up to date, quality controlled databases of aligned rRNA sequences from the Bacteria, Archaea and Eukarya domains.
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OrthoMCL: identification of ortholog groups for eukaryotic genomes.

TL;DR: OrthoMCL provides a scalable method for constructing orthologous groups across multiple eukaryotic taxa, using a Markov Cluster algorithm to group (putative) orthologs and paralogs.
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The Universal Protein Resource (UniProt)

TL;DR: During 2004, tens of thousands of Knowledgebase records got manually annotated or updated; the UniProt keyword list got augmented by additional keywords; the documentation of the keywords and are continuously overhauling and standardizing the annotation of post-translational modifications.
Journal ArticleDOI

An iteration method for the solution of the eigenvalue problem of linear differential and integral operators

TL;DR: In this article, a systematic method for finding the latent roots and principal axes of a matrix, without reducing the order of the matrix, has been proposed, which is characterized by a wide field of applicability and great accuracy, since the accumulation of rounding errors is avoided, through the process of minimized iterations.
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