ProtozoaDB 2.0: A Trypanosoma Brucei Case Study

Over the last decade new species of Protozoa have been sequenced and deposited in GenBank. Analyzing large amounts of genomic data, especially using Next Generation Sequencing (NGS), is not a trivial task, considering that researchers used to deal or focus their studies on few genes or gene families...

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Main Authors: Rodrigo Jardim, Diogo Tschoeke, Alberto M. R. Dávila
Format: Article
Language:English
Published: MDPI AG 2017-07-01
Series:Pathogens
Subjects:
Online Access:https://www.mdpi.com/2076-0817/6/3/32
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spelling doaj-bd79218494f6431a9cc90e4cf65920bc2020-11-24T22:52:29ZengMDPI AGPathogens2076-08172017-07-01633210.3390/pathogens6030032pathogens6030032ProtozoaDB 2.0: A Trypanosoma Brucei Case StudyRodrigo Jardim0Diogo Tschoeke1Alberto M. R. Dávila2Computational and Systems Biology Laboratory, Oswaldo Cruz Institute, Fiocruz, Rio de Janeiro 21040-900, BrazilMicrobiology Laboratory, Rio de Janeiro Federal University, Rio de Janeiro 21941-901, BrazilComputational and Systems Biology Laboratory, Oswaldo Cruz Institute, Fiocruz, Rio de Janeiro 21040-900, BrazilOver the last decade new species of Protozoa have been sequenced and deposited in GenBank. Analyzing large amounts of genomic data, especially using Next Generation Sequencing (NGS), is not a trivial task, considering that researchers used to deal or focus their studies on few genes or gene families or even small genomes. To facilitate the information extraction process from genomic data, we developed a database system called ProtozoaDB that included five genomes of Protozoa in its first version. In the present study, we present a new version of ProtozoaDB called ProtozoaDB 2.0, now with the genomes of 22 pathogenic Protozoa. The system has been fully remodeled to allow for new tools and a more expanded view of data, and now includes a number of analyses such as: (i) similarities with other databases (model organisms, the Conserved Domains Database, and the Protein Data Bank); (ii) visualization of KEGG metabolic pathways; (iii) the protein structure from PDB; (iv) homology inferences; (v) the search for related publications in PubMed; (vi) superfamily classification; and (vii) phenotype inferences based on comparisons with model organisms. ProtozoaDB 2.0 supports RESTful Web Services to make data access easier. Those services were written in Ruby language using Ruby on Rails (RoR). This new version also allows a more detailed analysis of the object of study, as well as expanding the number of genomes and proteomes available to the scientific community. In our case study, a group of prenyltransferase proteinsalready described in the literature was found to be a good drug target for Trypanosomatids.https://www.mdpi.com/2076-0817/6/3/32protozoainformation extractionTrypanosoma bruceitrypanosomatidsProtozoaDB
collection DOAJ
language English
format Article
sources DOAJ
author Rodrigo Jardim
Diogo Tschoeke
Alberto M. R. Dávila
spellingShingle Rodrigo Jardim
Diogo Tschoeke
Alberto M. R. Dávila
ProtozoaDB 2.0: A Trypanosoma Brucei Case Study
Pathogens
protozoa
information extraction
Trypanosoma brucei
trypanosomatids
ProtozoaDB
author_facet Rodrigo Jardim
Diogo Tschoeke
Alberto M. R. Dávila
author_sort Rodrigo Jardim
title ProtozoaDB 2.0: A Trypanosoma Brucei Case Study
title_short ProtozoaDB 2.0: A Trypanosoma Brucei Case Study
title_full ProtozoaDB 2.0: A Trypanosoma Brucei Case Study
title_fullStr ProtozoaDB 2.0: A Trypanosoma Brucei Case Study
title_full_unstemmed ProtozoaDB 2.0: A Trypanosoma Brucei Case Study
title_sort protozoadb 2.0: a trypanosoma brucei case study
publisher MDPI AG
series Pathogens
issn 2076-0817
publishDate 2017-07-01
description Over the last decade new species of Protozoa have been sequenced and deposited in GenBank. Analyzing large amounts of genomic data, especially using Next Generation Sequencing (NGS), is not a trivial task, considering that researchers used to deal or focus their studies on few genes or gene families or even small genomes. To facilitate the information extraction process from genomic data, we developed a database system called ProtozoaDB that included five genomes of Protozoa in its first version. In the present study, we present a new version of ProtozoaDB called ProtozoaDB 2.0, now with the genomes of 22 pathogenic Protozoa. The system has been fully remodeled to allow for new tools and a more expanded view of data, and now includes a number of analyses such as: (i) similarities with other databases (model organisms, the Conserved Domains Database, and the Protein Data Bank); (ii) visualization of KEGG metabolic pathways; (iii) the protein structure from PDB; (iv) homology inferences; (v) the search for related publications in PubMed; (vi) superfamily classification; and (vii) phenotype inferences based on comparisons with model organisms. ProtozoaDB 2.0 supports RESTful Web Services to make data access easier. Those services were written in Ruby language using Ruby on Rails (RoR). This new version also allows a more detailed analysis of the object of study, as well as expanding the number of genomes and proteomes available to the scientific community. In our case study, a group of prenyltransferase proteinsalready described in the literature was found to be a good drug target for Trypanosomatids.
topic protozoa
information extraction
Trypanosoma brucei
trypanosomatids
ProtozoaDB
url https://www.mdpi.com/2076-0817/6/3/32
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