FindTargetsWeb: This application automates the process of identification of fragile genes on genome-scale metabolic networks using Flux Balance Analysis (FBA), Flux Variability Analysis (FVA) and queries to several public repositories, such as KEGG, Uniprot and Drugbank.
This web application was developed in Python using CobraPy and Django 1.11.
Input: A SBML (level 3) file describing the genome-scale metabolic network.
Output: Spreadsheets listing potential therapeutic targets and related drugs. The files are sent to the e-mail address informed by the user.
Availability: The system is available at http://pseudomonas.procc.fiocruz.br/FindTargetsWEB
CurSystem: This application supports the curation of Biological Networks by experts in a decentralized way. It proposes the analysis of networks gaps through challenges. Each challenge receives answers and comments, helping the responsible for the challenge to reach conclusions and eventually solve it. CurSystem is currently being used to curate the Gene Transcription Network and the Metabolic Network of Pseudomonas aeruginosa CCBH4851.
This web application was developed in Java EE using JSF, JPA and Primefaces.
Input: A set of challenges defined by the team responsible for the reconstruction of a biological network.
Output: Answers to challenges provided by experts. The experts can be geographically distributed, and can answer challenges according to his/her convenience.
Availability: The system is available at http://pseudomonas.procc.fiocruz.br:8185/CurSystem
NetGEN: This application is a tool to perform reconstructions of metabolic networks of bacteria. It proposes an assisted methodology where the user starts from a genomic annotation in GBK format. The system also requires for the reconstruction process the metabolic network of a reference organism. NetGEN is currently being used for the reconstruction of the metabolic network of Pseudomonas aeruginosa CCBH4851.
This web application was developed in Java EE using JSF, JPA, Primefaces, BioJava, Jsoup and MySQL.
Input: A genomic annotation in GBK (GenBank File) format.
Output: Metabolic Network Model in Systems Biology Markup Language (SBML) format.