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Research resources for tuberculosis:

TB Database: http://www.tbdb.org/ Tuberculosis (TB) is a public health challenge of paramount importance. Control of TB will require a multifaceted approach integrating efficient public health interventions with the discovery and use of new vaccines and drugs. TBDatabase (TBDB) makes available the tools and resources available at the Stanford Microarray Database and the Broad Institute. Anyone is welcome to access the published data available on the TBDB site without signing in. Some data in TBDB are unpublished and can therefore only be accessed by the authors and their collaborators after they sign in. The “Access Polices” page provides more information about TBDB accounts. A grant from the Bill & Melinda Gates Foundation has enabled us to create an integrated software platform for tuberculosis drug discovery and research. Learn more >

Tuberculist: http://tuberculist.epfl.ch/ The TubercuList knowledge base integrates genome details, protein information, drug and transcriptome data, mutant and operon annotation, bibliography, structural views and comparative genomics, in a structured manner required for the rational development of new diagnostic, therapeutic and prophylactic measures against tuberculosis. With the means of expert curation and continuous updates, we deliver a broad view of the Mycobacterium tuberculosis genome.

 

webTB.org:  http://www.webtb.org/ a resource for Mycobacterium tuberculosis researchers is brought to you by the TB Structural Genomics Consortium with lots of tools: Gene expression correlation display: This server presents the pair wise gene expression correlation for two or more genes. For a set of genes you can get all the pair wise correlations and express it as a matrix, graphically display it.Operon Search: Search for operons and directions in the TB genome. Known operons are listed by name. These data will be expanded as more sources are found. BLAST the TB genome: BLAST a sequence against the TB genome and other NCBI databases. Target Explorer: Target Explorer is intended to be an interactive web site that allows researchers in the Tuberculosis research community to experiment with different target selection criteria and explore alternative ways of prioritizing gene targets for experimentation (crystallization structure solution, high-throughput screening for inhibitor discovery, etc.) Mycobacterial Genome DataBase: The site is a database of genomes of mycobacterial strains sequenced in the lab of James C. Sacchettini at Texas A&M University. It provides access to sequence data (including coverage statistics) and comparison of polymorphisms among various strains of tuberculosis, with a focus on drug-resistance. The sequencing is done on an Illumina GenomeAnalyzer II (short reads). The data was analyzed using customized sequence-assembly methods written by Tom Ioerger and his group at Texas A&M. The Genome browser: Graphically scan the entire TB genome for information on each ORF with indications of any predicted operons and includes links back to the quick search page for more gene information ORF Progress search tool: Search the status and progress of MTb ORFs that are targeted and pursued by consortium members. Structure Gallery: See the protein structures determined by members of the consortium.Structure Summary pagesThis page is a front page portal to the structure information on known TB proteins. All other WebTB servers can be accessed from this page, including the Gallery and JMOL viewer. MTBreg Database: A database of proteins up- and down-regulated in Mycobacterium tuberculosis grown under conditions mimicking infection as well as information on proteins that are regulated by selected transcription factors or other regulatory proteins. TBDB Legacy Tools: Legacy tools from the former TBSGC site to search and browse the TB Genome

 

TBDreamDB : http://www.tbdreamdb.com/index.html Exciting news at TBDreamDB! The Database is currently undergoing complete redesign and data evaluation. The database will be converted to a fully searchable relational Database with a new look front end website as well. We hope to have the beta design up and running towards the end of 2011 early 2012. Any feedback would be great, simply contact us at the curator email below. Also please keep sending in any errors you find in the dataset. The data is being evaluated and corrected as it is being inserted into the new database format. -Your Emails are much appreciated!

 

Sanger Institute Welcome Trust: The Wellcome Trust and DEFRA has funded the Sanger Instiute to sequence reference genomes for Mycobacterium africanum http://www.sanger.ac.uk/resources/downloads/bacteria/mycobacterium.html Mycobacterium is a genus within the order Actinomycetales that comprises a large number of well characterised species, several of which are associated with human and animal disease such as tuberculosis and leprosy.

 

MGDD : http://mirna.jnu.ac.in/mgdd/index.html (Mycobacterial Genome Divergence Database) is a repository of genetic differences among different strains and species of organisms belonging to Mycobacterium tuberculosis complex. The differences are based on comparison of user chosen organisms. The query sequences are used to compare against subject sequences. The users can also choose the type of genetic divergence, that is, SNPs (Single Nucleotide Polymorphism), insertions, repeat expansion and divergent sequences that they are interested in. The results from a specific region (based on boundary defined by nucleotide sequence) or a specific gene can be displayed based on user’s choice. Presently, the database has precomputed analysis from three different fully sequenced genomes of this complex. These are Mycobacterium tuberculosis H37Rv, Mycobacterium tuberculosis CDC1551 and Mycobacterium bovis AF2122/97. In future it will be updated with more strains species as fully sequenced genomes become available.

 

MTBreg: http://www.doe-mbi.ucla.edu/Services/MTBreg/ Proteins up- and down- regulated in Mycobacterium tuberculosis grown under conditions mimicking infection are included in this database. It also includes information on proteins that are regulated by selected transcription factors or other regulatory proteins. The literature data provided here is complimentary to the databases provided by Michael Strong that include recent TB computational functional linkages and the Prolinks Database by Peter Bowers.

 
MycoperonDB:  http://cdfd.org.in/mycoperondb/home.html is a database of computationaly predicted operons and transcriptional units of Mycobacteria. MycoperonDB is setup to provide operon and trancriptional unit information of different mycobacterial species at one place. At present, this database covers five species from mycobacteria and consist of an insilico model of operon organization of 18,053 genes . The operon information provides a basis and a refenece for a comprehensive understanding of how the transcriptional control are encoded in genome. The database has a user friendly web interface which takes simple sequence, gene name or ORF ID as an input and reports the transcription unit and operon associated with the input query.

 

GenoMycDB Browser: http://157.86.176.108/~catanho/genomycdb/ Several databases and computational tools have been created with the aim of organizing, integrating and analyzing the wealth of information generated by large-scale sequencing projects of mycobacterial genomes and those of other organisms. However, with very few exceptions, these databases and tools do not allow for massive and/or dynamic comparison of these data. GenoMycDB (http://www.dbbm.fiocruz.br/GenoMycDB) is a relational database built for large-scale comparative analyses of completely sequenced mycobacterial genomes, based on their predicted protein content. Its central structure is composed of the results obtained after pair-wise sequence alignments among all the predicted proteins coded by the genomes of six mycobacteria: Mycobacterium tuberculosis (strains H37Rv and CDC1551), M. bovis AF2122/97, M. avium subsp. paratuberculosis K10, M. leprae TN, and M. smegmatis MC2 155. The database stores the computed similarity parameters of every aligned pair, providing for each protein sequence the predicted subcellular localization, the assigned cluster of orthologous groups, the features of the corresponding gene, and links to several important databases. Tables containing pairs or groups of potential homologs between selected species/strains can be produced dynamically by user-defined criteria, based on one or multiple sequence similarity parameters. In addition, searches can be restricted according to the predicted subcellular localization of the protein, the DNA strand of the corresponding gene and/or the description of the protein. Massive data search and/or retrieval are available, and different ways of exporting the result are offered. GenoMycDB provides an on-line resource for the functional classification of mycobacterial proteins as well as for the analysis of genome structure, organization, and evolution.

 

TB Drug Target Database: http://www.bioinformatics.org/tbdtdb/ TB Drug Target Database contains information on the antituberculer drugs and the target proteins for the treatment of TB. Informations are avilable on the drugs and other possible inhibitors including their Structural details, also the analysis made to the target proteins are made available.

 

MIRU-VNTRplus web application: http://www.miru-vntrplus.org/MIRU/index.faces Molecular typing of bacteria from the Mycobacterium tuberculosis complex (MTBC) is essential for epidemiological purposes such as investigating the spreading of specific genotypes. Recently, mycobacterial interspersed repetitive units (MIRU) typing has become an important method, as it allows high-throughput, discriminatory and reproducible analysis of clinical isolates. MIRU is a MTBC specific name of a multiple locus VNTR [variable number of tandem repeats] analysis (MLVA) bacterial typing scheme. Because of its portable data format, MIRU typing has the potential to be a versatile tool for individual strain identification based on large reference databases. However, specialized bioinformatic web tools to analyze MIRU data and public reference databases are not available. To meet this need, a collection of 186 strains representing the major MTBC lineages was used for implementing a web server, MIRU-VNTRplus (http://www.miru-vntrplus.org/). For each strain species, lineage, and epidemiologic information was stored together with copy numbers of 24 MIRU loci, spoligotyping patterns, regions of difference (RD) profiles, single nucleotide polymorphisms (SNPs), susceptibility data, and IS6110 RFLP fingerprint images. Via the freely accessible MIRU-VNTRplus service users can compare their strain(s) with the reference strains for the assignment of MTBC species, lineages, and genotypes. For easier scientific communication a universal expanding nomenclature (MLVA MtbC15-9) to name different MIRU genotypes is maintained at the server. Comparisons can be based on MIRU-, spoligo-, RD-, SNP-, susceptibility-typing data, or by a combination of different data types. Several distance coefficients are available, including Jaccard’s and categorical. Based upon the respective distance matrix, a dendrogram can be calculated using UPGMA or neighbor-joining clustering algorithms. The resulting trees may be exported in various data formats. MIRU-VNTRplus provides also functions for the user to analyze own strains without interrogating the reference database. Extensive documentation (manual and tutorials) of the service is available to make best use of all features.

 

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