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  • Systems Biology - comprehensive data and models for the MTB Regulatory and Metabolic networks
  • Gene Expression Publications: Search and browse publications with gene expression data that are stored in TBDB.
  • Samples and Conditions:
    Search for a gene over all published samples and explore the expression significance of the indicated gene.
  • My Repository (sign in required): Access your saved microarray data sets for further analysis.
  • Download - download data files for sequence and annotation
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    The following publications describe the data provided on this site.

    • Galagan, J.E., Minch, K., Peterson, M., Lyubetskaya, A., Azizi, E., Sweet, L., Gomes, A., Rustad, T., Dolganov, G., Glotova, I., Abeel, T., Mahwinney, C., Kennedy, A.D., Allard, R., Brabant, W., Krueger, A., Jaini, S., Honda, B., Yu, W.H., Hickey, M.J., Zucker, J., Garay, C., Weiner, B., Sisk, P., Stolte, C., Winkler, J.K., Van de Peer, Y., Iazzetti, P., Camacho, D., Dreyfuss, J., Liu, Y., Dorhoi, A., Mollenkopf, H.J., Drogaris, P., Lamontagne, J., Zhou, Y., Piquenot, J., Park, S.T., Raman, S., Kaufmann, S.H., Mohney, R.P., Chelsky, D., Moody, D.B., Sherman, D.R., Schoolnik, G.K. (2013) The Mycobacterium tuberculosis regulatory network and hypoxia. Nature.499(7457):178-83
    • Galagan, J., Lyubetskaya, A., Gomes, A. (2013) ChIP-Seq and the Complexity of Bacterial Transcriptional Regulation. Current topics in microbiology and immunology.363:43-68
    • Jaini, S., Lyubetskaya, A., Gomes, A., Peterson, M., Park, S.T., Raman, S., Schoolnik, G., Galagan, J.E. Transcription Factor Binding Site Mapping Using ChIP-Seq. In: Hatfull G, Jacobs WR, Jr., editors. Molecular Genetics of Mycobacteria, 2nd Edition: ASM Press; In Press.

    Use of these data should include the following acknowledgement:

    Data used was generated in whole or in part with Federal funds fromthe National Institute of Allergy and Infectious DiseasesNational Institute of Health, Department of Health and Human Services, under contract no. HHSN272200800059C

    Coverage data for individual TFs are provided as both wig files and tdf files.

    A file with all predicted binding sites is available (right click to save). See this help page for information about binding sites

    A file with all predicted interactions is available (right click to save). See this help page for information about interactions

    Expression data following TF induction has been deposited in GEO under accession GSE43466

    We have developed a number of software packages for data analysis.


    CSDeconv is a computational method that determines the locations of transcription factor binding from ChIP-seq data. CSDeconv differs from prior methods in that it uses a blind deconvolution approach that allows multiple closely-spaced binding sites within a single promoter region to be called accurately. The method is described in Lun et al. (2009) .  The source code is available here .


    GenomeView is a stand-alone genome editor and viewer that provides fast and dynamic visualization of aligned short read data, genome sequences and annotations, and genome alignments.  GenomeView allows users to load .bam files directly or through a URL.  GenomeView was developed by a visiting graduate student in the Galagan lab,  Thomas Abeel from Ghent University . It can be accessed and downloaded from its sourceforge page


    E-Flux is novel method for modeling metabolic states using whole cell measurements of gene expression.  The method extends the technique of Flux Balance Analysis (FBA) by modeling maximum flux constraints as a function of measured gene expression. The method is described in Colijn et al. (2009).

    Experimental and computational protocols.

    The following protocols are currently available:
    (right-click on the links and choose "Save as..." to download the files)

    In Vivo Culture Core

    In Vitro Culture Core





    • Protocol 1: Processing of Extracted Proteins
    • Protocol 2: Protein Extraction from MTB by Bead Beating
    • Protocol 3: Subcellular Fractionation of MTB Proteins
    • Protocol 4: Protein Extraction for Secreted Proteome Analysis
    • Protocol 5: Processing of Culture Filtrate for Secreted Proteome Analysis by Size Fractionation
    • Protocol 6: Fractionation of Tryptic Digests of Extracted mTb Proteins/Peptides by Basic pH Reverse Phase Separation Method
    • Protocol 7: Enrichment of Glycopeptides from Tryptic Mtb Digests

    We use variety of third party software applications, publically available resources, and experimental methods.

    Third Party Software


    The Context Likelihood of Relatedness (CLR) algorithm is an extension of the relevance networks approach for identifying transcriptional regulatory interactions using gene expression data. The algorithm, developed by the lab of Tim Gardner, compares the mutual information between a transcription factor/gene pair to the background distribution of mutual information scores for all possible transcription factor/gene pairs that include either the transcription factor or its target. The algorithm is described in Faith et al. (2007) .



    BioTapestry is an interactive tool for building, visualizing, and simulating genetic regulatory networks. BioTapestry was developed as a joint effort between the Bolouri Lab at the Institute for Systems Biology and the Davidson Lab at Caltech The tool provides a circuit diagram layout of genetic regulatory networks using a list of genetic interactions that can be manually our automatically generated. The software and example data sets can be downloaded here.


    Cytoscape is a publically available open source software application for visualizing molecular interaction networks and integrating state information on the network. Cytoscape provides a general and flexible view of networks based on any type of underlying set of components and interactions, and is thus a standard tool for the initial visual interrogation of complex interaction maps.  The software is available here.