TRANSPATH

 

 
TRANSPATH® is a database of mammalian signal transduction and metabolic pathways. As one of the earliest pathway databases ever created, it has grown since to the remarkable volume of more than 458,000 manually curated reactions. One of the largest pathway databases available, optimally suited for geneXplain’s proprietary Upstream Analysis
 
Its contents can be used for pathway analysis with the geneXplain platform, requiring separate licensing (see below).

Structure

Reaction hierarchy in the TRANSPATH® database of molecular pathways.

Reaction hierarchy in the TRANSPATH® database on molecular pathways. (Click image for an enlarged view.)

TRANSPATH organizes the information about genes/molecules and reactions according to multiple hierarchies. Its sophisticated structure makes it one of the scientifically best conceptualized pathway resources, suitable for multi-purpose uses. It is complemented by one of the richest corpora of pathway data available among all public domain and commercial sources, all manually curated by experts.

Individual reactions are documented with all experimental details, in a strictly mechanistic way that includes all reaction partners and the taxonomic origin of each molecule as reported in the published experiment (“molecular evidence level”). All evidences for a certain pathway step are accumulated to provide a more comprehensive and complete picture (“pathway step level”). On top, a semantic view is provided, which focuses on the key components only and omits mechanistic details as well as small abundant molecules (“semantic projection”). Complete networks and pathways are built from molecules and their reactions.

To consider the heterogeneity of information given in the original publications, TRANSPATH transparently but precisely differentiates protein molecules according to:

    • their relatedness within one genome
      Information can be specifically retrieved regarding:

(a) specific individual proteins,

(b) all products of a certain gene (isoforms),

(c) different family relation levels (e.g., paralogs);

 

    • their relatedness between different genomes (orthology)

 

  • their association and modification status

(a) protein complexes are specified with their exact composition;

(b) post-translational modifications are given with their exact positions in the protein.

TGFbeta network

Visualization of a part of the TGFbeta network with the geneXplain platform; data were retrieved from the TRANSPATH® database. The one molecule of the displayed network that is not genome-encoded (PtdIns(3)P), phosphatidylinositol 3-phosphate) is shown in purple.

Visualization of the TGFbeta network with the geneXplain platform; data were retrieved from the TRANSPATH® database. (Click image to enlarge the picture.)

Key features

Information about pathways
More than 298,000 molecules and more than 80,000 genes involved in signaling or metabolic pathways of mammals (mostly human, mouse, rat), gathered by manual expert curation.
More than one million reactions
Extracted from original scientific literature and evaluated by experts.
Experimentally verified
About 1720 experimentally verified and annotated pathways and chains.
Transcription factor – site interactions
More than 98,000, manually annotated and quality-checked.
Peer-reviewed scientific publications
More than 72,000 publications evaluated.
Pathway visualization tool
Highly customizable view of pathways and networks under the geneXplain platform.

Benefits

Quickly access information
About signal transduction and metabolic pathway components and their reactions without tedious and time consuming literature searches.
Predict potential pathways
Targeting the genes of your interest.
Build customized regulatory and metabolic networks
With more than one million reactions extracted from original scientific literature and evaluated by experts.
Use network visualization
With advanced TRANSPATH®-based technology of the geneXplain platform.

Pathway analysis

Get a picture of TRANSPATH®

Pathway analysis and network visualization with the geneXplain platform using the TRANSPATH® database.

Pathway analysis and network visualization with the geneXplain platform using the TRANSPATH® database. (Click image to enlarge the picture.)

Learn more about pathway analysis with the geneXplain platform.

Recent applications

Selection of articles reporting about TRANSPATH applications:
  • Rajavel A., Klees S., Hui Y., Schmitt A.O., Gültas M. (2022) Deciphering the Molecular Mechanism Underlying African Animal Trypanosomiasis by Means of the 1000 Bull Genomes Project Genomic Dataset. Biology (Basel). 11(5), 742. Link
  • Menck K., Wlochowitz D., Wachter A., Conradi L.C., Wolff A., Scheel A.H., Korf U., Wiemann S., Schildhaus H.U., Bohnenberger H., Wingender E., Pukrop T., Homayounfar K., Beißbarth T., Bleckmann A. (2022) High-Throughput Profiling of Colorectal Cancer Liver Metastases Reveals Intra- and Inter-Patient Heterogeneity in the EGFR and WNT Pathways Associated with Clinical Outcome. Cancers 14(9), 2084. Link
  • Benjamin, S.J., Hawley, K.L., Vera-Licona, P., La Vake, C.J., Cervantes, J.L., Ruan, Y., Radolf, J.D., Salazar, J.C. (2021) Macrophage mediated recognition and clearance of Borrelia burgdorferi elicits MyD88-dependent and -independent phagosomal signals that contribute to phagocytosis and inflammation. BMC Immunol. 22, 32. Link
  • Ivanov, S., Filimonov, D., & Tarasova, O. (2021). A computational analysis of transcriptional profiles from CD8(+) T lymphocytes reveals potential mechanisms of HIV/AIDS control and progression. Comput Struct Biotechnol J. 19, 2447–2459. Link
  • Meier, T., Timm, M., Montani, M., Wilkens, L. (2021) Gene networks and transcriptional regulators associated with liver cancer development and progression. BMC Med. Genomics 14, 41. Link
  • Ramzan, F., Klees, S., Schmitt, A. O., Cavero, D., & Gültas, M. (2020). Identification of Age-Specific and Common Key Regulatory Mechanisms Governing Eggshell Strength in Chicken Using Random Forests. Genes (Basel). 11(4), 464. Link
  • Ayyildiz D., Antoniali G., D’Ambrosio C., Mangiapane G., Dalla E., Scaloni A., Tell G., Piazza S. (2020) Architecture of The Human Ape1 Interactome Defines Novel Cancers Signatures. Sci Rep. 10, 28. Link
  • Mekonnen, Y.A., Gültas, M., Effa, K., Hanotte, O., Schmitt, A.O. (2019) Identification of Candidate Signature Genes and Key Regulators Associated With Trypanotolerance in the Sheko Breed. Front. Genet. 10, 1095. Link
  • Nobis, C. C., Dubeau Laramée, G., Kervezee, L., Maurice De Sousa, D., Labrecque, N., & Cermakian, N. (2019). The circadian clock of CD8 T cells modulates their early response to vaccination and the rhythmicity of related signaling pathways. Proc Natl Acad Sci U S A. 116(40), 20077–20086. Link
  • Malusa, F., Taranta, M., Zaki, N., Cinti, C., & Capobianco, E. (2015). Time-course gene profiling and networks in demethylated retinoblastoma cell line. Oncotarget. 6(27), 23688–23707. Link
  • Kutumova EO, Kiselev IN, Sharipov RN, Lavrik IN, Kolpakov FA. A modular model of the apoptosis machinery. Adv Exp Med Biol. 736, 235-45. Link
  • Schuler, M., Keller, A., Backes, C., Philippar, K., Lenhof, H. P., & Bauer, P. (2011). Transcriptome analysis by GeneTrail revealed regulation of functional categories in response to alterations of iron homeostasis in Arabidopsis thaliana. BMC Plant Biol. 11, 87. Link
  • Chiu SC, Tsao SW, Hwang PI, Vanisree S, Chen YA, Yang NS. Differential functional genomic effects of anti-inflammatory phytocompounds on immune signaling. BMC Genomics. 11, 513. Link

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    Current TRANSPATH® release

    TRANSPATH® release 2022.1

    The TRANSPATH® database on mammalian signal transduction and metabolic pathways contains these new data features:

    • Increase in number of reactions

    57,268 new binding reactions from recent publications between proteins in human and mouse have been added, among them e.g. from the brain and kidney interactome.

    •  Update of links to Wikipathways and Reactome

    Links from genes/proteins to the pathway databases Wikipathways (20220110) and Reactome (v78) have been updated.

    24,118 new binding reactions from recent publications between proteins in human have been added, among them e.g. from the midbody and cilia-specific interactome. For 5,164 of these reactions, information on their intracellular location has been annotated.

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        TRANSPATH applications

        Information downloads

        TRANSPATH® Statistics (download)
        TRANSPATH® Features (download)
        TRANSPATH® Flyer (download)
        TRANSPATH® Documentation (download)
        Sample flat file for 3 molecule entries (download)
        Sample flat file for 4 reaction entries (download)
        Sample flat file for 2 pathway entries (download)
        TRANSPATH® is a registered trademark of QIAGEN.

        Videos

        Publications

        Wingender, E., Hogan, J., Schacherer, F., Potapov, A.P., Kel-Margoulis, O. (2007) Integrating pathway data for systems pathology. In Silico Biol. 7:S17-S25. PubMed.

        Kel, A., Voss, N., Jauregui, R., Kel-Margoulis, O., Wingender, E. (2006) Beyond microarrays: find key transcription factors controlling signal transduction pathways. BMC Bioinformatics 7:S13. PubMed.

        Krull, M., Pistor, S., Voss, N., Kel, A., Reuter, I., Kronenberg, D., Michael, H., Schwarzer, K., Potapov, A., Choi, C., Kel-Margoulis, O., Wingender, E. (2006) TRANSPATH: an information resource for storing and visualizing signaling pathways and their pathological aberrations. Nucleic Acids Res. 34:D546-D551. PubMed

        Choi, C., Crass, T., Kel, A., Kel-Margoulis, O., Krull, M., Pistor, S., Potapov, A., Voss, N., Wingender, E. (2004) Consistent re-modeling of signaling pathways and its implementation in the TRANSPATH database. Genome Inform. 15:244-254. PubMed

        Choi, C., Krull, M., Kel, A., Kel-Margoulis, O., Pistor, S., Potapov, A., Voss, N., Wingender, E. (2004) TRANSPATH – a high quality database focused on signal transduction. Comp. Funct. Genomics 5:163-168. PubMed

        Krull, M., Voss, N., Choi, C., Pistor, S., Potapov, A., Wingender, E. (2003) TRANSPATH: an integrated database on signal transduction and a tool for array analysis. Nucleic Acids Res. 31:97-100. PubMed

        Schacherer, F., Choi, C., Götze, U., Krull, M., Pistor, S., Wingender, E. (2001) The TRANSPATH signal transduction database: a knowledge base on signal transduction networks. Bioinformatics 17:1053-1057. PubMed

        Heinemeyer, T., Chen, X., Karas, H., Kel, A.E., Kel, O.V., Liebich, I., Meinhardt, T., Reuter, I., Schacherer, F., Wingender, E. (1999) Expanding the TRANSFAC database towards an expert system of regulatory molecular mechanisms. Nucleic Acids Res. 27:318-322. PubMed

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