geneXplain platform basic

The geneXplain platform

Basic or professional?

expression analysis of genes
Transcription factors
Networks
databases and tools
pathways and key nodes
Sequences from mouse, human and rat genomes
Next Generation Sequencing (NGS)
gene or protein cluster
Single Nucleotide Polymorphisms (SNPs)
ready-made workflows

What is the geneXplain platform?
The geneXplain platform is an online toolbox and workflow management system for a broad range of bioinformatic and systems biology applications.
What does the platform include?
The platform provides an integrated view on several databases and analysis tools. They can be combined in a highly flexible way to design customized analyses.
How does the platform work?
Ready-made workflows allow a quick and easy access to the platform and its complex analysis functions. Input forms are simple and user-friendly.
How much does the platform cost?
It is for free! After registration (see below) you will get access to the platform immediately with 15Mb working space.
What is the geneXplain platform professional?
You can adjust your working space to your needs and datasets, while we  support 50 different input formats  with drag-and-drop function.
What does the geneXplain platform professional include?
You can access over 30 state of the art tools for  raw data processing  and work in 200 downstream pipelines with over 15 included databases.
How to enable geneXplain’s unique upstream analysis?
You have the option to include geneXplain’s sophisticated commercial databases TRANSFAC®, TRANSPATH® and HumanPSD to qualify for the  full upstream analysis  within the platform.
How much does the geneXplain platform professional cost?
It starts with 1000 Euro (without VAT) for academic organizations with a 1-user account and 50 GB working space for one year.
Want professional account now?
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Start your own data analysis right away!

Make your registration and get your basic platform account for free now!

Videos
Third party publications
  • Drake, C., Zobl W., Wehr M., Koschmann J., De Luca D., Kühne B. A. , Vrieling H. , Boei J. , Hansen T. , Escher S. E. (2022) Transcriptome data to substantiate the assessment of similar mechanism of actions in a read-across context – a case study on volatile diketones. in preparation
  • 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
  • Myer P.A., Kim H., Blümel A.M., Finnegan E., Kel A., Thompson T.V., Greally J.M., Prehn J.H., O’Connor D.P., Friedman R.A., Floratos A., Das S. (2022) Master Transcription Regulators and Transcription Factors Regulate Immune-Associated Differences Between Patients of African and European Ancestry With Colorectal Cancer. Gastro Hep Adv. 1(3), 328–341. Link
  • Kawashima Y., Nagai H., Konno R., Ishikawa M., Nakajima D., Sato H., Nakamura R., Furuyashiki T., Ohara O. (2022) Single-Shot 10K Proteome Approach: Over 10,000 Protein Identifications by Data-Independent Acquisition-Based Single-Shot Proteomics with Ion Mobility Spectrometry. J Proteome Res. 21(6), 1418–1427. Link
  • Klees S., Schlüter J.S., Schellhorn J., Bertram H., Kurzweg A.C., Ramzan F., Schmitt A.O., Gültas M. (2022) Comparative Investigation of Gene Regulatory Processes Underlying Avian Influenza Viruses in Chicken and Duck. Biology (Basel). 11(2), 219. 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
  • Menck K., Heinrichs S., Wlochowitz D., Sitte M., Noeding H., Janshoff A., Treiber H., Ruhwedel T., Schatlo B., von der Brelie C., Wiemann S., Pukrop T., Beißbarth T., Binder C., Bleckmann A. (2021) WNT11/ROR2 signaling is associated with tumor invasion and poor survival in breast cancer. J Exp Clin Cancer Res. 40, 395. 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
  • Chereda H., Bleckmann A., Menck K., Perera-Bel J., Stegmaier P., Auer F., Kramer F., Leha A., Beißbarth T. (2021) Explaining decisions of graph convolutional neural networks: patient-specific molecular subnetworks responsible for metastasis prediction in breast cancer. Genome Med. 13, 42. Link
  • Heinrich F., Ramzan F., Rajavel A., Schmitt A.O., Gültas M. (2021) MIDESP: Mutual Information-Based Detection of Epistatic SNP Pairs for Qualitative and Quantitative Phenotypes. Biology (Basel). 10(9), 921. Link
  • Tenesaca S., Vasquez M., Alvarez M., Otano I., Fernandez-Sendin M., Di Trani C.A., Ardaiz N., Gomar C., Bella A., Aranda F., Medina-Echeverz J., Melero I., Berraondo P. (2021) Statins act as transient type I interferon inhibitors to enable the antitumor activity of modified vaccinia Ankara viral vectors. J Immunother Cancer. 9(7), e001587. Link
  • Vanvanhossou S.F.U., Giambra I.J., Yin T., Brügemann K., Dossa L.H., König S. (2021) First DNA Sequencing in Beninese Indigenous Cattle Breeds Captures New Milk Protein Variants. Genes (Basel). 12(11), 1702. Link
  • Lloyd K., Papoutsopoulou S., Smith E., Stegmaier P., Bergey F., Morris L., Kittner M., England H., Spiller D., White M.H.R., Duckworth C.A., Campbell B.J., Poroikov V., Martins Dos Santos V.A.P., Kel A., Muller W., Pritchard D.M., Probert C., Burkitt M.D.; SysmedIBD Consortium. Using systems medicine to identify a therapeutic agent with potential for repurposing in inflammatory bowel disease. Dis Model Mech. 13(11), dmm044040. Link
  • Odagiu L., Boulet S., Maurice De Sousa D., Daudelin J.F., Nicolas S., Labrecque N. (2020) Early programming of CD8+ T cell response by the orphan nuclear receptor NR4A3. Proc Natl Acad Sci U S A. 117(39), 24392–24402. 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
  • Ural, B.B., Yeung, S.T., Damani-Yokota, P., Devlin, J.C., de Vries, M., Vera-Licona, P., Samji, T., Sawai, C.M., Jang, G., Perez, O.A., Pham, Q., Maher, L., Loke, P., Dittmann, M., Reizis, B., Khanna, K.M. (2020) Identification of a nerve-associated, lung-resident interstitial macrophage subset with distinct localization and immunoregulatory properties. Sci. Immunol. 5, eaax8756. Link
  • Leiherer A., Muendlein A., Saely C.H., Fraunberger P., Drexel H. (2019) Serotonin is elevated in risk-genotype carriers of TCF7L2 – rs7903146. Sci Rep. 9, 12863. Link
  • Wang B., Ran Z., Liu M., Ou Y. (2019) Prognostic Significance of Potential Immune Checkpoint Member HHLA2 in Human Tumors: A Comprehensive Analysis. Front Immunol. 10, 1573. 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
  • Blazquez, R., Wlochowitz, D., Wolff, A., Seitz, S., Wachter, A., Perera-Bel, J., Bleckmann, A., Beißbarth, T., Salinas, G., Riemenschneider, M.J., Proescholdt, M., Evert, M., Utpatel, K., Siam, L., Schatlo, B., Balkenhol, M., Stadelmann, C., Schildhaus, H.U., Korf, U., Reinz, E., Wiemann, S., Vollmer, E., Schulz, M., Ritter, U., Hanisch, U.K., Pukrop, T. (2018) PI3K: A master regulator of brain metastasis-promoting macrophages/microglia. Glia 66, 2438-2455. Link
  • Orekhov, A.N., Oishi, Y., Nikiforov, N.G., Zhelankin, A.V., Dubrovsky, L., Sobenin, I.A., Kel, A., Stelmashenko, D., Makeev, V.J., Foxx, K., Jin, X., Kruth, H.S. Bukrinsky, M. (2018) Modified LDL Particles Activate Inflammatory Pathways in Monocyte-derived Macrophages: Transcriptome Analysis. Curr. Pharm. Des. 24, 3143-3151. Link
  • Smetanina, M.A., Kel, A.E., Sevost’ianova, K.S., Maiborodin, I.V., Shevela, A.I., Zolotukhin, I.A., Stegmaier, P., Filipenko, M.L. (2018) DNA methylation and gene expression profiling reveal MFAP5 as a regulatory driver of extracellular matrix remodeling in varicose vein disease. Epigenomics 10, 1103-1119. Link
  • Kalozoumi, G., Kel-Margoulis, O., Vafiadaki, E., Greenberg, D., Bernard, H., Soreq, H., Depaulis, A., Sanoudou, D. (2018) Glial responses during epileptogenesis in Mus musculus point to potential therapeutic targets. PLoS One 13, e0201742. Link
  • Mandić, A.D., Bennek, E., Verdier, J., Zhang, K., Roubrocks, S., Davis, R.J., Denecke, B., Gassler, N., Streetz, K., Kel, A., Hornef, M., Cubero, F. J., Trautwein, C. and Sellge, G. (2017) c-Jun N-terminal kinase 2 promotes enterocyte survival and goblet cell differentiation in the inflamed intestine. Mucosal Immunol. 10, 1211-1223. Link
  • Niehof, M., Hildebrandt, T., Danov, O., Arndt, K., Koschmann, J., Dahlmann, F., Hansen, T. and Sewald, K. (2017) RNA isolation from precision-cut lung slices (PCLS) from different species. BMC Res. Notes 10, 121. Link
  • Triska, M., Solovyev, V., Baranova, A., Kel, A., Tatarinova, T.V. (2017) Nucleotide patterns aiding in prediction of eukaryotic promoters. PLoS One 12, e0187243. Link
  • Pietrzyńska, M., Zembrzuska, J., Tomczak, R., Mikołajczyk, J., Rusińska-Roszak, D., Voelkel, A., Buchwald, T., Jampílek, J., Lukáč, M., Devínsky, F. (2016) Experimental and in silico investigations of organic phosphates and phosphonates sorption on polymer-ceramic monolithic materials and hydroxyapatite. Eur. J. Pharm. Sci. 93, 295-303. Link
  • Ciribilli, Y., Singh, P., Inga, A., Borlak, J. (2016) c-Myc targeted regulators of cell metabolism in a transgenic mouse model of papillary lung adenocarcinoma. Oncotarget 7, 65514-65539. Link
  • Wlochowitz, D., Haubrock, M., Arackal, J., Bleckmann, A., Wolff, A., Beißbarth, T., Wingender, E., Gültas, M. (2016) Computational Identification of Key Regulators in Two Different Colorectal Cancer Cell Lines. Front. Genet. 7, 42. Link
  • Lee, E.H., Oh, J.H., Selvaraj, S., Park, S.M., Choi, M.S., Spanel, R., Yoon, S. and Borlak, J. (2016) Immunogenomics reveal molecular circuits of diclofenac induced liver injury in mice. Oncotarget 7, 14983-15017. Link
  • Kural, K.C., Tandon, N., Skoblov, M., Kel-Margoulis, O.V. and Baranova, A.V. (2016) Pathways of aging: comparative analysis of gene signatures in replicative senescence and stress induced premature senescence. BMC Genomics 17(Suppl 14), 1030. Link
  • Borlak, J., Singh, P. and Gazzana, G. (2015) Proteome mapping of epidermal growth factor induced hepatocellular carcinomas identifies novel cell metabolism targets and mitogen activated protein kinase signalling events. BMC Genomics 16, 124. Link
  • Shi, Y., Nikulenkov, F., Zawacka-Pankau, J., Li, H., Gabdoulline, R., Xu, J., Eriksson, S., Hedström, E., Issaeva, N., Kel, A., Arnér, E.S., Selivanova, G. (2014) ROS-dependent activation of JNK converts p53 into an efficient inhibitor of oncogenes leading to robust apoptosis. Cell Death Differ. 21, 612-623. Link
  • Schlereth, K., Heyl, C., Krampitz, A.M., Mernberger, M., Finkernagel, F., Scharfe, M., Jarek, M., Leich, E., Rosenwald, A., Stiewe, T. (2013) Characterization of the p53 Cistrome – DNA Binding Cooperativity Dissects p53’s Tumor Suppressor Functions. PLoS Genet. 9, e1003726. Link
  • Nikulenkov, F., Spinnler, C., Li, H., Tonelli, C., Shi, Y., Turunen, M., Kivioja, T., Ignatiev, I., Kel, A., Taipale, J., Selivanova, G. (2012) Insights into p53 transcriptional function via genome-wide chromatin occupancy and gene expression analysis. Cell Death Differ. 19, 1992-2002. Link
  • Zawacka-Pankau, J., Grinkevich, V.V., Hunten, S., Nikulenkov, F., Gluch, A., Li, H., Enge, M., Kel, A., Selivanova, G. (2011) Inhibition of glycolytic enzymes mediated by pharmacologically activated p53: targeting Warburg effect to fight cancer. J. Biol. Chem. 286, 41600-41615. Link
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Our own publications
  • Kalya M., Kel A., Wlochowitz D., Wingender E., Beißbarth T. (2021) IGFBP2 Is a Potential Master Regulator Driving the Dysregulated Gene Network Responsible for Short Survival in Glioblastoma Multiforme. Front Genet. 12, 670240. Link
  • Alachram H., Chereda H., Beißbarth T., Wingender E., Stegmaier P. (2021) Text mining-based word representations for biomedical data analysis and protein-protein interaction networks in machine learning tasks. PLoS One., 16(10), e0258623. Link
  • Kel A., Boyarskikh U., Stegmaier P., Leskov L.S., Sokolov A.V., Yevshin I., Mandrik N., Stelmashenko D., Koschmann J., Kel-Margoulis O., Krull M., Martínez-Cardús A., Moran S., Esteller M., Kolpakov F., Filipenko M., Wingender E. (2019) Walking pathways with positive feedback loops reveal DNA methylation biomarkers of colorectal cancer. BMC Bioinformatics. 20(Suppl 4),119. Link
  • Boyarskikh, U., Pintus, S., Mandrik, N., Stelmashenko, D., Kiselev, I., Evshin, I., Sharipov, R., Stegmaier, P., Kolpakov, F., Filipenko, M., Kel, A. (2018) Computational master-regulator search reveals mTOR and PI3K pathways responsible for low sensitivity of NCI-H292 and A427 lung cancer cell lines to cytotoxic action of p53 activator Nutlin-3. BMC Med. Genomics 11(Suppl 1), 12. Link
  • Kel, A.E., Stegmaier, P., Valeev, T., Koschmann, J., Poroikov, V., Kel-Margoulis, O.V. and Wingender, E. (2016) Multi-omics “upstream analysis” of regulatory genomic regions helps identifying targets against methotrexate resistance of colon cancer. EuPA Open Proteomics 13, 1-13. Link
  • Koschmann, J., Bhar, A., Stegmaier,P., Kel, A. E. and Wingender, E. (2015) “Upstream Analysis”: An integrated promoter-pathway analysis approach to causal interpretation of microarray data. Microarrays 4, 270-286. Link
  • Kel, A., Kolpakov, F., Poroikov, V., Selivanova, G. (2011) GeneXplain — Identification of Causal Biomarkers and Drug Targets in Personalized Cancer Pathways. J. Biomol. Tech. 22(Suppl), S16. Link
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