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On 29 April Alexander Kel (CSO) and Olga Kel-Margoulis (Director Applied Life Science Informatics) carried out a hands-on training in handling the geneXplain platform. The training course took place within the framework of the project "Unlocking infectious diseases research potential at Rīga Stradiņš University". The training programme provided theoretical functionalities and practical application for the identification of #drug #targets and #biomarkers with the geneXplain platform.
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Expression Mapping on the geneXplain platform
 
This function enables highlighting of up-regulated and down-regulated genes in the network diagrams.
 
First, open a network in the work area. You might be interested to use the table with identified differentially expressed genes and calculated fold change values for #expression #mapping. After the table with expression data is dragged and dropped, the up- and down-regulated #genes are automatically highlighted.
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Analyze promoters on the geneXplain platform

This workflow is designed to search for putative transcription factor binding sites (#TFBS) on the promoters of an input gene set.

As input, any gene or protein table can be submitted. The input table contains genes under study, and it is called “Yes” set (1).

At the first step, the input table is converted into a table with Ensembl Gene IDs (2).
At the next step, #promoters are analyzed for potential cis-regulatory sites. Promoters in this workflow are defined as sequences from -1000 to +100 relative to the transcription start sites.
Site search is done with the help of the #TRANSFAC® library of the positional weight matrices (#PWMs).
At the same step, frequencies of putative TFBSs are compared between Yes set and No set to identify sites overrepresented in Yes set versus No set. Default No set in the workflow is a set of housekeeping genes for the corresponding species.
The result of this step is a list of PWMs the hits of which are overrepresented in Yes set versus No set. Default No set in the workflow is a set of housekeeping genes for the corresponding species.

Next, the list of PWMs is converted into a table of transcription factors (3).

The output is a new folder with several tables, including a summary of the predicted TFBSs, genomic tracks of the Yes and No promoters and sites, as well as the tables with transcription factors potentially regulating the genes in the Yes set.

It is possible to get a #visualization of TFBS for individual genes (4).
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Coordinated by geneXplain, a new collaborative Russian-German project (#Mediomics) funded by the German BMBF and the Russian FASIE has been launched.
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geneXplain GmbH

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...or you should use the geneXplain platform!
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Pathway analysis
 
Network visualization after #pathway #analysis. Shown is a network that was re-constructed from genes found to be differentially expressed in a particular experiment (blue boxes), how they are connected in a #network through other components (green boxes), and how their pathways converge into TNF-alpha (tumor necrosis factor alpha) as central regulator (red box). Besides the Orthogonal layout used here, another four layout options are available.
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geneXplain GmbH

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#Release 3.0 of the geneXplain platform is available now with new tools in expression data analysis, statistical analysis, binding site analysis, with several new and enhanced workflows, and with the integrated latest releases of TRANSFAC® and TRANSPATH® databases (2013.3 and 2013.4), and many additional enhancements.
Follow your key topics on our new start page.
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Find master regulators in networks
This workflow is designed to find master regulatory molecules upstream of an input list of genes. Input file is any gene or protein table.
This workflow is designed to find important #master #regulators in #signal #transduction pathways. The search is done based on the network of the TRANSPATH® database.
Red = Master regulatory molecule
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geneXplain GmbH

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The geneXplain team wish you a peaceful #Christmas time!

Hope to see you on the platform in 2014...
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#Organization of the geneXplain platform

When you login into the geneXplain platform for the first time, a window opens that contains the following areas:

A - The Work Space, which is the main part of the window. The Start page presents a couple of predefined workflows/pipelines, which are chains of ready-to-start methods.

B- The Tree Area (to the left of the Work Space), where you find the collection of Databases, the uploaded data files and the available analyses methods under the corresponding tabs, organized in a hierarchical tree structure.

C - The Info Box (in the lower left part), where you can select the data resource to search in, or where you will get Information about the data file or analysis method that you select with a single click in the Tree Area.

D - The Operations Field (lower right part), providing a number of options under the different tabs in a context-dependent manner.

E - The general Control Panel, on top of the different areas, showing a context-dependent set of icons for the available operations.

Register here for a #free #account of the geneXplain platform!
http://www.genexplain.com/genexplain-platform-registration
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geneXplain GmbH's profile photoAlexey Chernobrovkin's profile photo
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Please send an email to info@genexplain.com. We need your email adress to complete your registration! Sorry :-(

geneXplain GmbH

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GeneXplain contributes to a new national research consortium (#ExITox, Explain Inhalation Toxicity). The kick-off meeting was today in Hannover.
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Analyse ChIP-seq data
Are you interested in identification and classification of target genes?
Let’s do it with our geneXplain platform.
Any dataset in #BED format (e. g. peak regions from #ChIP-seq experiment) can be submitted as input #track.
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Contact Information
Contact info
Phone
+49(0)-5331-992200-0
Email
Fax
+49(0)-5331-992200-22
Address
geneXplain GmbH Am Exer 10b D-38302 Wolfenbüttel Germany
Story
Tagline
We can explain your genes and put bricks together.
Introduction
We provide a comprehensive set of computational tools to support the complete drug development pipeline from the statistical evaluation of high-throughput data, their biological interpretation, identification of potential targets to the prediction of most promising lead structures.
GeneXplain GmbH has been founded in April 2010 and is based in Wolfenbüttel, Germany.


People displayed "in geneXplain GmbH's circles" are our team members only, so you know who we are.


Products
are all available as free demo or trial versions.

Our geneXplain platform is the online toolbox and workflow management system for scientists in the fields of transcriptomics and proteomics. Here, you can store and analyze your experimental data (including raw microarray results), search for master regulator molecules, map to GO terms, and even add your own workflows and scripts.

We distribute software developed by in silico molecular biology, inc., Japan, for geneticists. In-Silico Molecular Cloning (IMC) lets you handle annotated DNA, conduct cloning experiments in silico, map features and sequences, and compare and align genomes.
GenomeTraveler (GT) takes this to the next level by adding the possibility to visualize and interpret your Next Generation Sequencing (NGS) data.

For scientists working on drug discovery and drug optimization, we distribute a range of tools from the Institute of Biomedical Chemistry (IBMC), Russia. PASS (Prediction of Activity Spectra for Substances) predicts whole bioactivity spectra for your compounds qualitatively, based only on 2D structural formulae. PharmaExpert is the additional software to help you choose the most suitable substance from a set of PASS predictions.
GUSAR (General Unrestricted Structure-Activity Relationships) predicts biological activities quantitatively, based on (Q)SAR models, which can also be created with the software.