Archive - geneXplain

TRANSFAC


The Gold Standard: more than 6500 positional weight matrices, and more than 30 million sites from high-throughput approaches!

The geneXplain platform


A versatile online toolbox for bioinformatics, systems biology and cheminformatics

Cheminformatics


Predict activity spectra of substances, and exploredrug-drug interactions and relationships between biological activities with PASS, GUSAR and PharmaExpert.

Upstream analysis


Discover unanticipated causal relationships in your data with our unique upstream analysis.

Genome Enhancer


Release 2.4 is now out!

 

Welcome to the new era of Precision Medicine

Meet Genome Enhancer – a fully automated pipeline for patient omics data analysis, which identifies prospective drug targets and corresponding treatments by reconstructing the molecular mechanism of the studied pathology. Proven applications of Genome Enhancer include cancer, neurodegenerative diseases, infectious diseases, diabetes and metabolic diseases.

Starting from release 2.0 Genome Enhancer is also available as Genome Enhancer Expert solution – a powerful synergism between the automatic pipeline for multi-omics data processing of Genome Enhancer and the comprehensive bioinformatics toolbox of the geneXplain® platform. More details about Genome Enhancer Expert solution are available here.

You can login to Genome Enhancer directly with your geneXplain® platform account or register for a new account in just several seconds to check out this great tool yourself.

 

Genome Enhancer uses Upstream Analysis, an integrated promoter and pathway analysis, to identify potential drug targets of the studied pathology.

In the first step of this analysis the transcription factors that regulate differentially expressed or mutated genes are identified with the use of the TRANSFAC® database of transcription factors binding sites.

The second step searches for common master-regulators of the identified transcription factors by building a personalized signal transduction network of the studied pathology using the TRANSPATH® database of mammalian signal transduction and metabolic pathways. The identified

master regulators are prospective drug target candidates. They are used for further selection of chemical compounds that can bring therapeutic benefit for the studied clinical case. In this step the HumanPSD database is employed to identify drugs that have been tested in clinical trials. The cheminformatic tool PASS predicts small molecules that can affect the identified targets.

Finally, Genome Enhancer generates a comprehensive analysis report about the personalized drug targets identified for a certain patient, or a group of patients, and the drugs that may be effective in this case. You can view a number of Genome Enhancer demo reports at the corresponding section of this page.

 

A detailed description of Genome Enhancer analysis schema can be found on this page.

You are welcome to activate a free trial or purchase a paid subscription for Genome Enhancer at the geneXplain store.

Key features

  • Identifies activated targets in the examined patient data and suggests known and re-purposing drugs
  • Based on well accepted databases TRANSFAC®, TRANSPATH®, HumanPSD™
  • Applies unique in-house developed algorithms
  • Suites for use by researches and by medical doctors
  • Does not require special skills to operate
  • Analyses all types of omics data starting either with raw or pre-processed data
  • Generates a comprehensive report on the identified drug targets and prospective therapies
  • Generates MTB (Molecular Tumor Board) report on patient’s genomics data for a number of pathologies (if not more than 2 conditions were selected during the analysis launch)

 

Available solutions

 

Starting from release 2.0 Genome Enhancer is also available as Genome Enhancer Expert solution – a powerful synergism between the automatic pipeline for multi-omics data processing of Genome Enhancer and the comprehensive bioinformatics toolbox of the geneXplain® platform.

Genome Enhancer Expert will open you the full functionality of the geneXplain® platform with TRANSFAC®, TRANSPATH® and HumanPSD™ databases connected. In the platform view you will be able to perform further processing of your analysis results, received from Genome Enhancer, create, modify and use already pre-defined workflows for your multi-omics data analysis and work with data coming from other model organisms. For more info on geneXplain® platform functionality please refer to the platform product page.

Only three steps to launch the analysis


 

Running Genome Enhancer takes only three steps:

1. Upload your data to the server and specify the import options (data type)


2. Split your data by the conditions you want to compare


3. Launch the analysis by specifying the conditions to be compared and the disease and tissue types (optional)

The analysis report will be ready shortly. Depending on your input data, it will include lists of differentially expressed or mutated genes; transcription factors, regulating those genes; reconstructed signaling network of the studied pathological process; potential drug targets and corresponding known drugs and re-purposing drugs, which may be effective in the studied case, as well as further cheminformatically predicted drug-like compounds. The report also contains description of analysis methods used and the references.

Acceptable input data formats

Genome Enhancer works with genomics, transcriptomics, epigenomics, proteomics and metabolomics input data types of the following formats:

Transcriptomics (RNA-seq, microarrays)

*.txt, *.csv, *.xls (table with gene identifiers)

*.CEL (affymetrix)

*.txt (special agilent format)

*.txt (special illumina format)

*.fastq

Epigenomics (ChIP-seq)

*.fastq

*.bam (hg38 only)

*.bed (hg38 only)

*.txt (table with illumina methylation probe ids, cg*)

Genomics

*.vcf

*.txt, *.csv, *.xls (table data with SNP identifiers, rs*), *.tsv

*.fastq

Proteomics

*.txt, *.csv, *.xls (table with protein identifiers)

Metabolomics

*.txt, *.csv, *.xls (table with the list of metabolites from chebi database, e.g. CHEBI:57316)


Files of one data format can be uploaded in a .zip archive

What we offer

Multi-omics analysis

Use genomics, transcriptomics, metabolomics, proteomics, and epigenomics data in one analysis run and receive an integrated report

 

Easy interface

Due to complete automation of the analysis, the system can be used by medical doctors and biologists without any bioinformatics skills

 

Personalized medicine

Running the analysis on omics data of a certain patient, you will identify personalized prospective drug targets and corresponding treatments

 

Scientific base

Integration of promoter and enhancer analysis with pathway reconstruction gives unrivaled disease molecular mechanism modeling accuracy

Drug target identification

Genome Enhancer reconstructs a complex network of signal transduction pathways that are activated in the pathology and identifies their key regulators

 

 

Flexible pricing

Select the license which fits you best – both short-term and long-term licenses are supported by our flexible tariffs. For more details visit the geneXplain store

Report examples

You can view various analysis report examples generated by Genome Enhancer on the basis of different omics input data types and various origins of the studied pathologies:

You are also very welcome to view or download the Genome Enhancer flyer.

Videos

Below you will find a compilation of our videos referring to different aspects of Genome Enhancer.
In English Language
This video introduces you to the fully automated pipeline for the easy bioinformatics analysis of multi-omics data. (2:02 min)

 

In Chinese Language
The video provides you with a preview to the user interface of Genome Enhancer, and shows how to perform an analysis using Genome Enhancer. (4:42 min)
This video uses transcriptomics data as an example to highlight the detailed content of the data analysis report obtained as result of an analysis by Genome Enhancer. (3:09 min)
Here, Genome Enhancer is applied to analyze multi-omics data of colorectal cancer cell lines to find master regulators and to predict drug compounds affecting them. Thereafter, the effect of the predicted drug compounds on tumors is verified in an animal experiment.

References

  1. Lloyd, Katie, et al. “Using systems medicine to identify a therapeutic agent with potential for repurposing in Inflammatory Bowel Disease.” Disease models & mechanisms (2020).
  2. Kel, Alexander, et al. “Walking pathways with positive feedback loops reveal DNA methylation biomarkers of colorectal cancer.” BMC bioinformatics 20.4 (2019): 119.
  3. Kolpakov, Fedor, et al. “BioUML: an integrated environment for systems biology and collaborative analysis of biomedical data.” Nucleic acids research 47.W1 (2019): W225-W233.
  4. Boyarskikh, Ulyana, et al. “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 medical genomics 11.1 (2018): 12.
  5. Boyarskikh, U. A., et al. “Master-regulators driving resistance of non-small cell lung cancer cells to p53 reactivator Nutlin-3.” Virtual Biology 4 (2017): 1-31.

 

Disclaimer

The results of Genome Enhancer analysis, contained in any of the reports produced by this pipeline, are intended for research use only and should not be used for medical or professional advice. GeneXplain GmbH makes no guarantee of the comprehensiveness, reliability or accuracy of the information contained in the reports generated by Genome Enhancer.

Decisions regarding care and treatment of patients should be fully made by attending doctors. The predicted chemical compounds listed in the reports are given only for doctor’s consideration and they cannot be treated as prescribed medication. It is the physician’s responsibility to independently decide whether any, none or all of the predicted compounds can be used solely or in combination for patient treatment purposes, taking into account all applicable information regarding FDA prescribing recommendations for any therapeutic and the patient’s condition, including, but not limited to, the patient’s and family’s medical history, physical examinations, information from various diagnostic tests, and patient preferences in accordance with the current standard of care. Whether or not a particular patient will benefit from a selected therapy is based on many factors and can vary significantly.

The compounds predicted to be active against the identified drug targets in the reports are not guaranteed to be active against any particular patient’s condition. GeneXplain GmbH does not give any assurances or guarantees regarding the treatment information and conclusions given in the reports. There is no guarantee that any third party will provide a refund for any of the treatment decisions made based on these results. None of the listed compounds was checked by Genome Enhancer for adverse side-effects or even toxic effects.

The analysis reports contain information about chemical drug compounds, clinical trials and disease biomarkers retrieved from the HumanPSD™ database of gene-disease assignments maintained and exclusively distributed worldwide by geneXplain GmbH. The information contained in this database is collected from scientific literature and public clinical trials resources. It is updated to the best of geneXplain’s knowledge however we do not guarantee completeness and reliability of this information leaving the final checkup and consideration of the predicted therapies to the medical doctor. In all cases, the end user (including researchers and medical doctors) accepts full responsibility for all risks associated with using of information, contained in the reports generated by Genome Enhancer.

The scientific analysis underlying the Genome Enhancer reports employs a complex analysis pipeline which uses geneXplain’s proprietary Upstream Analysis approach, integrated with TRANSFAC® and TRANSPATH® databases maintained and exclusively distributed worldwide by geneXplain GmbH. The pipeline and the databases are updated to the best of geneXplain’s knowledge and belief, however, geneXplain GmbH shall not give a warranty as to the characteristics or to the content and any of the results produced by Genome Enhancer. Moreover, any warranty concerning the completeness, up-to-dateness, correctness and usability of Genome Enhancer information and results produced by it, shall be excluded.

The results produced by Genome Enhancer, including the analysis reports, severely depend on the quality of input data used for the analysis. It is the responsibility of Genome Enhancer users to check the input data quality and parameters used for running the Genome Enhancer pipeline.

Note that the text given in the reports is not unique and can be fully or partially repeated in other Genome Enhancer analysis reports, including reports of other users. This should be considered when publishing any results or excerpts from the reports. This restriction refers only to the general description of analysis methods used for generating the reports. All data and graphics referring to the concrete set of input data, including lists of mutated genes, differentially expressed genes/proteins/metabolites, functional classifications, identified transcription factors and master regulators, constructed molecular networks, lists of chemical compounds and reconstructed model of molecular mechanisms of the studied pathology are unique in respect to the used input data set and Genome Enhancer pipeline parameters used for the current run.

Upstream Analysis

genexplain platform logo

What is Upstream Analysis?

GeneXplain’s proprietary approach to analyze gene expression data is called Upstream Analysis. The term indicates that it is a causal analysis, providing a clue about the reason why a certain set of genes has been up- (or down-) regulated in the system under study. In contrast, conventional analyses usually reveal the effects of the differentially expressed genes, e.g. by mapping them onto ontological categories.

upstream_analysis_overview

How does it work?

GeneXplain’s Upstream Analysis is an integrated promoter – pathway analysis. It starts from any list of differentially expressed genes (DEGs), which you may have extracted from your raw data with the aid of the geneXplain platform, and comprises two main steps:
  • At first, the promoters of the differentially regulated genes are retrieved and analyzed for potential transcription factor (TF) binding sites and their combinations. From that, a set of TFs is identified that potentially have regulated the found DEGs.
  • In a second step, the pathways are reconstructed that are known to activate the previously hypothesized TFs. Molecules where these pathways converge are considered as potential master regulators of the process under study

Step 1: Promoter analysis

First, potential transcription factor binding sites (TFBSs) are identified in all promoters of the DEGs of your experiment (Yes set) as well as in a negative control set (No set). This is the usually done with a library of position-specific scoring or positional weight matrices (PSSMs or PWMs).
We recommend to apply the most comprehensive matrix library available, the TRANSFAC® database, and using the MATCHTM algorithm for the sequence analysis.
Next, out of all these potential transcription factor binding sites (TFBSs), those that are characteristic for the DEG set under study are identified. This is done by rigorously determining their enrichment in the Yes- compared to the No set.
site-enrichment
Learn more about promoter analysis with TRANSFAC® in the geneXplain platform.

Step 2: Pathway analysis

Step 1 resulted in a set of transcription factors (TFs), that are likely repsonsible for the differential regulation of the observed set of DEGs. From available pathway data, we have extracted information about all relevant signaling cascades that regulate the activity of TFs; optimally, the TRANSPATH® database is used for this and the further analysis.
As has been proven in a large number of use cases, these pathways usually converge in a couple of key nodes, which qualify as candidate master regulators of the process under study.
master_regulators

Activities of transcription factors (TFs, blue circles) are regulated by upstream signaling cascades (components shown as green circles). These converge in certain nodes, representing molecules that are potential master regulators of the process under study.

PharmaExpert

PharmaExpert Logo
PharmaExpert analyzes the relationships between biological activities, drug-drug interactions and multiple targeting of chemical compounds and selects compounds that have a pre-defined biological activity. It helps answer a question like “How to select the most promising compounds among those known to interact with the selected protein?”

Click image to enlarge the picture.

What PharmaExpert can do

The input of the program is a (set of) SDfile(s) with PASS results.

PharmaExpert then allows to:

  • Select compounds with the required therapeutic, but without adverse effects;
  • Comparatively analyze compounds with similar structures;
  • Do a multitargeted selection of compounds with multiple mechanisms of action;
  • Assess drug-drug interactions with regard to their pharmacokinetic, pharmacodynamic, and adverse effects.
PharmaExpert performs these tasks through an elaborate system to assign:

  • Superclass–subclass relations between biological activities (see box below)
  • Mechanistic cause–effect relations in either direction:
    • Effects (e.g., anxiolytic effect) are traced back to a molecular mechanism (e.g., acting as 5-Hydroxytryptamine 1A agonist)
    • Mechanisms are predicted to exhibit certain effects

PharmaExpert interface

Several diagrams, e.g. pointing at different master regulators (figure below, red nodes), can be easily joined.

PharmaExpert interface. PharmaExpert analyzes the relationships between biological activities, drug-drug interactions and multiple targeting of chemical compounds and selects compounds that have a pre-defined biological activity.

PharmaExpert interface. (Click image for an enlarged view.)

More to gain an insight into PharmaExpert’s look-and-feel can be found on facebook

Key features of PharmaExpert 2020

To make the software even more user-friendly, the code of PharmaExpert has been improved especially with respect to the user interface. In addition, all parts of the code have been double-checked.
The number of synonyms for different activity types increased to 20,288 which enables you to search more effectively for your the activity terms of interest.

PharmaExpert interface

Several diagrams, e.g. pointing at different master regulators (figure below, red nodes), can be easily joined.

PharmaExpert interface. PharmaExpert analyzes the relationships between biological activities, drug-drug interactions and multiple targeting of chemical compounds and selects compounds that have a pre-defined biological activity.

PharmaExpert interface. (Click image for an enlarged view.)

More to gain an insight into PharmaExpert’s look-and-feel can be found on facebook

PASS

PASS Logo
The acronym PASS stands for Prediction of Activity Spectra for Substances. Upon entering a structural formula of a chemical substance, the program returns the potential biological activities of this compound.
PASS has been well accepted by the community, and is now actively used in the field of medicinal chemistry, by both academic organizations and pharma companies.
There are over 300 third-party publications with references to PASS. Some of the most recent papers that provide experimental evaluation of PASS predictions are listed
here.
Application areas
  • Medicinal chemistry
  • Computational chemistry
  • Drug discovery / drug development
  • Drug repositioning
  • Chemical toxicity
  • Safety assessment
  • Pharmacogenomics, chemogenomics
  • SAR (qualitative structure-activity relationship)
  • Natural compound effects
  • Translational research / translational medicine

Activity prediction for a chemical substance by PASS

The slide show demonstrating the look-and-feel of PASS can be found here as well as on our Facebook site. A particularly useful tool to analyze and utilize PASS results further is PharmaExpert.

Key features of PASS 2020

The general PASS training set has been improved. So PASS 2020 SAR Base contains information about 1,368,353 substances, which are described by 128,917 MNA descriptors of the 1st and 2nd levels.
The entire activity list includes 9,942 terms of activity type. Thereof, 8,283 activity types may be predicted with the average invariant accuracy, IAP, of prediction 0.9301.
All predictable activity types are categorized into seven groups:

  • 559 Pharmacological Effects
  • 4,481 Mechanisms of Action
  • 678 Toxic and Adverse Effects
  • 161 Antitargets
  • 225 Metabolism-Related Actions
  • 2,414 Gene Expression Regulation
  • 86 Transporters-Related Actions
By default, PASS 2020 predicts 1,945 activity types with the average invariant accuracy of prediction 0.9711. Find the recommended list of activity types here (pdf, 294 KB).
Depending on the particular purpose, the user may include into the predictable activity list any of the 8,283 activity types using the “Selection” procedure.

News

Find history in our archive.
September 23, 2021

Join us for geneXplain’s open day devoted to the World Cancer Research Day on September 23rd at 3 PM CEST. Check the event page for further info and registration details.

September 10, 2021

Basel Computational Biology Conference Logo

Don’t miss the chance to attend geneXplain’s contribution to the BioNetVisA workshop at the [BC]2 conference on Monday September 13, 2021.
In his online-talk entitled “Personalized anti-cancer drug treatment choice using RNA-seq and network analysis” Dr. Alexander Kel will present the application of Genome Enhancer to cancer patient data.

September 9, 2021

TRANSFAC® 2.0 is now out! Check out this great resource for gene regulation studies.

September 9, 2021

GeneXplain announces:

TRANSPATH® 2021.2
HumanPSDTM 2021.2

September 9, 2021

Genome Enhancer 2.4 release is now out!
Check out the new features list for more info.

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