Discover with precision

Apply high-quality knowledge of diseases, drugs, pathways, and gene regulation.

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TRANSFAC 2.0 Packages

Choose your package of gold standard databases and tools

Master your gene regulation

200 000

users

30 000

citations

35-year

experience

TRANSFAC

Basic

Discover TF binding sites in promoters and enhancers of your genes
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Buy TRANSFAC BASIC
TRANSFAC

Pathways

Reconstruct signal transduction network controlling your genes
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Buy TRANSFAC PATHWAYS
TRANSFAC

Diseases

Identify drug targets and disease
biomarkers
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Buy TRANSFAC DISEASES

PASS chemo-informatics

Biological activity spectrum for a compound library

Predict drug biological activity

5 000

users

10 000

citations

45-year

experience

PASS

PASS and PharmaExpert

Compute biological activity for chemical compounds using SAR 
(structure-activity relationship)
approach
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Buy PASS and Pharma Expert
PASS

GUSAR

Create quantitative models on  structure-activity (structure-property) relationships
OR run your compounds on pre-computed models
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Buy GUSAR

BRENDA metabolism database

Master the enzymes and metabolites

Model enzymes and metabolic pathways

5 000

users

10 000

citations

45-year

experience

BRENDA

BRENDA

The most comprehensive enzyme database powered by industry standard systems biology platform
Compute biological activity for chemical compounds using SAR 
(structure-activity relationship)
approach
More…

Buy BRENDA

OUR PARTNERS

Testimonials

GeneXplain’s databases and software tools are very helpful for our research. The training program is absolutely amazing. It clearly shows to my students how to maximize results of analysis of our omics data! They can learn all the steps of the analysis  – from raw data preprocessing to unraveling the hidden molecular mechanisms behind the pathology we’re studying
DR. SUDIPTO DAS
Royal College Of Surgeons In Ireland (RCSI), Lecturer, Pharmacy And Biomolecular Sciences
The geneXplain “Click and Run” bioinformatics approach is absolutely perfect for my needs! I’ve discovered how to uncover the biological significance hidden within my data.
Maria Smetanina
Baylor College of Medicine, Houston, Texas, USA