genexplain

Discover with precision

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

TRANSFAC 2.0

Master your gene regulation

EXPLORE TRANSFAC

200 000

users

30 000

citations

35-year

experience

PASS

Predict drug biological activity

EXPLORE PASS

5 000

users

10 000

citations

45-year

experience

BRENDA

Model enzymes and metabolic pathways

EXPLORE BRENDA

100 000

users

5 000

citations

30-year

experience

TRANSFAC 2.0 Packages

Choose your package of gold standard databases and tools

TRANSFAC

Basic

Discover TF binding sites in promoters and enhancers of your genes

Buy TRANSFAC BASIC

TRANSFAC

Pathways

Reconstruct signal transduction network controlling your genes

Buy TRANSFAC PATHWAYS

TRANSFAC

Diseases

Identify drug targets and disease
biomarkers

Buy TRANSFAC DISEASES

PASS chemo-informatics

Biological activity spectrum for a compound library

PASS

PASS and PharmaExpert

Compute biological activity for chemical compounds using SAR
(structure-activity relationship)
approach

Buy PASS and Pharma Expert

PASS

GUSAR

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

Buy GUSAR

BRENDA metabolism database

Master the enzymes and metabolites

BRENDA

BRENDA

The most comprehensive enzyme database powered by industry standard systems biology platform

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