Mavatar Discovery
Science takes time. Discovery shouldn’t.
An AI- and data-driven research platform that helps pharma, biotech, and academia turn large-scale transcriptomic data into testable hypotheses.
A New Starting Point for Research
What if researchers could generate new hypotheses about drug targets, biomarkers, and disease mechanisms in hours, not months?
Mavatar Discovery is now available, delivering biologically grounded, data-driven insights from large-scale transcriptomic data, with speed, clarity, and scientific rigor.
A platform built for researchers, by researchers
Mavatar Discovery is a SaaS platform designed for researchers, pharmaceutical companies, and academia to accelerate basic, translational, and clinical research.
It supports data-driven exploration of publicly available transcriptomic data, generating statistical analyses, visualizations, and hypotheses to guide your research.
No code. No Pipelines. Just Discovery.
Accelerating discovery where data is scarce
Check out the opportunity to receive one of four full-year Mavatar Discovery licenses in 2026, awarded quarterly to researchers advancing rare disease science.
Key benefits
Discover what makes Mavatar Discovery different
GROUNDED IN DATA
Built on Real-World Data
Powered by curated and quality controlled, publicly available transcriptomic data, including sources like GEO, TCGA, and CellxGene.
NETWORK BIOLOGY
Context-Rich Analysis
Explore context-specific gene networks, functional enrichment, and cross-disease comparisons, all with full traceability back to the source data.
BUILT FOR RESEARCHERS
No Code Required
Visualize complex gene networks in minutes, no pipelines, no bioinformatics setup required.
Built for Speed
From Months to Minutes
Analyze thousands of datasets at once and identify candidate biological patterns to guide your next experiment.
How it works
From Questions to Hypotheses, in Four Steps
Mavatar Discovery guides you from a research question to a testable hypothesis. Here's how it works:
01
Select Your Focus Area
Choose from a growing library of tissue- and disease-specific gene networks, each built from thousands of samples across dozens of independent studies.
02
Explore Interactive Networks
Visualize gene conserved co-expression, pathways, and cross-disease overlaps. Because each network aggregates relationships across many studies, connections reflect reproducible biology, not artifacts of a single dataset.
03
Compare and Contextualize
See how genes of interest behave across different tissues, conditions, or diseases, including overlapping mechanisms across disease areas.
04
Take Your Hypotheses Forward
Export results and carry your hypotheses into experimental validation, focusing lab time on new questions rather than repeating existing studies or focusing on the wrong targets.
Who it's for
Pharma & Biotech R&D Teams
De-risk early discovery by prioritizing candidate targets built on reproducible gene networks, before committing to experimental validation.
Basic & Clinical Academic Researchers
Move from raw transcriptomic data to well-supported hypotheses, without building your own analysis pipeline.
Translational Medicine Groups
Explore candidate biomarkers and generate hypotheses for patient stratification studies, grounded in cross-disease network analysis.
Contract Research Organizations (CROs)
Deliver data-driven analysis to clients without building new infrastructure.
Licenses & Access Options
Flexible licensing tiers to fit your research needs
From first exploration to full integration in your workflows.
Free trial
For those trying out our features
Free 30-day trial
- Instant access for any user who creates an account
- Limited access - includes two selected, limited network - based on two mice tissue models; lung and liver
- Explore platform features and workflow before upgrading to a full license
- Onboarding pdf and video available
- Standard support
Academic/ Research
Contact us
- Monthly & Yearly Subscription options
- Upon registering with a valid academic email address - Full access to all networks with curated datasets, context-specific gene networks, cross-disease comparison, and functional enrichment tools
- Designed for academic researchers and smaller research groups
- Includes standard support and optional 1:1 digital platform onboarding
Professional
Contact us
- Full access to all networks with curated datasets, context-specific gene networks, cross-disease comparison, and functional enrichment tools
- Tailored for pharmaceutical R&D, CROs, and translational medicine teams
- Includes a 1-hour expert session/year with a Mavatar scientist to support your research goals, demonstrate advanced workflows, and provide tailored platform guidance
- Option to add up to 10 seats/users
- Priority support, dedicated 1:1 onboarding
Enterprise
Contact us
- Full access to all networks with curated datasets, context-specific gene networks, cross-disease comparison, and functional enrichment tools
- Ideal for large-scale organizations with specific workflow needs
- Option to add unlimited number of seats/users
- Includes a 2-hour expert session per year with a Mavatar scientist to support your research goals, demonstrate advanced workflows, and provide tailored platform guidance
- Dedicated account management and strategic consultation
- Priority support, dedicated 1:1 onboarding
Join as a Mavatar Discovery Tester
We are inviting passionate researchers to help us take Mavatar Discovery further.
If you work in bioinformatics or computational biology - whether in academia, clinical research, pharma, or biotech - this is your chance to influence the future of our platform.
- Get 1 month of full access - free
- Share your feedback to shape new features
- Accelerate your research with ready-to-use networks and context
This is your chance to explore the full power of Mavatar Discovery - and influence how it evolves.
Frequently Asked Questions
Mavatar Discovery
Mavatar Discovery is a data‑driven research SaaS platform for systems-level analyses of disease biology consisting of a broad collection of tissue and disease-specific deep integrated gene networks. Each network is built based on thousands of samples from dozens of independent studies and further connected by Mavatar R&D-team curated metadata. It is developed to help researchers, pharmaceutical companies, and academic teams analyze complex biological networks, accelerating research within disease and drug discovery, reducing work that traditionally takes months down to minutes or hours.
Mavatar Discovery is designed to support:
Pharma & Biotech R&D Teams prioritizing candidate targets and exploring drug repurposing opportunities.
Contract Research Organizations (CROs) delivering data-driven analysis to clients without building new infrastructure.
Academic & Clinical Researchers investigating disease mechanisms and exploring candidate biomarkers.
Translational Medicine Groups generating hypotheses for patient stratification studies.
Mavatar Discovery's core design integrates vast amounts of published transcriptomic data into a single, cohesive resource. Large-scale integrated analyses are performed by Mavatar in advance, so when a researcher logs in, they arrive at a set of ready-to-use tools and resources.
Analytical platforms elsewhere typically offer tools for differential expression, clustering, heatmaps, and similar early-stage analyses. While these are useful, Mavatar Discovery moves past these initial steps, arriving directly at biologically meaningful networks and context to explore.
For example, a researcher working with our breast or lung cancer resources doesn't just access single datasets, but integrated networks built by aggregating data across hundreds of datasets and tens of thousands of patients. The platform also enables cross-referencing: studying lung cancer, you can simultaneously compare findings with fibrosis, long COVID, or asthma to reveal overlapping mechanisms and pathways.
With Mavatar Discovery, researchers can dive deep into disease-specific networks and explore tissue-wide patterns, making it faster and easier to prioritize candidate biomarkers, investigate disease mechanisms, and generate hypotheses about therapeutic targets.
Mavatar is powered by rich, fast-growing data sources from the global scientific community, such as Gene Expression Omnibus (GEO), ArrayExpress, The Cancer Genome Atlas (TCGA), CellxGene, Single Cell Portal and others.
Mavatar Discovery is built on DINA (Deep Integrated Network Analysis), our proprietary framework developed over 20+ years of scientific research. DINA integrates and analyzes thousands of transcriptomic datasets to model disease mechanisms at a systems level, delivering:
- Gene-level networks by tissue and disease
- Functional enrichment tools with full traceability back to original datasets
- Overlapping networks across diseases, revealing shared mechanisms and pathways
- Curated, structured results, not just raw data or pre-packaged database queries
- New features and capabilities added on an ongoing basis
Our approach supports high reproducibility, more accurate translation between animal and human studies, and comparison across diseases affecting the same tissue, or the same disease across different tissues.
Mavatar Discovery helps you explore:
- Gene co-expression patterns within a tissue or disease context, built from reproducible relationships across many independent studies, not a single dataset.
- Candidate biomarkers and therapeutic targets, prioritized through network analysis rather than single-gene or single-dataset queries.
- Disease mechanisms, by examining how genes relate to one another as a system rather than in isolation.
- Cross-disease and cross-tissue overlaps, for example, comparing lung cancer to fibrosis, long COVID, or asthma to reveal shared pathways.
- Functional enrichment results, with full traceability back to the original datasets behind each network.
These outputs are designed to generate testable hypotheses, supporting further experimental validation rather than replacing it.
- Free Trial: Anyone can sign up for a 30-day Free Trial License with limited access.
- Other license depends on type of user
- Contract Terms: Standard contract period is 1 year with automatic renewal, although monthly licenses are also supported.
- Contact Sales for more information sales@mavatar.com
Mavatar Discovery gives you access to a set of interactive network cards, each providing further detail and analysis options on your generated network:
DINA Network card: network construction details, including nodes, edges, modules, datasets, samples, and version, with a full downloadable list of contributing datasets and sources.
Gene Information card: gene identity, alternative names, gene type, and known associations, such as drug targets or rare disease links.
Edge Information card: connection strength between two genes, based on normalized correlation values.
Functional Enrichment: Gene Ontology, disease-association, and rare disease gene analyses, showing which biological functions are over-represented in your network.
Conditions Expression Chart: gene expression levels across different conditions within a tissue, useful for spotting potential biomarkers.
Network Similarity analysis: structural comparison between networks, showing which networks share functional characteristics.
Cell Type Explorer: a single-cell UMAP view showing where selected genes are expressed across cell types.
Patient Stratification Heatmap: expression patterns across genes and samples, with statistical tools to test for enrichment across sample groups.
All cards can be resized, expanded, or popped out into separate windows, and most link directly back to source datasets for full traceability.
And much more to come...
That’s just for now - Mavatar Discovery is just getting started, so expect continuous improvements and new features to be released going forward. Or better yet - be a part of the development and join us as an early user and make your voice heard!
Mavatar Discovery is a cloud-based platform accessible through a secure web interface. Users can log in, explore networks, and run analyses directly from their browser.
User can export their findings to png and svg (vector graphics). They can also customizable coloring and layout including pre-set themes that can match publication graphic requirements etc.
Yes, users can securely upload gene lists from e.g. their differential expression analysis to explore in the platform.
Depending on the complexity of the query, results can be generated in seconds to hours, significantly reducing the time required for traditional analysis. Is the tissue / disease you are interested in not available in Mavatar Discovery yet? Contact us and we will be happy to arrange a project together for a custom data survey and network construction.
Some examples on how to cite Mavatar Discovery are given below.
The graph was generated based on the [tissue, context] (version 1.0) network using Mavatar Discovery v1.1.0 (2025 Mavatar, https://discovery.mavatar.com/).
The graph was generated based on the combined [1st tissue, context] (version 1.0) and [2nd tissue, context] (version 1.0) networks using Mavatar Discovery v1.1.0 (2025 Mavatar, https://discovery.mavatar.com/).
The analyses were done based on the [tissue, context] (version 1.0) network using Mavatar Discovery v1.1.0 (2025 Mavatar, https://discovery.mavatar.com/).