PanHunter
Analyze Your Deep Biological Omics Data at Ease
It is an open secret that the path to new medicines and treatments for previously incurable diseases lies hidden under a huge mountain of scientific data. Today, we have developed an overwhelming number of data generation methods and analytical procedures that help us to study the human body. However, the great challenge we face is to extract the crucial insights from this mountain of data, which has been growing exponentially for years.
Evotec has developed PanHunterTM, a multi-omics data analysis platform. It helps to manage, explore and analyze these large molecular biology data. Through a web-based graphical user interface, it enables all scientists to access and interpret the data. With a wide range of tools, it helps users find the hidden connections in the data and map the critical shortcuts to reach their goal: medicines that matter!
PanHunter was developed and used successfully internally, and in industry-shaping drug discovery partnerships, over the years. Since 2022, it is also available to interested collaborators and partners as a software-as-a-service (“SaaS”) product.
PanHunter Key Features
Data is the basis for all insights. We provide the necessary tools for fast and comprehensive interpretations:
- Highly Interactive
No more waiting for pipelines to finish. See your fully interactive results right away - True Multi-omics Support
Analyze and interpret data from any omics platforms and protocols across species borders together or next to each other - Modular and Extendable
Battle-proven features, developed for researchers by researchers - Always the Right Interface
You decide whether you interact with the data via the graphical user interface or use scripts and the API - Fully Collaborative
Share data, results, and more with your colleagues or even work in parallel - Reliable and Reproducible
Rely on peer-reviewed algorithms and a fully transparent and reproducible workflow
~15k
Patients in molecular patient database>150
Users working simultaneously on internal instance300
Clinical parameters per patient (on avg.)>20,000
Samples in one project*Raw data sizes in range of terabytes per project
>1,000,000
Full transcriptome & proteome analyzed so far~15k
Patients in molecular patient database>150
Users working simultaneously on internal instance300
Clinical parameters per patient (on avg.)>20,000
Samples in one project*Raw data sizes in range of terabytes per project
>1,000,000
Full transcriptome & proteome analyzed so far
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