A Fresh Approach to Data Analysis ...
Tercen is a rapid and flexible, drag and drop, data analytics platform that requires no coding knowledge. It easily allows users to share, integrate, and build-upon large data-sets in a simple and user-friendly environment. All online and in the cloud.
Easy To Use
Take control of your data quickly.
No coding necessary.
Build insightful views of your data in seconds. Simply drag and drop.
Copy, share, contribute, and collaborate on all your projects effortlessly.
Data Analysis Workflow
• Start an analysis workflow quickly
• Use simple and advanced statistics
• No coding skills necessary
Simplicity in Seconds
• Drag and drop to create any type of visual
• Create heatmaps, bar graphs, scatter plots, and more
• Quickly get an overview of your data
• Change workflows intuitively
Research and Innovation
To make quick decisions, investigators need real-time integration of their patients' clinical and biomarker data. Clinical trials generate data using different laboratory technologies by teams located in different countries. Use Tercen’s multivariate integration and workflow features to follow the behaviour of novel therapies.
At Tercen, we believe that everyone should have the opportunity to easily access ecology and biodiversity data. The Tara Ocean Foundation produces some of the world's leading oceanic datasets and is instrumental in the study of climate change. Follow the link to see Tercen's powerful visualisation and discover an ocean carbon export analysis.
Tercen brings an exciting approach to single-cell RNA-seq measurements. The transcriptome of single cells is widely used to study the properties of cell populations and biological systems, such as in oncology. Tercen makes scRNA-seq analysis workflow simple and accessible to the community, no coding necessary!
Tutorials, Webinars & How To's
On 24th June 2020, Tercen joined The Francis Crick Institute to present a webinar on 'Considerations For High Dimensional Flow Cytometry Data Analysis.' We would like to thank Derek Davies for giving us the opportunity to contribute to his program. Access the Tercen webinar recording and demonstration material by following the link below.
To get the most from their data and stay relevant in a competitive job market, biomedical researchers need to learn the basics of data science. Tercen makes this easy with our intuitive workflow and visualisation features that require no coding skills. View our demonstration using a famous multivariate study and get started with data science.
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What our users say
"Tercen enables me to analyses high-dimensional flow cytometry data with clustering algorithms that would otherwise require me to learn and use an elaborate R pipeline. In addition, Tercen allows for easy quality checks in between each data-step and can integrate multiple datasets."
Ralph MassPhD student at the Radboud umc
"I did not have experience in handling large data sets, and it was overwhelming at first. Tercen offered the flexibility I needed to study the changes in phosphorylation patterns upon gene knockdown without learning how to code. It became extremely easy to perform data analysis and present results."
Calum BaneMaster Student at University of Glasgow
“During our ongoing clinical trial, Tercen helped us analyse and visualize the clinical data, multi-marker and multi-site. Data analytics using Tercen provided us with relevant insights into the behaviour of our drug in a very efficient manner.”
Timothy PereraPhD, CSO at Octimet Oncology
“We quickly realized that Tercen could help us valorize data from bacteria growth study. By integrating multivariate datasets, Tercen allowed us to rapidly produce conclusions and plan the next experiments quickly and accurately.”
Bernhard PaetzoldPhD, Co-Founder of S-Biomedic
“Supporting wet-lab scientists while keeping man-power to develop our own informatics-heavy and independent research is a challenge we face. We had no platform allowing us to supervise and empower wet-lab scientists to perform analysis themselves. Tercen allows us to deepen and expand our services and scientific output.”
Javier AlfaroPhD, group leader in computational Biology, International centre for Cancer Vaccines Science
“We had no multivariate data analytics platform available and our flow cytometry data was not fully used. Tercen allowed us to integrate the readouts and produce publications.”