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5 days, 3 hours agoAccelerating single-cell omics-driven research
Nygen is dedicated to advancing the field of single-cell genomics data analytics.
Our mission is to democratize this powerful technology by building accessible, accurate, and reproducible analytics tools (scarfweb.nygen.io). By improving collaboration between bench and computational scientists, we strive to create an environment that fosters innovation and breakthrough discoveries.
With our open-access data infrastructure (cellhub.nygen.io), researchers have the opportunity to explore and analyze vast amounts of single-cell genomics data, driving scientific progress forward. Our platform enables seamless integration of diverse datasets, enabling researchers to gain comprehensive insights from multi-modal and multi-omic analyses. We prioritize data quality and ensure rigorous validation, allowing researchers to trust the accuracy and reliability of their analyses.
We are committed to providing cutting-edge solutions in single-cell genomics analytics. Our partnerships with leading academic and research institutions allow us to constantly push the boundaries of what is possible in this field. Collaborations with top scientists and computational experts ensure that our tools stay at the forefront of innovation.
At Nygen, we are proud to be recognized as experts in this field. Our team possesses deep expertise in building cloud-based, data-intensive, and highly secure infrastructure. We have developed sophisticated algorithms, scalable analytics solutions, and a tailored, state-of-the-art cloud infrastructure to support the growing demand for data analysis in single-cell genomics. Our commitment to security and privacy ensures that researchers can trust that their data is protected while benefiting from seamless access and collaboration.
Join us in the exciting journey of democratizing single-cell genomics data analytics.
single-cell, genomics, transcriptomics, multiomics, cloud, data, AI, ML, and Predictive analysis
Nygen empowers researchers to unlock insights from single-cell RNA-seq data with accessible, no-code solutions, facilitating reproducible transcriptomic research.