These new partnerships are intended to bring powerful new Single Cell Analysis Services to Cancer Researchers. ROSALIND adds a Web-based solution to offer advanced biological analysis and interpretation of Single Cell Clusters in tumor genome profiling experiments.
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This new web-based system, developed with NIH funding, will aid in monitoring emerging SARS-CoV-2 variants and the performance of diagnostic tests
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Our latest ROSALIND update v3.16 is now live and delivers enhancements for collaboration, 10X Single Cell RNA (scRNA-seq), Pathway Enrichment and more.
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We’ve all been reminded across various social media feeds how Isaac Newton discovered calculus while “social distancing” during the Great Plague of London or how some of Shakespeare’s greatest works happened while in quarantine. Although the thought of being able to work from home was once a dream we wished for, as Adam Ruben, Ph.D. puts it, science-ing from home isn’t easy.
If juggling your altered home-life alongside the 9-5 work routine wasn’t challenging enough, it’s even more questionable how you can advance your research now that you have limited access to your laboratory, your data and your team.
As we all grapple with the new reality of lockdowns and work-from-home mandates, there’s now a new opportunity re-define what it truly means to do collaborative research and remote science anywhere in the world.
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After conversations with thousands of Scientists, there is stunning lesson in their feedback that every Pharma and Biotech manager should internalize: Collaboration is more valuable than the underlying analysis pipelines.
No matter how great the pipeline, if Scientists can’t explore, interpret and consistently collaborate on a common version of the data then the value invested in the experiment is lost, or simply not realized.
Like dark data, the latent insights in these experiments remain trapped. Interestingly, Pharma and Biotech institutions with a deluge of clinical trial and research data are looking for collaboration tools for their Scientists, not the fundamental analysis pipelines. The implications for oncology research, immunology, drug discovery and disease research are significant.
- Something every Scientist should read: we walked through Collaboration Spaces on ROSALIND, highlighting how it's now possible to collaborate in real-time on genomic data (like Google Docs). Read the post here.
- We've forever transformed Public Data exploration. Follow this link for more information.
- Learn more about the latest capabilities, supported species and levels of access in this post on empowering scientists.
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Let’s face it, collaborating on genomics data is hard.
Topics: Rosalind Public Data Collaboration
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Thousands of Scientists around the world entrust ROSALIND every day to discover the most valuable results in their NGS data and to enable collaboration across project teams and labs. ROSALIND provides fast, easy data processing and is recognized as the leading Scientist-focused platform for genomic analysis and collaboration.
In this post, I'll review ROSALIND's latest capabilities, supported species and experiment types as well as our new subscription plans designed specifically for Scientists and Biologists.
- In case you missed it, we recently provided a detailed walk-through on Public Data exploration. Follow this link for more information.
- As well as the ability to Collaborate on Genomic Data as easily and in real-time like Google Docs. Follow this link for more information.
- NanoString recently announced a collaboration for the development of new analysis tools for data generated on NanoString’s nCounter® Analysis System. The new analysis functionality is built into ROSALIND and will soon be available to all NanoString customers. Learn more and join the Early Access Program.
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Working with Public Data is important to nearly every Scientist in our community. Unfortunately, it's harder than it should be to work with these valuable datasets. We all see and hear the news each week of exciting discoveries and breakthroughs in leading research, yet accessing and analyzing these Public Datasets, especially from RAW (SRA), requires determination, persistence and more coding skills than should be required of Scientists today.