August 1, 2018  |  Announcements, Press Releases

PRESS RELEASE: Cytobank Awarded NIH Grant to Scale its Cloud-based Machine Learning Platform for Accelerating Immunotherapy Translational Research

 Novel data analysis methods will automate biomarker discovery
to predict patient response in clinical trials

Mountain View, Calif. – August 1, 2108 – Cytobank has beenNIHLogo awarded a $1.3M Phase II SBIR grant from the NIH to scale and add more machine learning algorithms to its popular cloud-based informatics platform. In use at many leading academic institutions and the top ten global pharmaceutical companies, Cytobank’s research platform enables faster, more comprehensive analysis of the high-dimensional single cell datasets captured in immunotherapy clinical trials. There are greater than 1,000 active clinical trials for immunotherapies in oncology alone. More »

July 18, 2018  |  Announcements

Manage Experiments More Efficiently with Cytobank 6.3.1

storagedetailCytobank’s latest release introduces functionality to help you better manage your account storage and more easily clone experiment features

Improved Storage Management
You can now see how much storage space you are using, and can filter by experiment size in the inbox. Understand quickly which of your experiments may be more resource-intensive, cull unused or duplicate experiments, and keep your storage usage in check.

Improvements to cloning and sharing (learn more)
Select which components from your clonedetail-2experiments to clone. Carry over sharing permissions, compensation matrices separately from gates, panels separately from sample tags, and more. You can also choose whether to give your PI full access when you clone experiments. These features are also fully-supported in the Cytobank API.

Iterate and Refine Faster 
You can now quickly cancel SPADE, viSNE, and CITRUS runs in progress to correct mistakes or refine settings.

 

May 3, 2018  |  Announcements

New Release 6.3.0: Do More with Exploratory Data Analysis

viSNE is a powerful tool for exploratory data analysis. Samples or cells are visible in one view or “map” based on their similarity across the n-dimensions used to generate the map. Cytobank’s latest release introduces features to facilitate data exploration and the reproducibility of your results.

Our new expanded features can help investigators use viSNE in translational or clinical research studies to both uncover new discoveries and repeat these exciting findings.

More »

April 11, 2018  |  Announcements, Conferences, Flow Cytometry

Announcing Cytobank’s Collaboration with Cytek Biosciences

We’rCytekLogoe excited to announce a new collaboration with Cytek, makers of the innovative CytekTM Aurora Flow Cytometer. Cytek’s Aurora and Cytobank’s next-generation analytics platform have united in their goal to make high-dimensional data and its subsequent machine learning analysis more accessible to more scientists.

  • Aurora’s unique optical design combined with spectral unmixing delivers quality, high-dimensional data where rare and dim populations can be easily resolved, regardless of sample complexity.
  • Cytobank’s algorithms simplify visualization and analysis of high-dimensional unmixed data and allow you to quickly share discrete insights from these data.

Here are two specific examples of how you can apply our combined solutions to enable faster, more highly-resolved discoveries: More »

March 13, 2018  |  Announcements, API, Education

Introducing Cytobank BridgeR: An easy-to-use R package for Biologists

imagesThe Cytobank API opens up our platform to workflows and creative use beyond native functionality to improve the efficiency and velocity of your research efforts. We are excited to enhance the usability of the Cytobank API with the release of BridgeR, an easy-to-use R package for biologists.

Experience working in R isn’t required.  Our step-by-step guide provides instructions on how to execute the API-leveraged workflows detailed in BridgeR. More »

January 17, 2018  |  Announcements

Free Webinar – Machine Learning and Systems Biology Unite to Decode Drug Resistance

viSNEJanWebinar-576pxDon’t miss our free Webinar Thursday, January 25th at 9:00 AM PDT.

Learn how a systems biology approach that utilizes machine learning tools facilitates drug resistance discovery. Special guest, Cancer Biology PhD candidate Reema Baskar, co-mentored by Drs. Sean Bendall and Sylvia Plevritis of Stanford University, will show you how they leveraged Cytobank along with other computational tools to identify mechanisms of drug resistance in cancer cells.

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