October 23, 2017  |  Announcements, Conferences, DROP, viSNE

Biomedical Engineering Society Conference Review: Using viSNE on Single-cell Image Data for Improved Characterization of Immunotherapeutic Stem Cells

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Recently at the Biomedical Engineering Society MeetingRoss Marklein from the FDA’s Center for Biologics Evaluation and Research (CBER), presented a poster using viSNE in Cytobank on single-cell image data to characterize the function of mesenchymal stem cells (MSCs) used for cell therapy in autoimmune disease.
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August 16, 2017  |  Announcements, DROP, Release Notes

New Release: DROP Expands Machine Learning Analysis
to More Data Types

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The team at Cytobank is delighted to announce the release of version 6.0.

In addition to updates and improvements across the platform, we are most excited to announce that our new DROP functionality is now available on all Enterprise Cytobank sites.

DROP (Data to Results Optimization Portal) enables you to import any numeric data in the format of a spreadsheet / numeric matrix for analysis by automating its conversion into an FCS file within Cytobank.

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August 16, 2017  |  Announcements, DROP

Don’t Miss Our DROP Training Webinar Aug. 23

You are invited to join us Wednesday, August 23rd at 12:00 PM EDDropSimpleGoldT/9:00 AM PDT for a live webinar showcasing our new DROP functionality in Cytobank Enterprise.

Geoff-144px Join Cytobank’s Application Scientist Geoff Kraker for a live demo and training for the newest features that enable broader analysis of more data types than ever before. Brush up on all that Cytobank has to offer, ask your questions, and take back more tools and methods to help accelerate your discovery.

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June 8, 2017  |  Cytobank, DROP, Education

Maximize Your Insight with Machine Learning Algorithms
and NanoString® 3D Biology™ Technology

Courtesy: NanoString
Image courtesy: NanoString

Scientists across many therapeutic areas are striving to solve complex biological problems by measuring multiple analytes, thinking that together these data will power deeper discovery. However, analyzing these data independently is less effective and more time-consuming than analyzing them together. Cytobank’s new DROP feature allows scientists to apply machine learning algorithms to many data types, including these datasets, and to develop integrated insights quickly.

With bulk data, unsupervised machine learning algorithms on Cytobank can help you identify clinically relevant groups of samples by combining information from all of your markers at the same time. We’ll illustrate that here with Nanostring® 3D Biology technology, which simultaneously analyzes up to 800 SNVs, RNA, and proteins and phospho-proteins from the same sample. In this example, the assays used profile 104 SNV and small InDels, 192 RNA, and 28 total and phospho-proteins in 144 samples.

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May 24, 2017  |  Announcements, DROP

Coming Soon: Analyze More Data Types in Cytobank

Run Cytobank’s machine learning-based dimensionality reduction and clustering tools across additional data types beyond cytometry. Discover biomarkers and explore cellular interactions and clinical outcomes faster and more comprehensively leveraging the scalable compute and collaborative power of the cloud.

Measuring system-wide immune responses requires significant breadth and depth of data [123]. Cytobank will soon release functionality on its Enterprise-level platform enabling you to expand your analysis beyond cytometry to tabular single cell or bulk data including RNA, DNA, extracted imaging features, proteins (e.g. cytokine/chemokine, antibodies, cellular proteins), metabolomics, clinical features, and more.

Analyze Multiple Single Cell Data Types to Discover More:image1

Leverage the discovery potential of broader, agnostic data types such as genomics and transcriptomics. Then cross-validate and delve deeper into mechanism with proteomics.

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