Automatically Identify Predictive Biomarkers with Our Newest Algorithm
Why do some cancer patients respond well to immunotherapy but others do not?
Why do some people have a slow and painful recovery from surgery but others have a speedy recovery?
What are the biomarkers thatcan help predict these outcomes ahead of time?
The Challenge: High-dimensional single-cell analysis approaches are excellent for investigating such questions because many mechanisms of disease may only be visible at the single-cell level, eluding bulk analysis techniques. Emerging technologies such as high parameter fluorescence and mass cytometry, and powerful data analysis platforms like Cytobank, are providing unprecedented resolution for measuring single-cell biology. With these new technologies, a variety of specific cellular populations can be simultaneously identified, and anomalies can define different clinically relevant cohorts and serve as predictive diagnostics and prognostics.
The challenge of going from high-dimensional data to these useful findings lies in the analysis, which is often cumbersome, manual, subjective, and irreproducible. Our new version of the CITRUS algorithm aims to change that. More »
What is an important problem in human health and/or fundamental biology that you’d like to address? What is your scientific vision?
My vision is to develop high-dimensional techniques and computational tools to address the challenge of ‘big data.’ My hope is that these tools may be broadly applied to aid our understanding of the human condition. Technology, such as mass cytometry (CyTOF), has made it possible to capture different facets of biology such as cell function, epigenetic traits, and transcriptional readouts with infinitesimal single-cell granularity. More »
Achieve better results, faster. Automate your end-to-end pipelines with the Cytobank Platform via The Cytobank API. The Cytobank API extends the power of the Cytobank Cloud to any software application. Now bench scientists can more seamlessly interact with computational biologists and reviewers to assess results of internal algorithms and pipelines.
Every month, leading researchers investigate, discover, and publish new findings with the help of the Cytobank’s tools, platform, and community. Here are just a few papers of interest from the past few months: More »
Spitzer and Gherardini et al., from the Nolan Lab at Stanford University, report a novel bioinformatics approach to mapping the immune system called Scaffold (Single-Cell Analysis by Fixed Force- and Landmark-Directed).
Scaffold allows clustering of samples independently, thus allowing addition of new sample data over time. This approach requires users to develop or use a pre-defined reference map.
In their recent publication in Science, the authors reveal maps comparing immune organization among several tissue compartments, among mouse strains, between circadian states, and between species (mouse and human). More »
Come visit the Cytobank team at FOCiS and CYTO next week to learn more about what we’ve been up to, for some hands-on help, to share your wish list or just to chit-chat. We look forward to seeing you there!
Check out the various talks and posters at CYTO featuring Cytobank:
Saturday June 27, 2015
11:00 (Room: Alsh) – The First Multi-center Comparative Study Using a Novel Technology Mass Cytometry Time-of-Flight Mass Spectrometer (CyTOF2) for High-Speed Acquisition of Highly Multi-parametric Single Cell Data: A Status Report A. Nasaar, B. Carter, J. Lannigan, R. Montgomery, N. Paul, M. Poulin, K. Raddassi, A. Rahman and N. Rashidi. Yale Univ. Sch. of Med., Stanford Shared FACS Facilities, Univ. of Virginia Sch. of Med., Dana-Farber Cancer Inst., Fluidigm, Cambridge, MA, Icahn Sch. of Med. at Mount Sinai and Ragon Inst. of MGH, MIT and Harvard.
11:40 (Room: Alsh) – High Content Dissection of Human Melanoma Tumor Heterogeneity during Treatment Using Mass Cytometry J. Irish, D. Doxie, A. Greenplate, K. Diggins, H. Polikowsky, K. Dahlman, J. Sosman and M. Kelley. Vanderbilt Univ. Sch. of Med.
Cytobank 5.0 is on its way to customer sites, and includes sweeping ease-of-use updates driven by customer feedback, enabling you to reach your goal faster. We’ve implemented a three-level system, centralizing site-wide, experiment-wide, and page-specific actions and reducing time-to-goal.
Welcome to Cytobank User Stories, a series featuring interviews with Cytobank users on their research, scientific vision, and use of fluorescence and mass cytometry.
This week we interview Claude Chew, a Flow Cytometry Specialist Senior at University of Virginia in
Charlottesville, VA. We asked Claude to share with us his favorite features from our 4.2 release and to describe how this release has helped to improve his scientific workflow.
What are you excited about in science? What is your scientific vision?
My vision is to try to bring together the technical aspects of flow/mass cytometry with biology. My experience is that there is often a disconnect between the two. Hopefully there is a way to more fully integrate these aspects to make a fully-functioning unit that will be a powerful tool for looking into how life works at the single cell level! I’m particularly excited about recent developments in the field of high-dimensional analysis with the advent of the CyTOF and the data analysis platforms that have and continue to be generated to meet the challenge of ‘big data’. More »