CLC bio Delivers Specialized Immunoinformatics Solution to Symphogen
News Aug 21, 2009
CLC bio has just completed a specialized immunoinformatics solution that is fully customized to fit into Symphogen’s proprietary Symplex™ technology for high throughput identification of antibodies with diversity and specificity customized to a particular therapeutic application.
CLC bio has developed a CLC Main Workbench plug-in, which is designed to optimize the end-to-end workflow and analysis pipeline when working with the large number of antibodies retrieved during the Symplex™ process.
“When investigating the diversity and complexity of disease-relevant antibody repertories from human donors, speed and quality are essential. Thus, the faster we can go through our initial bioinformatics workflow and identify a diverse panel of complementary antibodies of interest, the earlier we can compose the optimal recombinant polyclonal antibody (rpAb) drug lead candidate to advance into development - this is of course of the utmost importance to us” says Director of Antibody Discovery at Symphogen, Dr. Allan Jensen, PhD.
He continues, “CLC bio has fully integrated the workflow by automating all the steps in the downstream bioinformatics analysis process. Not only has this accelerated the research process tremendously by eliminating tedious and complicated manual procedures but it also removes the overhead of keeping third party software running and updated - and in turn it provides a high quality and robust workflow.”
Director of Consulting Services at CLC bio, Dr. Jannick D. Bendtsen, continues, “Where Symplex™ is a cutting-edge concept for testing on humans and in the lab, Symphogen’s new special plug-in is designed to analyze the sequencing data coming from all these research projects, and integrate them nicely into an end-to-end workflow. We are proud to deliver this intricate solution to Symphogen, which stresses the flexibility and stability that our overall bioinformatics platform provides, and we look forward to seeing Symphogen’s projects coming faster through their development phases.”
An artificial intelligence (AI) approach based on deep learning convolutional neural network (CNN) could identify nuanced mammographic imaging features specific for recalled but benign (false-positive) mammograms and distinguish such mammograms from those identified as malignant or negative.
8th Edition of International Conference and Exhibition on Separation Techniques
Jul 29 - Jul 30, 2019
International Women Health and Breast Cancer Conference
Jul 03 - Jul 05, 2019