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Biognosys, a leading proteomics company, announced today that it has secured USD 5m funding from new and existing investors in an extended series C round. Biognosys' contract research services and tools are successfully applied in biomarker research, drug and target discovery, pathway modeling, mechanisms of action studies and many other areas. Its market leading expertise in next-generation proteomics is recognized by top pharma and biotech companies like Novartis, AstraZeneca, Moderna Therapeutics, and world's leading academic institutions. Biognosys is using the funds to extend its commercial operations and to accelerate the development of next generation proteomics workflows and products for high-content and high-throughput protein analysis. Proteomics refers to the large-scale study of proteins, biomolecules that govern most of the functions of any organism. Analyzing proteins and how their expression changes under different conditions offers major advantages when studying biological systems. However, for many years the development of large-scale proteomics techniques has lagged behind genomics and researchers have been using gene expression as a proxy for protein expression. This has recently changed with the introduction of high resolution liquid chromatography-mass spectrometry (LC-MS/MS) instruments that enable the simultaneous quantification of thousands of proteins in a single experiment. "The feedback that we get from our customers shows there is a shift in the perception of proteomics, away from a highly specialized analytical tool and towards a universally applicable technology for mode of action studies and biomarker development," says Dr. Oliver Rinner, CEO and co-founder of Biognosys. He adds: "Until recently the only option to get a broad picture of protein expression across different conditions or over time was to look at RNA expression as a proxy for the proteome. Now we can directly analyze the proteome with high depth and throughput. The funds will help us to further extend our technological lead, to accelerate the development of new products and workflows, and to better address the life science research market outside the classical proteomics field." Biognosys is the leading proteomics company offering innovative services and products for highly multiplexed protein quantification. We are dedicated to transforming the life sciences with superior proteomics solutions. Biognosys' next generation technology quantifies proteins with unbeatable precision and depth. Our solution relies on mass spectrometry, which allows simultaneous quantification of thousands of proteins in a single experiment. This new generation protein quantification technology is available to researchers worldwide through our contract research services or our portfolio of innovative reagent and software products. For more information, please visit http://www.biognosys.com.


SCHLIEREN, Schweiz, July 13, 2017 /PRNewswire/ -- Biognosys, ein führendes Unternehmen für Proteomik, gab heute bekannt, dass es sich fünf Millionen USD von neuen und bereits vorhandenen Investoren in einer erweiterten Serie-C-Runde sichern konnte. Die...


Biognosys, a leading proteomics company, announced today that it has secured USD 5m funding from new and existing investors in an extended series C round. Biognosys' contract research services and tools are successfully applied in biomarker research, drug and target discovery, pathway modeling, mechanisms of action studies and many other areas. Its market leading expertise in next-generation proteomics is recognized by top pharma and biotech companies like Novartis, AstraZeneca, Moderna Therapeutics, and world's leading academic institutions. Biognosys is using the funds to extend its commercial operations and to accelerate the development of next generation proteomics workflows and products for high-content and high-throughput protein analysis. Proteomics refers to the large-scale study of proteins, biomolecules that govern most of the functions of any organism. Analyzing proteins and how their expression changes under different conditions offers major advantages when studying biological systems. However, for many years the development of large-scale proteomics techniques has lagged behind genomics and researchers have been using gene expression as a proxy for protein expression. This has recently changed with the introduction of high resolution liquid chromatography-mass spectrometry (LC-MS/MS) instruments that enable the simultaneous quantification of thousands of proteins in a single experiment. "The feedback that we get from our customers shows there is a shift in the perception of proteomics, away from a highly specialized analytical tool and towards a universally applicable technology for mode of action studies and biomarker development" says Dr. Oliver Rinner, CEO and co-founder of Biognosys. He adds: "Until recently the only option to get a broad picture of protein expression across different conditions or over time was to look at RNA expression as a proxy for the proteome. Now we can directly analyze the proteome with high depth and throughput. The funds will help us to further extend our technological lead, to accelerate the development of new products and workflows, and to better address the life science research market outside the classical proteomics field". Biognosys is the leading proteomics company offering innovative services and products for highly multiplexed protein quantification. We are dedicated to transforming the life sciences with superior proteomics solutions. Biognosys' next generation technology quantifies proteins with unbeatable precision and depth. Our solution relies on mass spectrometry, which allows simultaneous quantification of thousands of proteins in a single experiment. This new generation protein quantification technology is available to researchers worldwide through our contract research services or our portfolio of innovative reagent and software products. For more information, please visit http://www.biognosys.com.


"DIA is part of our quantitative proteomics arsenal. It is it an excellent fit for discovery proteomics, providing both high depth of proteome coverage in large sample series and the ability to reproduce data points more precisely between technical replicates than other methods. As such, it complements other quantitative techniques such as Tandem Mass Tags (TMT) and Parallel Reaction Monitoring (PRM)," said Andreas Huhmer, director, proteomics and metabolomics marketing, chromatography and mass spectrometry, Thermo Fisher. "The Spectronaut Pulsar software creates an efficient pipeline for spectral library creation and processing of large DIA datasets." "We developed Spectronaut Pulsar to support our own contract DIA services business, as well as our research customers with access to high-resolution instruments," said Lukas Reiter, chief technology officer, Biognosys. "It has been extensively optimized to take advantage of HRAM data from Orbitrap mass spectrometers as this is the platform we work on ourselves. Spectronaut Pulsar is easy to use, very fast and able to process very large datasets and every detail was optimized to provide the best possible quantitative results." Orbitrap mass spectrometry, which was introduced by Thermo Fisher more than 10 years ago, is well accepted as the gold standard platform for proteomics research. As part of the collaboration, both companies will continue to further build upon and optimize DIA-related workflows. Thermo Fisher is featuring the software and instruments during the 65th Annual American Society for Mass Spectrometry (ASMS) Conference, being held June 4-8, in the White River Ballroom F-J at the JW Marriott, Indianapolis. For more information on Thermo Fisher's proteomics solutions, visit thermofisher.com/asms. About Thermo Fisher Scientific Thermo Fisher Scientific Inc. is the world leader in serving science, with revenues of $18 billion and more than 55,000 employees globally. Our mission is to enable our customers to make the world healthier, cleaner and safer. We help our customers accelerate life sciences research, solve complex analytical challenges, improve patient diagnostics and increase laboratory productivity. Through our premier brands – Thermo Scientific, Applied Biosystems, Invitrogen, Fisher Scientific and Unity Lab Services – we offer an unmatched combination of innovative technologies, purchasing convenience and comprehensive support. For more information, please visit www.thermofisher.com. About Biognosys Biognosys is the leading proteomics company offering innovative services and products for highly multiplexed protein quantification. We are dedicated to transforming the life sciences with superior proteomics solutions. Biognosys' next generation technology quantifies proteins with unbeatable precision and depth. Our solution relies on mass spectrometry, which allows simultaneous quantification of thousands of proteins in a single experiment. This new generation protein quantification technology is available to researchers worldwide through our contract research services or our portfolio of innovative reagent and software products. For more information, please visit www.biognosys.com. To view the original version on PR Newswire, visit:http://www.prnewswire.com/news-releases/thermo-fisher-scientific-and-biognosys-announce-co-marketing-agreement-to-create-industry-leading-data-independent-acquisition-workflows-300468451.html


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: BIOTEC-2-2015 | Award Amount: 10.71M | Year: 2016

Recent developments in omics technologies demand implementation of systems biology approaches to facilitate analysis and interpretation of the generated complex datasets.This is essential for biotechnological as well as preclinical and clinical applications. In comparison to previous approaches, most cancer relevant studies are confined to pattern recognition or at best modelling of single pathways, rather than the complex pathways and cross-talk determining cancer progression and drug response. Systematic tools that evaluate and validate personalised medicine approaches on a preclinical level are missing; an important prerequisite for translation into clinical practice. The overall objective of CanPathPro is to build and validate a new biotechnological application: a combined experimental and systems biology platform, which will be utilized in testing cancer signaling hypotheses in biomedical research and life sciences. Thus, the proposed project will focus on developing and refining bioinformatic and experimental tools for the evaluation of systems biology modelling predictions. Components comprise a highly controlled mouse experimental system, NGS, a quantitative proteomics based read-out of changes in pathway signalling and an integrative systems biology model for data integration. Testable hypotheses about biological systems will be generated and experimentally validated. The developed system tools will be made available to researchers, SMEs and industry for practical applications. Following this project, a commercial platform for interpretation and analysis of complex omics data and for deriving and testing new hypotheses will be set up by the participating companies and academic partners. CanPathPro will enhance the competitive potential of the SMEs involved expanding in the field of biotechnology, personalised medicine and drug development and also provide new opportunities for other SMEs working in the field of bioinformatics and biomedical applications.


Picotti P.,ETH Zurich | Rinner O.,ETH Zurich | Rinner O.,Biognosys | Stallmach R.,ETH Zurich | And 8 more authors.
Nature Methods | Year: 2010

Selected reaction monitoring (SRM) uses sensitive and specific mass spectrometric assays to measure target analytes across multiple samples, but it has not been broadly applied in proteomics owing to the tedious assay development process for each protein. We describe a method based on crude synthetic peptide libraries for the high-throughput development of SRM assays. We illustrate the power of the approach by generating and applying validated SRM assays for all Saccharomyces cerevisiae kinases and phosphatases. © 2010 Nature America, Inc. All rights reserved.


Karlsson C.,Lund University | Malmstrom L.,ETH Zurich | Aebersold R.,ETH Zurich | Aebersold R.,University of Zürich | And 2 more authors.
Nature Communications | Year: 2012

Selected reaction monitoring mass spectrometry (SRM-MS) is a targeted proteomics technology used to identify and quantify proteins with high sensitivity, specificity and high reproducibility. Execution of SRM-MS relies on protein-specific SRM assays, a set of experimental parameters that requires considerable effort to develop. Here we present a proteome-wide SRM assay repository for the gram-positive human pathogen group A Streptococcus. Using a multi-layered approach we generated SRM assays for 10,412 distinct group A Streptococcus peptides followed by extensive testing of the selected reaction monitoring assays in >200 different group A Streptococcus protein pools. Based on the number of SRM assay observations we created a rule-based selected reaction monitoring assay-scoring model to select the most suitable assays per protein for a given cellular compartment and bacterial state. The resource described here represents an important tool for deciphering the group A Streptococcus proteome using selected reaction monitoring and we anticipate that concepts described here can be extended to other pathogens. © 2012 Macmillan Publishers Limited. All rights reserved.


Ori A.,Structural and Computational Biology Unit | Banterle N.,Structural and Computational Biology Unit | Iskar M.,Structural and Computational Biology Unit | Andres-Pons A.,Structural and Computational Biology Unit | And 8 more authors.
Molecular Systems Biology | Year: 2013

To understand the structure and function of large molecular machines, accurate knowledge of their stoichiometry is essential. In this study, we developed an integrated targeted proteomics and super-resolution microscopy approach to determine the absolute stoichiometry of the human nuclear pore complex (NPC), possibly the largest eukaryotic protein complex. We show that the human NPC has a previously unanticipated stoichiometry that varies across cancer cell types, tissues and in disease. Using large-scale proteomics, we provide evidence that more than one third of the known, well-defined nuclear protein complexes display a similar cell type-specific variation of their subunit stoichiometry. Our data point to compositional rearrangement as a widespread mechanism for adapting the functions of molecular machines toward cell type-specific constraints and context-dependent needs, and highlight the need of deeper investigation of such structural variants. Copyright © 2013 EMBO and Macmillan Publishers Limited.


The invention relates to the analysis of compounds with mass spectrometry and more particularly to instruments, substances, and methods for polypeptide analysis, in particular in targeted proteomics applications and based on indexed retention time as peptide specific property. The method of chemical analysis comprises the steps of: a) providing a first complex sample comprising a set of at least two reference peptides associated to an indexed retention time scale (iRT), as well as at least one further peptide; b) performing LC-MS on said complex sample and determining the empirical retention time values (RTe) of the reference peptides and of the at least one further peptide; c) translating the empirical retention time values (RTe) of the reference peptides and of the at least one further peptide into the indexed retention time scale and associating to each reference peptide a reference indexed retention time value (iRTr) and to the at least one further peptide an associated indexed retention time value (iRTa); d) providing a second complex sample comprising at least one polypeptide as well as said set of the at least two reference peptides; e) performing LC-MS on said second complex sample and determining the empirical retention time values (RTe) of the reference peptides; f) translating the empirical retention time values (RTe) of the reference peptides into the indexed retention time scale by numerically adapting the transformation function for the conversion of the retention time values (RTe) into indexed retention time values such that the calculated indexed retention time values (iRTe) calculated based on the measured retention time values (RTe) of the reference peptides match the assigned indexed retention time values (iRTr) of the reference peptides; g) determining the predicted empirical retention time value (RTp) of the at least one further peptide by using the numerically adapted transformation function determined in step f).


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