Tag Archives: Progenesis CoMet

Progenesis CoMet Application Note – rapid validation of LC-MS approach for non-targeted metabolomics

If you need to set-up and validate the potential of LC-MS for non-targeted metabolomics, Progenesis CoMet makes it much simpler and quicker. Our application note shows data analysis could be performed in hours, not weeks, to demonstrate LC-MS would differentiate pig adipose samples with and without “taint”, a characteristic that impacts boar meat production. The […]

The one reason you should join the Progenesis Improvement Program

Because it’s in your interest; you’ll get better, faster software as a result. 🙂 But there are other reasons too: It’s completely automated, so you won’t ever have to do anything after opting in If you ever change your mind, you’re in control; you can opt-out instantly, at any time We only collect information that […]

At last! Pain-free reviewing in the Progenesis workflow

One of the great benefits of all of the software in the Progenesis range is the visualization of your data throughout the analysis process. Being able to skip back and review any stage of the analysis gives you confidence in that analysis and the freedom to explore your data. For a long time, however, there […]

Progenesis CoMet v2.0 released for LC-MS-based metabolomics

Early last year we announced a beta version of Progenesis CoMet v2.0 was available so we could get feedback on a radical new workflow we introduced.  After showing it to many metabolomics researchers and finalising the development work we have now released Progenesis CoMet v2.0. The latest version has new features but retains the benefits […]

Solutions for your proteomics and metabolomics data analysis–come and see us at HUPO, Boston

We have made our final preparations for the HUPO 11th Annual World Congress which starts in Boston, Massachusetts on Sunday 9th Sept and we are really looking forward to what promises to be a great meeting. We will be based in the exhibit hall, at booth #404, and our data analysis specialists will be on […]

Waters and Nonlinear co-develop analysis solutions for large-scale, complex data sets

Following our earlier blog post announcing that we had embarked on a major project with Waters Corporation to supply software as part of their new ‘Omics Research Platform Solution we can bring you a progress update. The formal agreement has been signed and a press release made by Waters Corporation, which was reported the same […]

New Omics Research Platform Solution from Waters, powered by Nonlinear Dynamics

Note:This post refers to the TransOmics™ Informatics range of software, which has since been superseded by the Progenesis QI range, which represents the merging of Waters’ TransOmics™ Informatics into Nonlinear Dynamics’ existing Progenesis software. All of the features described, however, remain relevant. A fuller description of the new products can be found here. Thanks! The […]

A new version of Progenesis CoMet for metabolomics data analysis

Right now, we have a beta version of Progenesis CoMet v2.0 that we’d love to share with you. The first version was launched back in May 2011 and since then we have been working hard to improve it based on your feedback. It continues to solve the main challenges you face, by giving you confidence […]

Free download: improved cross-platform support in CoMet and LC-MS

In recent months, we’ve broadened our support for data file formats in the latest versions of both Progenesis LC-MS and Progenesis CoMet. Thanks to the plug-in architecture that we use in Progenesis, you can get these improvements today, free of charge. mzML and netCDF support for Progenesis CoMet Earlier this month, we introduced support for […]

Co-detection: The secret to reliably quantifying & identifying the same peptides on all your LC-MS runs

A question that we get asked by people new to Progenesis LC-MS is “why is the final list of proteins in my experiment exactly the same in every group?” The simple answer, and part of the power of Progenesis LC-MS, is co-detection. Co-detection is what we call our approach to peak picking based on an […]