Tag Archives: Progenesis QI for proteomics

You can now analyse your labelled data with Progenesis!

During an upcoming webinar on 28th March, you can hear about a new offering for quantitative proteomics. Progenesis QI for proteomics (QIP) now has the capability to analyse samples where stable isotope labels have been added, including SILAC and dimethyl labelling. These capabilities are added through a new module called Proteolabels, from Omic Analytics Ltd. […]

Report research with confidence – Who else wants to publish small molecule LC-MS analysis confidently?

Meaningful results Over 800 groups worldwide are using Progenesis QI routinely to generate small molecules and proteomics results that really reflect the effect of the conditions in the experimental design, so they can have confidence in presenting these results to their peers, with minimal fear of false positives. How can we claim that only Progenesis […]

How Progenesis QI resolves the problem of missing values

I’ve been at Nonlinear Dynamics for ten years now. In that time, we’ve seen the Progenesis range develop beyond just proteomics and, in 2013, we were acquired by Waters, although Progenesis QI will work on label-free data from any major MS vendor. I was originally brought into Nonlinear Dynamics to generate leads, so after 2 […]

Progenesis plugins: gotta catch ’em all!

Here at Nonlinear Dynamics, we’ve always strived to keep Progenesis QI and Progenesis QI for proteomics vendor agnostic. This allows our users to utilise a single software package to analyse data from all of their instruments, and interface with a wide range of search methods and pathways tools. We achieve this through our plugin architecture, […]

Out now – Progenesis QI for proteomics v3.0

If you attended ASMS 2016, you may have been lucky enough to see a preview of Progenesis QI for proteomics v3.0, and today I’m pleased to announce that it is now available to download. This release is focussed on peptide level information, with a few other treats as well. What’s New? Improved access to peptide […]

Missing values: the hard truths

  “I could burst into tears… I spent weeks of time and effort on sample collection, instrument optimisation, sample running, and data generation from a very expensive LC-MS setup that has the resolving power to find tiny but significant differences between my conditions, only to find that my data analysis led me down a dead […]

Come and see us at ProteoMMX 4.0!

Two years ago, I attended my first conference for Nonlinear, ProteoMMX 3.0. ProteoMMX 4.0 is fast approaching (5th – 7th April, at The Queen Hotel, Chester, UK) and I’m excited to say I’m lucky enough to be attending again. While this will be my second time at ProteoMMX, and one of many conferences I’ve been […]

Missing values: what’s the problem?

Missing values are a major problem in LC-MS based discovery ‘omics analysis and could be the difference between a successful research project and a failure. Whether you run a 3 vs. 3 experiment on a model biological system or a much larger clinical study, missing values will adversely affect the results; some expression changes which […]

Hi-N Quantitation For Clinical Discovery Proteomics

Progenesis QI for proteomics provides untargeted absolute quantitation of all identified proteins via the Hi-N method. This post explains the method and how it can be a useful tool for discovery proteomics in a clinical setting. What is Hi-N? Hi-N is a label-free quantitation method allowing absolute quantitation of all identified proteins in a sample, […]

Come and see us at ASMS 2015!

They say time flies when you’re having fun, so that must explain how it’s already time for ASMS 2015 – the  63rd annual conference for the American Society of Mass Spectrometry. This year it’s being held in St. Louis, MO, in America’s Center Convention Complex, with hospitality suites in the nearby Renaissance Grand Hotel. The […]