“Cloud-based” has become a popular term. Yet we find a lot of people don’t really understand what it means. Maybe that is because it means different things to different people. So, let’s clarify what it means to us at ProteoWorker. “Cloud-based” means that all the computing power needed to perform analysis is provided by a huge cluster of remote machines that we’ll call “cloud workers”. Cloud workers come in all different shapes and sizes and are called up to work as needed to make analysis fast and efficient. Literally hundreds to thousands of cloud workers can be called up to work in parallel on demand.
What does that mean for you? It means you are no longer limited by your local machine’s memory or processing power. It means you have a sea of computers at your fingertips, ready and waiting to do your bidding. It means your analysis will be done more quickly. Sounds great, right? That’s what we thought.
So, the take home is that “cloud-based” means that the computing can done remotely and is scalable to your computing problem.
In this case, proteomic simply means study of proteins (it could be full proteome or a specific subproteome, whatever biology you may be interested in). We added it in our description to make sure you knew that we aren’t dealing with lipids, carbohydrates or metabolites except as modifications of proteins. ProteoWorker has been built around data-dependent proteomic toolss, but may be expanded to include data independent analysis. (Please take our survey to help steer ProteoWorker!)
A data pipeline is just a series of analysis steps. Our pipeline integrates multiple proteomic data processing steps. You can start with raw, unsearched OR searched MS/MS files. Peptide-spectrum-matches are then scored for accuracy, filtered, assembled and dynamically displayed for user interrogation and analysis. Our pipeline simplifies and expedites data processing from raw data to publication quality results and will work for ANY vendor.
Proteoworker is a seamless proteomic pipeline designed to simplify your experience and provide powerful analysis and visualization tools, making in-depth proteomic analysis easier and faster.