作者
Matthew Chambers,Brendan MacLean,Robert Burke,Dario Amodei,Daniel Ruderman,Steffen Neumann,Laurent Gatto,Bernd Fischer,Brian Pratt,Jarrett D. Egertson,Katherine Hoff,Darren Kessner,Natalie Tasman,Nicholas Shulman,Barbara Frewen,Tahmina A Baker,Mi‐Youn Brusniak,Christopher Paulse,David M. Creasy,Lisa Flashner,Kian Kani,Chris Moulding,Sean L. Seymour,Lydia M. Nuwaysir,Brent Lefebvre,Frank E. Kuhlmann,Joe Roark,Rainer Paape,Detlev Suckau,Tina Hemenway,Andreas Hühmer,James Langridge,B. Connolly,Trey Chadick,Krisztina Holly,Josh Eckels,Eric W. Deutsch,Robert L. Moritz,Jonathan E. Katz,David B. Agus,Michael J. MacCoss,David L. Tabb,Parag Mallick
摘要
Mass-spectrometry-based proteomics has become an important component of biological research. Numerous proteomics methods have been developed to identify and quantify the proteins in biological and clinical samples1, identify pathways affected by endogenous and exogenous perturbations2, and characterize protein complexes3. Despite successes, the interpretation of vast proteomics datasets remains a challenge. There have been several calls for improvements and standardization of proteomics data analysis frameworks, as well as for an application-programming interface for proteomics data access4,5. In response, we have developed the ProteoWizard Toolkit, a robust set of open-source, software libraries and applications designed to facilitate proteomics research. The libraries implement the first-ever, non-commercial, unified data access interface for proteomics, bridging field-standard open formats and all common vendor formats. In addition, diverse software classes enable rapid development of vendor-agnostic proteomics software. Additionally, ProteoWizard projects and applications, building upon the core libraries, are becoming standard tools for enabling significant proteomics inquiries.