Proteomics:Work Packages

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The contribution of groups into workpackages

Work Package 1 (WP1)

WP1 involves all developments related to information management and infrastructure.

The lead scientists are Rainer Breitling (RUG) and Morris Swertz (RUG; day-to-day project management), and contributing scientists are George Byelas (RUG), User:Andrew Stubbs (EMC), and Henk van den Toorn (UU).

This is an overarching/unifying WP that will use state-of-the-art web- and grid-based mechanisms to make the software, tools and functionalities developed in the other WPs accessible to the broadest audience of researchers in a robust and standardized way. Specifically, this WP has the following aims:

  • provide generic tools for data management, to define and use already existing proteomics data standards (e.g. mzData.xml, mzXML).
  • provide tools for organizing data processing and evaluation using the Taverna workflow management system.
  • provide generic tools for easier web services implementation.
  • development a structured approach towards the design and management of bioinformatics experiments and data structures.

This WP is based on the expertise of Morris Swertz in data and software structure management and the extensive software platform developed by the group of Rainer Breitling; it uses MOLGENIS for genomic data analysis, and benefits from the collaboration with the Taverna development team aimed at incorporating data and software management into the Taverna workflow environment. The WP will benefit from the expertise on proteomics data standards and PRIDE proteomics database development of Henk van den Toorn and from the expertise in implementing biomarker informatics and decision support discovery platform of User:Andrew Stubbs. This WP will provide an implementation of use cases into the MOLGENIS/Taverna environment, based on already existing proteomics pipelines (e.g., LC-MS data processing pipelines developed in the groups of Morris Swertz, Rainer Breitling and Péter Horvatovich) and the integrated Proteomics Analysis Service intended to be developed by User:Andrew Stubbs.

Work Package 2 (WP2)

WP2 includes research concerning mass spectrometry based data processing. The lead researcher is Twan America (WUR) and the contributing researchers are Péter Horvatovich (RUG), Bas van Breukelen (UU) and User:Mandalina Drugan (UU). This work package will deal with algorithms and methods for processing raw mass spectrometric data and will include methods like peak detection methods, raw data filtering, alignment algorithms for multiple data types, protein and peptide quantification algorithms for label-free and stable isotope labeled LC-MS data, normalization and standardization techniques, and various evaluation tools to asses the quality of data processing modules. Enhancing protein identification and matching label-free LC-MS with MS/MS information will be also part of the WP2. This WP is based on the label-free data processing workflows and modules already under development in the groups of Rainer Breitling, Péter Horvatovich in collaboration with Frank Suits (IBM, USA) and Twan America, on LC-MS data processing frameworks for modularizing and interconnecting several freely available open source workflows (e.g. OpenMS, Superhirn etc.) currently under development by Rainer Breitling and Péter Horvatovich, and on de novo MS/MS protein identification expertise of User:Mandalina Drugan and Bas van Breukelen. Important novel developments of this WP will be new data processing modules with missing capabilities (e.g., retention time normalization algorithms using machine learning approaches), evaluation and assessment of data processing modules (e.g, accuracy of time alignment, normalization) and new de novo MS/MS protein identification algorithms using machine learning techniques. This WP will use the data and software management infrastructure developed in WP1 and will provide high quality annotated and integrated data for knowledge discovery taking place in WP3.

Work Package 3 (WP3)

WP3 contains all research related to biological knowledge extraction, functional annotation and classification. The lead scientist is User:Huub Hoefsloot (UvA) and contributing scientists are User:Andrew Stubbs (EMC), User:Theo Luider (EMC) and Antoine van Kampen (AMC). WP3 will deal with bioinformatics tools for evaluating processed mass spectrometric data for biological knowledge discovery and will contain different classification tools, e.g. for biomarker research, tools to visualize, interpret and analyze protein pathways, integration of proteomics data into protein-protein interaction networks and other types of biological networks, inference of new protein-protein interaction (sub)network, and new approaches for proteomics data annotation. The work of this WP is based on the expertise in statistical interpretation and evaluation of 'omics' data of the group of User:Huub Hoefsloot, in chemometrics and proteomics-related bioinformatics expertise of the group of Antoine van Kampen, in implementing biomarker informatics and decision support discovery platforms of User:Andrew Stubbs, and will benefit from the proteomics expertise of the group of User:Theo Luider. This WP will provide a Statistical Prediction Module containing already existing statistical methods and new proteomics related statistical developments (e.g. time series analysis), an integrated Proteomics Analysis Service task containing GUI's for a pathway knowledge management module, a functional analysis module for biological knowledge discovery and a pathway and network visualization part. WP3 will use tailor-made data and software management tools in the MOLGENIS/Taverna framework developed in WP1 and will extensively use processed and annotated data provided by WP2. Majority of specific tools developed will be open source, however the intellectual properties and commercialization right will belong to the institutions that have developed the tools. However the intellectual property of the framework of NBPP will belong to NGI.



See also the Portal page for the proteomics task force