Reference number : GC-2017-Q1-03516, amendment number : , agreement type : G, recipient legal name : Lavallée-Adam, Mathieu (University of Ottawa)|Lavallée-Adam, Mathieu (Université d’Ottawa), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Discovery Grants Program - Individual, program name french : Programme de subventions à la découverte - individuelles, program purpose english : Proteins are molecules that govern the behaviour of the cell. To accomplish their function, proteins typically interact with each other to form larger macromolecules called protein complexes. Mass spectrometry allows the identification and quantification of proteins and of their interactions. However, currently used software packages struggle to identify and quantify proteins and interactions that have a low abundance. This makes it difficult to obtain a good understanding of the protein interactions that contribute to the assembly and regulation of protein complexes. In our research program, we will design algorithms that will integrate genomics and interactomics data to facilitate the identification of proteins using mass spectrometry. We will also develop software packages that will identify and quantify proteins while they are being analyzed by mass spectrometry instruments. This will allow us to automatically direct the instrument towards the analysis of lower abundance proteins. Finally, protein interactions that are detected with mass spectrometry can be grouped into networks of interactions. We will analyze such networks of interactions to identify protein complexes and understand which interactions are vital for their assembly, their transport to the proper location in the cell, and their regulation. 
 
 Our research program will produce computational tools that will be designed to be easily integrated with current state-of-the-art mass spectrometry instrumentation and analysis pipelines. They will highlight novel data acquisition strategies for mass spectrometry instruments to identify and quantify more proteins. Our tools will also influence the design of the next generation of instruments. The algorithms we will develop will pave a new way for the design of novel families of computational methods that will use protein interaction networks to gain new biological knowledge. Our approaches will enable biologists and biochemists to get a more comprehensive characterization of the mechanisms at work in the organism under study. Indeed, our software packages will produce the identification and quantification of more proteins and protein interactions. They will allow the mapping of low abundance protein interactions, which are critical to the assembly, transport, and regulation of protein complexes. The characterization of these regulating interactions has a number of applications in many fields related to molecular biology, including agriculture and biofuel production. Mapping such interactions can lead in the future to the discovery of plant resistance pathways to pathogens or frost to increase crop yield in Canada. Similarly, describing such interactions in bacteria could favour a more efficient production of biofuels. Finally, our methods will provide a better understanding of the biology of the cell and of its molecular mechanisms., program purpose french : Proteins are molecules that govern the behaviour of the cell. To accomplish their function, proteins typically interact with each other to form larger macromolecules called protein complexes. Mass spectrometry allows the identification and quantification of proteins and of their interactions. However, currently used software packages struggle to identify and quantify proteins and interactions that have a low abundance. This makes it difficult to obtain a good understanding of the protein interactions that contribute to the assembly and regulation of protein complexes. In our research program, we will design algorithms that will integrate genomics and interactomics data to facilitate the identification of proteins using mass spectrometry. We will also develop software packages that will identify and quantify proteins while they are being analyzed by mass spectrometry instruments. This will allow us to automatically direct the instrument towards the analysis of lower abundance proteins. Finally, protein interactions that are detected with mass spectrometry can be grouped into networks of interactions. We will analyze such networks of interactions to identify protein complexes and understand which interactions are vital for their assembly, their transport to the proper location in the cell, and their regulation. 
 
 Our research program will produce computational tools that will be designed to be easily integrated with current state-of-the-art mass spectrometry instrumentation and analysis pipelines. They will highlight novel data acquisition strategies for mass spectrometry instruments to identify and quantify more proteins. Our tools will also influence the design of the next generation of instruments. The algorithms we will develop will pave a new way for the design of novel families of computational methods that will use protein interaction networks to gain new biological knowledge. Our approaches will enable biologists and biochemists to get a more comprehensive characterization of the mechanisms at work in the organism under study. Indeed, our software packages will produce the identification and quantification of more proteins and protein interactions. They will allow the mapping of low abundance protein interactions, which are critical to the assembly, transport, and regulation of protein complexes. The characterization of these regulating interactions has a number of applications in many fields related to molecular biology, including agriculture and biofuel production. Mapping such interactions can lead in the future to the discovery of plant resistance pathways to pathogens or frost to increase crop yield in Canada. Similarly, describing such interactions in bacteria could favour a more efficient production of biofuels. Finally, our methods will provide a better understanding of the biology of the cell and of its molecular mechanisms., agreement title english : Computational analysis of large-scale proteomics datasets and protein-protein interaction networks, agreement title french : Computational analysis of large-scale proteomics datasets and protein-protein interaction networks, agreement number : RGPIN, agreement value : 155000.0, agreement start date : 2017-05-10, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada