Computational analysis of large-scale proteomics datasets and protein-protein interaction networks

蛋白质是控制细胞行为的分子。为了完成它们的功能，蛋白质通常相互作用形成更大的大分子，称为蛋白质复合物。质谱法可以鉴定和定量蛋白质及其相互作用。然而，目前使用的软件包很难识别和量化具有低丰度的蛋白质和相互作用。这使得很难很好地理解有助于蛋白质复合物组装和调节的蛋白质相互作用。在我们的研究计划中，我们将设计算法，将整合基因组学和相互作用组学数据，以促进使用质谱法识别蛋白质。我们还将开发软件包，将确定和量化蛋白质，而他们正在分析的质谱仪器。这将使我们能够自动引导仪器分析低丰度蛋白质。最后，用质谱法检测的蛋白质相互作用可以被分组为相互作用网络。我们将分析这种相互作用的网络，以识别蛋白质复合物，并了解哪些相互作用对于它们的组装，它们在细胞中的适当位置的运输以及它们的调节至关重要。 我们的研究计划将产生计算工具，这些工具将被设计为易于与当前最先进的质谱仪器和分析管道集成。他们将重点介绍质谱仪器的新型数据采集策略，以识别和定量更多的蛋白质。我们的工具也将影响下一代仪器的设计。我们将开发的算法将为设计新的计算方法家族铺平新的道路，这些计算方法将使用蛋白质相互作用网络来获得新的生物学知识。我们的方法将使生物学家和生物化学家能够更全面地表征所研究的生物体中的工作机制。事实上，我们的软件包将产生更多的蛋白质和蛋白质相互作用的识别和定量。它们将允许绘制低丰度蛋白质相互作用的图谱，这对蛋白质复合物的组装、运输和调节至关重要。这些调节相互作用的表征在与分子生物学相关的许多领域中具有许多应用，包括农业和生物燃料生产。绘制这种相互作用可以在未来发现植物对病原体或霜冻的抗性途径，以增加加拿大的作物产量。同样，描述细菌中的这种相互作用可能有助于更有效地生产生物燃料。最后，我们的方法将提供一个更好的理解细胞的生物学及其分子机制。

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.