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。

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.