From proteome lists to biological impact– tools and strategies for the analysis of large MS data sets

Abstract

MS has become a method-of-choice for proteome analysis, generating large data sets, which reflect proteome-scale protein-protein interaction and PTM networks. However, while a rapid growth in large-scale proteomics data can be observed, the sound biological interpretation of these results clearly lags behind. Therefore, combined efforts of bioinformaticians and biologists have been made to develop strategies and applications to help experimentalists perform this crucial task. This review presents an overview of currently available analytical strategies and tools to extract biologically relevant information from large protein lists. Moreover, we also present current research publications making use of these tools as examples of how the presented strategies may be incorporated into proteomic workflows. Emphasis is placed on the analysis of Gene Ontology terms, interaction networks, biological pathways and PTMs. In addition, topics including domain analysis and text mining are reviewed in the context of computational analysis of proteomic results. We expect that these types of analyses will significantly contribute to a deeper understanding of the role of individual proteins, protein networks and pathways in complex systems.

ApoptoProteomics, an Integrated Database for Analysis of Proteomics Data Obtained from Apoptotic Cells

“…Functional interactions can be sharing common substrates in a pathway, regulating each other transcriptionally or indirect binding through participation in larger complexes (50). Although detecting these interactions through PPI analysis previously has suffered from problems with identifier mapping (51), iRefIndex assigns Sequence Global Unique Identifiers (SEGUID) to every protein based on the protein sequence to ensure that proteins with the exact same sequence will be represented only once.…”

Bottom-Up Mass Spectrometry–Based Proteomics as an Investigative Analytical Tool for Discovery and Quantification of Proteins in Biological Samples

“…To interpret the data correctly and obtain a deeper understanding of the biological systems, novel bioinformatics tools are required to ''mine'' the proteomics data. In addition to commercially available tools such as GeneGo and Ingenuity Pathway Analysis, as pointed out in a recent article, 26 freely available software tools such as Gene Ontology and Kyoto Encyclopedia of Genes and Genomes are currently widely used to extract biologically relevant information on signaling pathways, biological networks, and proteinprotein interactions from these large data sets.…”

The persisting effects of electroconvulsive stimulation on the hippocampal proteome

“…Protein accession numbers were converted to gene identifiers allowing biological meaning to be extracted from the lists of proteins detected following mass spectrometry (Huang da et al, 2009a(Huang da et al, , 2009b. DAVID was used to search the Gene Ontology (GO) database (Gene Ontology Consortium, 2001;Malik et al, 2010). The GO terms cellular component FAT, biological processes FAT and molecular function FAT were selected.…”