Pathway and network analysis in proteomics

Abstract

Proteomics is inherently a systems science that studies not only measured protein and their expressions in a cell, but also the interplay of proteins, protein complexes, signaling pathways, and network modules. There is a rapid accumulation of Proteomics data in recent years. However, Proteomics data are highly variable, with results being sensitive to data preparation methods, sample condition, instrument types, and analytical method. To address this challenge in Proteomics data analysis, we review common approaches developed to incorporate biological function and network topological information. We categorize existing tools into four categories: tools with basic functional information and little topological features (e.g., GO category analysis), tools with rich functional information and little topological features (e.g., GSEA), tools with basic functional information and rich topological features (e.g., Cytoscape), and tools with rich functional information and rich topological features (e.g., PathwayExpress). We review the general application potential of these tools to Proteomics. In addition, we also review tools that can achieve automated learning of pathway modules and features, and tools that help perform integrated network visual analytics.

Identification of altered pathways in hypertrophic cardiomyopathy based on combined data of protein-protein interactions and molecular pathways

“…PPI network analysis differs from pathway analysis in that it uses comprehensive networks to gain system-level biological meanings (Wu and Chen, 2009). To achieve biochemical functions, a combination of protein complexes and signaling pathways are needed (Wu et al, 2014). A pathway association network is a special form of "functional crosstalk networks" constructed from significant PPIs (Wu and Chen, 2012).…”

Grouping miRNAs of similar functions via weighted information content of gene ontology

“…The two most common relationships between two terms are is_a for subclass and part_of for component [8]. GO terms, their relationships and the similarity between two GO trees have been considered in many bioinformatics applications by literature such as for pathway analysis [9], gene network analysis [10], and gene expression research [11]. …”

Proteomic Characterization Reveals That MMP-3 Correlates With Bronchiolitis Obliterans Syndrome Following Allogeneic Hematopoietic Cell and Lung Transplantation

“…MMP-3 was identified as a candidate plasma protein specific for BOS after HCT and lung transplantation via an in-depth tandem MS (MS/MS)–based analysis of plasma combined with a multiscale computational biology process: (1) generation of abundance rate from the comparison of plasma samples taken from BOS and cGVHD without lung involvement, (2) generation of protein–protein interactions pairs in the STRING database and selection of the BOS-relevant proteins by the relevance score Rp, (3) computing penalty scores for unspecific proteins found in proteomics experiments for cancer and cardiovascular diseases, (4) pair-wise baseline transformation and comparison of proteins specific for BOS versus pulmonary infection versus cGVHD without BOS, (5) filtering out proteins found in proteomics experiments that are not related to BOS using domain knowledge provided by experts, and (6) visual exploration of the candidate list using a GeneTerrain computational biology visual analytic software tool (28–30). This process enabled us to reduce a list of hundreds of proteins to about a dozen proteins with little human selection bias.…”