Journal
EXPERT REVIEW OF PROTEOMICS
Volume 14, Issue 10, Pages 845-855Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/14789450.2017.1374179
Keywords
Macromolecular complex; functional proteomics; interactome; machine learning; mass spectrometry; network; prediction; protein interaction; scoring; systems biology
Categories
Funding
- Canadian Foundation for Innovation
- Genome Canada
- Ontario Genomics Institute
- Canadian Institutes for Health Research
- University of Toronto Open Graduate Student Fellowship
- Manitoba Research Health Council Establishment Grant
- University of Manitoba
Ask authors/readers for more resources
Overview: Elucidation of the networks of physical (functional) interactions present in cells and tissues is fundamental for understanding the molecular organization of biological systems, the mechanistic basis of essential and disease-related processes, and for functional annotation of previously uncharacterized proteins (via guilt-by-association or -correlation). After a decade in the field, we felt it timely to document our own experiences in the systematic analysis of protein interaction networks.Areas covered: Researchers worldwide have contributed innovative experimental and computational approaches that have driven the rapidly evolving field of functional proteomics'. These include mass spectrometry-based methods to characterize macromolecular complexes on a global-scale and sophisticated data analysis tools - most notably machine learning - that allow for the generation of high-quality protein association maps.Expert commentary: Here, we recount some key lessons learned, with an emphasis on successful workflows, and challenges, arising from our own and other groups' ongoing efforts to generate, interpret and report proteome-scale interaction networks in increasingly diverse biological contexts.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available