@inbook{ea5fecb9bcc941a3a6d161376a6eb832,
title = "Automated computational inference of multi-protein assemblies from biochemical co-purification data",
abstract = "Biology has amassed a wealth of information about the function of a multitude of protein-coding genes across species. The challenge now is to understand how all these proteins work together to form a living organism, and a crucial step for gaining this knowledge is a complete description of the molecular “wiring circuits” that underlie cellular processes. In this chapter, we describe a general computational framework for predicting multi-protein assemblies from biochemical co-fractionation data.",
keywords = "Bioinformatics, Cytoscape, Docker, Machine learning, Protein complex prediction, Protein interaction prediction, Protein-protein interaction, Python, Systems biology",
author = "Florian Goebels and Lucas Hu and Gary Bader and Andrew Emili",
note = "Publisher Copyright: {\textcopyright} 2018, Springer Science+Business Media, LLC, part of Springer Nature.",
year = "2018",
doi = "10.1007/978-1-4939-7759-8\_25",
language = "English (US)",
series = "Methods in Molecular Biology",
publisher = "Humana Press Inc.",
pages = "391--399",
booktitle = "Methods in Molecular Biology",
}