Enhancement of COPD biological networks using a web-based collaboration interface

Stephanie Boue, Brett Fields, Julia Hoeng, Jennifer Park, Manuel C. Peitsch, Walter K. Schlage, Marja Talikka, Ilona Binenbaum, Vladimir Bondarenko, Oleg V. Bulgakov, Vera Cherkasova, Norberto Diaz-Diaz (+21 others)
2015 F1000Research  
Discuss this article (0) Comments 3 2 1 Abstract The construction and application of biological network models is an approach that offers a holistic way to understand biological processes involved in disease. Chronic obstructive pulmonary disease (COPD) is a progressive inflammatory disease of the airways for which therapeutic options currently are limited after diagnosis, even in its earliest stage. COPD network models are important tools to better understand the biological components and
more » ... sses underlying initial disease development. With the increasing amounts of literature that are now available, crowdsourcing approaches offer new forms of collaboration for researchers to review biological findings, which can be applied to the construction and verification of complex biological networks. We report the construction of 50 biological network models relevant to lung biology and early COPD using an integrative systems biology and collaborative crowd-verification approach. By combining traditional literature curation with a data-driven approach that predicts molecular activities from transcriptomics data, we constructed an initial COPD network model set based on a previously published non-diseased lung-relevant model set. The crowd was given the opportunity to enhance and refine the networks on a website ( ) and to add mechanistic detail, as well as https://bionet.sbvimprover.com/ critically review existing evidence and evidence added by other users, so as to enhance the accuracy of the biological representation of the processes captured in the networks. Finally, scientists and experts in the field discussed and refined the networks during an in-person jamboree meeting. Here, we describe examples of the changes made to three of these networks: Neutrophil , , and . We describe an Signaling Macrophage Signaling Th1-Th2 Signaling innovative approach to biological network construction that combines literature and data mining and a crowdsourcing approach to generate a comprehensive set of COPD-relevant models that can be used to help understand the mechanisms related to lung pathobiology. Registered users of the website can freely browse and download the networks. Julia Hoeng ( ) Corresponding author: Julia.Hoeng@pmi.com The sbv IMPROVER project team (in alphabetical order), Boue S, Fields B How to cite this article: et al. Enhancement of COPD biological 2015, :32 (doi: networks using a web-based collaboration interface [version 2; referees: 3 approved] F1000Research 4 ) Boundaries Build "Literature" network A. Literature network building B. Dataset-based extension and publication Computational Predictions Data set-based extension (RCR) Vet link to "literature" network Final network Publish Version 1.0 of 90 non-diseased network models published in 5 manuscripts C. Preparation of networks for Network Veri cation Challenge Version 1.0 of network models in scienti c literature BEL to openBEL conversion Consolidate/merge network models Publish on bionet website PubMed Abstract | Publisher Full Text | Free Full Text 2. Kanehisa M, Goto S, Sato Y, et al.: Data, information, knowledge and principle: back to metabolism in KEGG. 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doi:10.12688/f1000research.5984.1 pmid:25767696 pmcid:PMC4350443 fatcat:f3eihadqrvftbjtwljegaa3ovu