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

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 ar...

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Autores principales: Boue, Stephanie, Fields, Brett, Hoeng, Julia, Park, Jennifer, Peitsch, Manuel C., Schlage, Walter K., Talikka, Marja, Binenbaum, Ilona, Bondarenko, Vladimir, Bulgakov, Oleg V., Cherkasova, Vera, Diaz-Diaz, Norberto, Fedorova, Larisa, Guryanova, Svetlana, Guzova, Julia, Igorevna Koroleva, Galina, Kozhemyakina, Elena, Kumar, Rahul, Lavid, Noa, Lu, Qingxian, Menon, Swapna, Ouliel, Yael, Peterson, Samantha C., Prokhorov, Alexander, Sanders, Edward, Schrier, Sarah, Schwaitzer Neta, Golan, Shvydchenko, Irina, Tallam, Aravind, Villa-Fombuena, Gema, Wu, John, Yudkevich, Ilya, Zelikman, Mariya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000Research 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4350443/
https://www.ncbi.nlm.nih.gov/pubmed/25767696
http://dx.doi.org/10.12688/f1000research.5984.2
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author Boue, Stephanie
Fields, Brett
Hoeng, Julia
Park, Jennifer
Peitsch, Manuel C.
Schlage, Walter K.
Talikka, Marja
Binenbaum, Ilona
Bondarenko, Vladimir
Bulgakov, Oleg V.
Cherkasova, Vera
Diaz-Diaz, Norberto
Fedorova, Larisa
Guryanova, Svetlana
Guzova, Julia
Igorevna Koroleva, Galina
Kozhemyakina, Elena
Kumar, Rahul
Lavid, Noa
Lu, Qingxian
Menon, Swapna
Ouliel, Yael
Peterson, Samantha C.
Prokhorov, Alexander
Sanders, Edward
Schrier, Sarah
Schwaitzer Neta, Golan
Shvydchenko, Irina
Tallam, Aravind
Villa-Fombuena, Gema
Wu, John
Yudkevich, Ilya
Zelikman, Mariya
author_facet Boue, Stephanie
Fields, Brett
Hoeng, Julia
Park, Jennifer
Peitsch, Manuel C.
Schlage, Walter K.
Talikka, Marja
Binenbaum, Ilona
Bondarenko, Vladimir
Bulgakov, Oleg V.
Cherkasova, Vera
Diaz-Diaz, Norberto
Fedorova, Larisa
Guryanova, Svetlana
Guzova, Julia
Igorevna Koroleva, Galina
Kozhemyakina, Elena
Kumar, Rahul
Lavid, Noa
Lu, Qingxian
Menon, Swapna
Ouliel, Yael
Peterson, Samantha C.
Prokhorov, Alexander
Sanders, Edward
Schrier, Sarah
Schwaitzer Neta, Golan
Shvydchenko, Irina
Tallam, Aravind
Villa-Fombuena, Gema
Wu, John
Yudkevich, Ilya
Zelikman, Mariya
collection PubMed
description 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 processes 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 ( https://bionet.sbvimprover.com/) and to add mechanistic detail, as well as 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 Signaling, Macrophage Signaling, and Th1-Th2 Signaling. We describe an 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.
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spelling pubmed-43504432015-03-11 Enhancement of COPD biological networks using a web-based collaboration interface Boue, Stephanie Fields, Brett Hoeng, Julia Park, Jennifer Peitsch, Manuel C. Schlage, Walter K. Talikka, Marja Binenbaum, Ilona Bondarenko, Vladimir Bulgakov, Oleg V. Cherkasova, Vera Diaz-Diaz, Norberto Fedorova, Larisa Guryanova, Svetlana Guzova, Julia Igorevna Koroleva, Galina Kozhemyakina, Elena Kumar, Rahul Lavid, Noa Lu, Qingxian Menon, Swapna Ouliel, Yael Peterson, Samantha C. Prokhorov, Alexander Sanders, Edward Schrier, Sarah Schwaitzer Neta, Golan Shvydchenko, Irina Tallam, Aravind Villa-Fombuena, Gema Wu, John Yudkevich, Ilya Zelikman, Mariya F1000Res Research Article 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 processes 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 ( https://bionet.sbvimprover.com/) and to add mechanistic detail, as well as 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 Signaling, Macrophage Signaling, and Th1-Th2 Signaling. We describe an 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. F1000Research 2015-05-20 /pmc/articles/PMC4350443/ /pubmed/25767696 http://dx.doi.org/10.12688/f1000research.5984.2 Text en Copyright: © 2015 The sbv IMPROVER project team (in alphabetical order) et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Boue, Stephanie
Fields, Brett
Hoeng, Julia
Park, Jennifer
Peitsch, Manuel C.
Schlage, Walter K.
Talikka, Marja
Binenbaum, Ilona
Bondarenko, Vladimir
Bulgakov, Oleg V.
Cherkasova, Vera
Diaz-Diaz, Norberto
Fedorova, Larisa
Guryanova, Svetlana
Guzova, Julia
Igorevna Koroleva, Galina
Kozhemyakina, Elena
Kumar, Rahul
Lavid, Noa
Lu, Qingxian
Menon, Swapna
Ouliel, Yael
Peterson, Samantha C.
Prokhorov, Alexander
Sanders, Edward
Schrier, Sarah
Schwaitzer Neta, Golan
Shvydchenko, Irina
Tallam, Aravind
Villa-Fombuena, Gema
Wu, John
Yudkevich, Ilya
Zelikman, Mariya
Enhancement of COPD biological networks using a web-based collaboration interface
title Enhancement of COPD biological networks using a web-based collaboration interface
title_full Enhancement of COPD biological networks using a web-based collaboration interface
title_fullStr Enhancement of COPD biological networks using a web-based collaboration interface
title_full_unstemmed Enhancement of COPD biological networks using a web-based collaboration interface
title_short Enhancement of COPD biological networks using a web-based collaboration interface
title_sort enhancement of copd biological networks using a web-based collaboration interface
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4350443/
https://www.ncbi.nlm.nih.gov/pubmed/25767696
http://dx.doi.org/10.12688/f1000research.5984.2
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