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Article ; Online: Fast and accurate genome-wide predictions and structural modeling of protein-protein interactions using Galaxy.

Guerler, Aysam / Baker, Dannon / van den Beek, Marius / Gruening, Bjoern / Bouvier, Dave / Coraor, Nate / Shank, Stephen D / Zehr, Jordan D / Schatz, Michael C / Nekrutenko, Anton

BMC bioinformatics

2023 Volume 24, Issue 1, Page(s) 263

Abstract: Background: Protein-protein interactions play a crucial role in almost all cellular processes. Identifying interacting proteins reveals insight into living organisms and yields novel drug targets for disease treatment. Here, we present a publicly ... ...

Abstract	Background: Protein-protein interactions play a crucial role in almost all cellular processes. Identifying interacting proteins reveals insight into living organisms and yields novel drug targets for disease treatment. Here, we present a publicly available, automated pipeline to predict genome-wide protein-protein interactions and produce high-quality multimeric structural models. Results: Application of our method to the Human and Yeast genomes yield protein-protein interaction networks similar in quality to common experimental methods. We identified and modeled Human proteins likely to interact with the papain-like protease of SARS-CoV2's non-structural protein 3. We also produced models of SARS-CoV2's spike protein (S) interacting with myelin-oligodendrocyte glycoprotein receptor and dipeptidyl peptidase-4. Conclusions: The presented method is capable of confidently identifying interactions while providing high-quality multimeric structural models for experimental validation. The interactome modeling pipeline is available at usegalaxy.org and usegalaxy.eu.
MeSH term(s)	Humans ; Protein Interaction Mapping ; RNA, Viral/metabolism ; COVID-19 ; SARS-CoV-2 ; Saccharomyces cerevisiae/metabolism
Chemical Substances	RNA, Viral
Language	English
Publishing date	2023-06-23
Publishing country	England
Document type	Journal Article
ZDB-ID	2041484-5
ISSN	1471-2105 ; 1471-2105
ISSN (online)	1471-2105
ISSN	1471-2105
DOI	10.1186/s12859-023-05389-8
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Fast and accurate genome-wide predictions and structural modeling of protein–protein interactions using Galaxy

Aysam Guerler / Dannon Baker / Marius van den Beek / Bjoern Gruening / Dave Bouvier / Nate Coraor / Stephen D. Shank / Jordan D. Zehr / Michael C. Schatz / Anton Nekrutenko

BMC Bioinformatics, Vol 24, Iss 1, Pp 1-

2023 Volume 13

Abstract: Abstract Background Protein–protein interactions play a crucial role in almost all cellular processes. Identifying interacting proteins reveals insight into living organisms and yields novel drug targets for disease treatment. Here, we present a publicly ...

Abstract	Abstract Background Protein–protein interactions play a crucial role in almost all cellular processes. Identifying interacting proteins reveals insight into living organisms and yields novel drug targets for disease treatment. Here, we present a publicly available, automated pipeline to predict genome-wide protein–protein interactions and produce high-quality multimeric structural models. Results Application of our method to the Human and Yeast genomes yield protein–protein interaction networks similar in quality to common experimental methods. We identified and modeled Human proteins likely to interact with the papain-like protease of SARS-CoV2’s non-structural protein 3. We also produced models of SARS-CoV2’s spike protein (S) interacting with myelin-oligodendrocyte glycoprotein receptor and dipeptidyl peptidase-4. Conclusions The presented method is capable of confidently identifying interactions while providing high-quality multimeric structural models for experimental validation. The interactome modeling pipeline is available at usegalaxy.org and usegalaxy.eu.
Keywords	Protein–protein interactions ; Structural modeling ; Galaxy workflow ; Computer applications to medicine. Medical informatics ; R858-859.7 ; Biology (General) ; QH301-705.5
Language	English
Publishing date	2023-06-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Ready-to-use public infrastructure for global SARS-CoV-2 monitoring.

Maier, Wolfgang / Bray, Simon / van den Beek, Marius / Bouvier, Dave / Coraor, Nathan / Miladi, Milad / Singh, Babita / De Argila, Jordi Rambla / Baker, Dannon / Roach, Nathan / Gladman, Simon / Coppens, Frederik / Martin, Darren P / Lonie, Andrew / Grüning, Björn / Kosakovsky Pond, Sergei L / Nekrutenko, Anton

Nature biotechnology

2021 Volume 39, Issue 10, Page(s) 1178–1179

MeSH term(s)	COVID-19/epidemiology ; COVID-19/virology ; Databases, Factual ; Genome, Viral/genetics ; Humans ; Pandemics ; SARS-CoV-2/pathogenicity
Language	English
Publishing date	2021-09-01
Publishing country	United States
Document type	Letter ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, P.H.S.
ZDB-ID	1311932-1
ISSN	1546-1696 ; 1087-0156
ISSN (online)	1546-1696
ISSN	1087-0156
DOI	10.1038/s41587-021-01069-1
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Article: Freely accessible ready to use global infrastructure for SARS-CoV-2 monitoring.

Maier, Wolfgang / Bray, Simon / van den Beek, Marius / Bouvier, Dave / Coraor, Nathaniel / Miladi, Milad / Singh, Babita / De Argila, Jordi Rambla / Baker, Dannon / Roach, Nathan / Gladman, Simon / Coppens, Frederik / Martin, Darren P / Lonie, Andrew / Grüning, Björn / Kosakovsky Pond, Sergei L / Nekrutenko, Anton

bioRxiv : the preprint server for biology

2021

Abstract: The COVID-19 pandemic is the first global health crisis to occur in the age of big genomic data.Although data generation capacity is well established and sufficiently standardized, analytical capacity is not. To establish analytical capacity it is ... ...

Abstract	The COVID-19 pandemic is the first global health crisis to occur in the age of big genomic data.Although data generation capacity is well established and sufficiently standardized, analytical capacity is not. To establish analytical capacity it is necessary to pull together global computational resources and deliver the best open source tools and analysis workflows within a ready to use, universally accessible resource. Such a resource should not be controlled by a single research group, institution, or country. Instead it should be maintained by a community of users and developers who ensure that the system remains operational and populated with current tools. A community is also essential for facilitating the types of discourse needed to establish best analytical practices. Bringing together public computational research infrastructure from the USA, Europe, and Australia, we developed a distributed data analysis platform that accomplishes these goals. It is immediately accessible to anyone in the world and is designed for the analysis of rapidly growing collections of deep sequencing datasets. We demonstrate its utility by detecting allelic variants in high-quality existing SARS-CoV-2 sequencing datasets and by continuous reanalysis of COG-UK data. All workflows, data, and documentation is available at https://covid19.galaxyproject.org .
Language	English
Publishing date	2021-03-25
Publishing country	United States
Document type	Preprint
DOI	10.1101/2021.03.25.437046
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Article: A reference model for deploying applications in virtualized environments.

Afgan, Enis / Baker, Dannon / Nekrutenko, Anton / Taylor, James

Concurrency and computation : practice & experience

2011 Volume 24, Issue 12, Page(s) 1349–1361

Abstract: Modern scientific research has been revolutionized by the availability of powerful and flexible computational infrastructure. Virtualization has made it possible to acquire computational resources on demand. Establishing and enabling use of these ... ...

Abstract	Modern scientific research has been revolutionized by the availability of powerful and flexible computational infrastructure. Virtualization has made it possible to acquire computational resources on demand. Establishing and enabling use of these environments is essential, but their widespread adoption will only succeed if they are transparently usable. Requiring changes to applications being deployed or requiring users to change how they utilize those applications represent barriers to the infrastructure acceptance. The problem lies in the process of deploying applications so that they can take advantage of the elasticity of the environment and deliver it transparently to users. Here, we describe a reference model for deploying applications into virtualized environments. The model is rooted in the low-level components common to a range of virtualized environments and it describes how to compose those otherwise dispersed components into a coherent unit. Use of the model enables applications to be deployed into the new environment without any modifications, it imposes minimal overhead on management of the infrastructure required to run the application, and yields a set of higher-level services as a byproduct of the component organization and the underlying infrastructure. We provide a fully functional sample application deployment and implement a framework for managing the overall application deployment.
Language	English
Publishing date	2011-08-26
Publishing country	England
Document type	Journal Article
ZDB-ID	2052606-4
ISSN	1532-0634 ; 1532-0626
ISSN (online)	1532-0634
ISSN	1532-0626
DOI	10.1002/cpe.1836
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Article ; Online: No more business as usual: Agile and effective responses to emerging pathogen threats require open data and open analytics.

Baker, Dannon / van den Beek, Marius / Blankenberg, Daniel / Bouvier, Dave / Chilton, John / Coraor, Nate / Coppens, Frederik / Eguinoa, Ignacio / Gladman, Simon / Grüning, Björn / Keener, Nicholas / Larivière, Delphine / Lonie, Andrew / Kosakovsky Pond, Sergei / Maier, Wolfgang / Nekrutenko, Anton / Taylor, James / Weaver, Steven

PLoS pathogens

2020 Volume 16, Issue 8, Page(s) e1008643

Abstract: The current state of much of the Wuhan pneumonia virus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) research shows a regrettable lack of data sharing and considerable analytical obfuscation. This impedes global research cooperation, ... ...

Abstract	The current state of much of the Wuhan pneumonia virus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) research shows a regrettable lack of data sharing and considerable analytical obfuscation. This impedes global research cooperation, which is essential for tackling public health emergencies and requires unimpeded access to data, analysis tools, and computational infrastructure. Here, we show that community efforts in developing open analytical software tools over the past 10 years, combined with national investments into scientific computational infrastructure, can overcome these deficiencies and provide an accessible platform for tackling global health emergencies in an open and transparent manner. Specifically, we use all SARS-CoV-2 genomic data available in the public domain so far to (1) underscore the importance of access to raw data and (2) demonstrate that existing community efforts in curation and deployment of biomedical software can reliably support rapid, reproducible research during global health crises. All our analyses are fully documented at https://github.com/galaxyproject/SARS-CoV-2.
MeSH term(s)	Betacoronavirus/pathogenicity ; COVID-19 ; Coronavirus Infections/virology ; Data Analysis ; Humans ; Pandemics ; Pneumonia, Viral/virology ; Public Health ; SARS-CoV-2 ; Severe Acute Respiratory Syndrome/virology
Keywords	covid19
Language	English
Publishing date	2020-08-13
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2205412-1
ISSN	1553-7374 ; 1553-7366
ISSN (online)	1553-7374
ISSN	1553-7366
DOI	10.1371/journal.ppat.1008643
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Article ; Online: No more business as usual

Dannon Baker / Marius van den Beek / Daniel Blankenberg / Dave Bouvier / John Chilton / Nate Coraor / Frederik Coppens / Ignacio Eguinoa / Simon Gladman / Björn Grüning / Nicholas Keener / Delphine Larivière / Andrew Lonie / Sergei Kosakovsky Pond / Wolfgang Maier / Anton Nekrutenko / James Taylor / Steven Weaver

PLoS Pathogens, Vol 16, Iss 8, p e

Agile and effective responses to emerging pathogen threats require open data and open analytics.

2020 Volume 1008643

Abstract	The current state of much of the Wuhan pneumonia virus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) research shows a regrettable lack of data sharing and considerable analytical obfuscation. This impedes global research cooperation, which is essential for tackling public health emergencies and requires unimpeded access to data, analysis tools, and computational infrastructure. Here, we show that community efforts in developing open analytical software tools over the past 10 years, combined with national investments into scientific computational infrastructure, can overcome these deficiencies and provide an accessible platform for tackling global health emergencies in an open and transparent manner. Specifically, we use all SARS-CoV-2 genomic data available in the public domain so far to (1) underscore the importance of access to raw data and (2) demonstrate that existing community efforts in curation and deployment of biomedical software can reliably support rapid, reproducible research during global health crises. All our analyses are fully documented at https://github.com/galaxyproject/SARS-CoV-2.
Keywords	Immunologic diseases. Allergy ; RC581-607 ; Biology (General) ; QH301-705.5 ; covid19
Subject code	306
Language	English
Publishing date	2020-08-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Experiences with Integrating Custos SecurityServices

Ranawaka, Isuru / Liyanage, Samitha / Baker, Dannon / Mahmoud, Alexandru / Graham, Juleen / Fleury, Terry / Wannipurage, Dimuthu / Ma, Yu / Afgan, Enis / Basney, Jim / Marru, Suresh / Pierce, Marlon

2021

Abstract: Science gateways are user-facing cyberinfrastruc-ture that provide researchers and educators with Web-basedaccess to scientific software, computing, and data resources.Managing user identities, accounts, and permissions are essentialtasks for science ... ...

Abstract	Science gateways are user-facing cyberinfrastruc-ture that provide researchers and educators with Web-basedaccess to scientific software, computing, and data resources.Managing user identities, accounts, and permissions are essentialtasks for science gateways, and gateways likewise must man-age secure connections between their middleware and remoteresources. The Custos project is an effort to build open sourcesoftware that can be operated as a multi-tenanted service thatprovides reliable implementations of common science gatewaycybersecurity needs, including federated authentication, iden-tity management, group and authorization management, andresource credential management. Custos aims further to provideintegrated solutions through these capabilities, delivering end-to-end support for several science gateway usage scenarios. Thispaper examines four deployment scenarios using Custos andassociated extensions beyond previously described work. Thefirst capability illustrated by these scenarios is the need forCustos to provide hierarchical tenant management that allowsmultiple gateway deployments to be federated together andalso to support consolidated, hosted science gateway platformservices. The second capability illustrated by these scenarios is theneed to support service accounts that can support non-browserapplications and agent applications that can act on behalf ofusers on edge resources. We illustrate how the latter can be builtusing Web security standards combined with Custos permissionmanagement mechanisms. Comment: 9 pages, 12 figures
Keywords	Computer Science - Distributed ; Parallel ; and Cluster Computing
Subject code	005
Publishing date	2021-07-08
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Dissemination of scientific software with Galaxy ToolShed.

Blankenberg, Daniel / Von Kuster, Gregory / Bouvier, Emil / Baker, Dannon / Afgan, Enis / Stoler, Nicholas / Taylor, James / Nekrutenko, Anton

Genome biology

2014 Volume 15, Issue 2, Page(s) 403

Abstract: The proliferation of web-based integrative analysis frameworks has enabled users to perform complex analyses directly through the web. Unfortunately, it also revoked the freedom to easily select the most appropriate tools. To address this, we have ... ...

Abstract	The proliferation of web-based integrative analysis frameworks has enabled users to perform complex analyses directly through the web. Unfortunately, it also revoked the freedom to easily select the most appropriate tools. To address this, we have developed Galaxy ToolShed.
MeSH term(s)	Computational Biology ; Internet ; Science ; Software
Language	English
Publishing date	2014-02-20
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2040529-7
ISSN	1474-760X ; 1474-760X
ISSN (online)	1474-760X
ISSN	1474-760X
DOI	10.1186/gb4161
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Freely accessible ready to use global infrastructure for SARS-CoV-2 monitoring

Maier, Wolfgang / Bray, Simon / van den Beek, Marius / Bouvier, Dave / Coraor, Nathaniel / Miladi, Milad / Singh, Babita / Rambla De Argila, Jordi / Baker, Dannon / Roach, Nathan / Gladman, Simon / Coppens, Frederik / Martin, Darren / Lonie, Andrew / Gruning, Bjorn / Kosakovsky Pond, Sergei / Nekrutenko, Anton

bioRxiv

Abstract: The COVID-19 pandemic is the first global health crisis to occur in the age of big genomic data. Although data generation capacity is well established and sufficiently standardized, analytical capacity is not. To establish analytical capacity it is ... ...

Abstract	The COVID-19 pandemic is the first global health crisis to occur in the age of big genomic data. Although data generation capacity is well established and sufficiently standardized, analytical capacity is not. To establish analytical capacity it is necessary to pull together global computational resources and deliver the best open source tools and analysis workflows within a ready to use, universally accessible resource. Such a resource should not be controlled by a single research group, institution, or country. Instead it should be maintained by a community of users and developers who ensure that the system remains operational and populated with current tools. A community is also essential for facilitating the types of discourse needed to establish best analytical practices. Bringing together public computational research infrastructure from the USA, Europe, and Australia, we developed a distributed data analysis platform that accomplishes these goals. It is immediately accessible to anyone in the world and is designed for the analysis of rapidly growing collections of deep sequencing datasets. We demonstrate its utility by detecting allelic variants in high-quality existing SARS-CoV-2 sequencing datasets and by continuous reanalysis of COG-UK data. All workflows, data, and documentation is available at https://covid19.galaxyproject.org.
Keywords	covid19
Language	English
Publishing date	2021-03-25
Publisher	Cold Spring Harbor Laboratory
Document type	Article ; Online
DOI	10.1101/2021.03.25.437046
Database	COVID19

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