E
Enis Afgan
Researcher at Johns Hopkins University
Publications - 75
Citations - 6420
Enis Afgan is an academic researcher from Johns Hopkins University. The author has contributed to research in topics: Cloud computing & Grid computing. The author has an hindex of 18, co-authored 73 publications receiving 4585 citations. Previous affiliations of Enis Afgan include University of Alabama at Birmingham & Victorian Life Sciences Computation Initiative.
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Journal ArticleDOI
BioBlend: automating pipeline analyses within Galaxy and CloudMan.
TL;DR: BioBlend makes it easy for bioinformaticians to automate end-to-end large data analysis, from scratch, in a way that is highly accessible to collaborators, by allowing them to both provide the required infrastructure and automate complex analyses over large datasets within the familiar Galaxy environment.
Journal ArticleDOI
Community-driven development for computational biology at Sprints, Hackathons and Codefests.
Steffen Möller,Enis Afgan,Michael Banck,Raoul J. P. Bonnal,Timothy F. Booth,John Chilton,Peter J. A. Cock,Markus Gumbel,Nomi L. Harris,Richard Holland,Matúš Kalaš,László Kaján,Eri Kibukawa,David R. Powel,David R. Powel,Pjotr Prins,Jacqueline Quinn,Olivier Sallou,Francesco Strozzi,Torsten Seemann,Torsten Seemann,Clare Sloggett,Stian Soiland-Reyes,William Spooner,Sascha Steinbiss,Andreas Tille,Anthony J. Travis,Roman Valls Guimera,Toshiaki Katayama,Brad Chapman +29 more
TL;DR: Hackathons, Codefests and Sprints share a stimulating atmosphere that encourages participants to jointly brainstorm and tackle problems of shared interest in a self-driven proactive environment, as well as providing an opportunity for new participants to get involved in collaborative projects.
Journal ArticleDOI
CloudMan as a platform for tool, data, and analysis distribution
TL;DR: The presented solution improves accessibility of cloud resources, tools, and data to the level of an individual researcher and contributes toward reproducibility and transparency of research solutions.
Journal ArticleDOI
Erratum: The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2020 update (Nucleic Acids Research (2020) DOI: 10.1093/nar/gkaa434)
Book ChapterDOI
Galaxy: A Gateway to Tools in e-Science
TL;DR: Galaxy abstracts individual tools behind a consistent and easy-to-use web interface to enable advanced data analysis that requires no informatics expertise, thus supporting tool developers, as well as transparent and reproducible communication of computationally intensive analyses.