@article{Gruning_Rasche_Rebolledo-Jaramillo-Jupyt_and_Galax-2017,
author = {Grüning, Björn A. and Rasche, Eric and Rebolledo-Jaramillo, 
          Boris and Eberhard, Carl and Houwaart, Torsten and Chilton, 
          John and Coraor, Nate and Backofen, Rolf and Taylor, James 
          and Nekrutenko, Anton},
title = {Jupyter and {Galaxy}: {Easing} entry barriers into complex 
         data analyses for biomedical researchers},
journal = {PLoS Comput Biol},
year = {2017},
doi = {10.1371/journal.pcbi.1005425},
volume = {13},
user = {backofen},
pmid = {28542180},
pages = {e1005425},
number = {5},
issn = {1553-734X},
abstract = {What does it take to convert a heap of sequencing data into 
            a publishable result? First, common tools are employed to 
            reduce primary data (sequencing reads) to a form suitable 
            for further analyses (i.e., the list of variable sites). The 
            subsequent exploratory stage is much more ad hoc and 
            requires the development of custom scripts and pipelines, 
            making it problematic for biomedical researchers. Here, we 
            describe a hybrid platform combining common analysis 
            pathways with the ability to explore data interactively. It 
            aims to fully encompass and simplify the "raw 
            data-to-publication" pathway and make it reproducible.}
}