bibliography.bib

@article{perkel2020,
	title = {Streamline your writing {\textemdash} and collaborations {\textemdash} with these reference managers},
	author = {{Perkel}, {Jeffrey M.}},
	year = {2020},
	month = {09},
	date = {2020-09-01},
	journal = {Nature},
	pages = {149--150},
	volume = {585},
	number = {7823},
	doi = {10.1038/d41586-020-02491-2},
	url = {http://dx.doi.org/10.1038/d41586-020-02491-2},
	langid = {en}
}

@article{perkel2018,
	title = {Why Jupyter is data scientists{\textquoteright} computational notebook of choice},
	author = {{Perkel}, {Jeffrey M.}},
	year = {2018},
	month = {10},
	date = {2018-10-30},
	journal = {Nature},
	pages = {145--146},
	volume = {563},
	number = {7729},
	doi = {10.1038/d41586-018-07196-1},
	url = {http://dx.doi.org/10.1038/d41586-018-07196-1},
	langid = {en}
}

@article{perkel2018a,
	title = {A toolkit for data transparency takes shape},
	author = {{Perkel}, {Jeffrey M.}},
	year = {2018},
	month = {08},
	date = {2018-08},
	journal = {Nature},
	pages = {513--515},
	volume = {560},
	number = {7719},
	doi = {10.1038/d41586-018-05990-5},
	url = {http://dx.doi.org/10.1038/d41586-018-05990-5},
	langid = {en}
}

@article{perkel2021,
	title = {Reactive, reproducible, collaborative: computational notebooks evolve},
	author = {{Perkel}, {Jeffrey M.}},
	year = {2021},
	month = {05},
	date = {2021-05-03},
	journal = {Nature},
	pages = {156--157},
	volume = {593},
	number = {7857},
	doi = {10.1038/d41586-021-01174-w},
	url = {http://dx.doi.org/10.1038/d41586-021-01174-w},
	langid = {en}
}

@article{shen2014,
	title = {Interactive notebooks: Sharing the code},
	author = {{Shen}, {Helen}},
	year = {2014},
	month = {11},
	date = {2014-11},
	journal = {Nature},
	pages = {151--152},
	volume = {515},
	number = {7525},
	doi = {10.1038/515151a},
	url = {http://dx.doi.org/10.1038/515151a},
	langid = {en}
}



@book{xieMarkdownCookbook2020,
  title = {R {{Markdown Cookbook}}},
  author = {Xie, Yihui and Dervieux, Christophe and Riederer, Emily},
  year = {2020},
  month = oct,
  series = {The {{R Series}}},
  publisher = {{Chapman and Hall/CRC}},
  abstract = {This book showcases short, practical examples of lesser-known tips and tricks to helps users get the most out of these tools. After reading this book, you will understand how R Markdown documents are transformed from plain text and how you may customize nearly every step of this processing. For example, you will learn how to dynamically create content from R code, reference code in other documents or chunks, control the formatting with customer templates, fine-tune how your code is processed, and incorporate multiple languages into your analysis.},
  isbn = {978-0-367-56383-7},
  langid = {english},
  file = {/Users/jpn8428/Zotero/storage/SL4UARXZ/rmarkdown-cookbook.html}
}