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paper.bib
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% Generated by Paperpile. Check out http://paperpile.com for more information.
% BibTeX export options can be customized via Settings -> BibTeX.
@BOOK{Dunn2010-ik,
title = "Practical Computing for Biologists",
author = "Dunn, Casey and Haddock, Steven HD",
abstract = "Increasingly, scientists find themselves facing exponentially
larger data sets and analyses without suitable tools to deal
with them. Many biologists end up using spreadsheet programs for
most of their data-processing tasks and spend hours clicking
around or copying and pasting, and then repeating the process
for other data files. Practical Computing for Biologists shows
you how to use many freely available computing tools to work
more powerfully and effectively. The book was born out of the
authors' own experience in developing tools for their research
and helping other biologists with their computational problems.
Although many of the techniques are relevant to molecular
bioinformatics, the motivation for the book is much broader,
focusing on topics and techniques that are applicable to a range
of scientific endeavors. Twenty-two chapters organized into six
parts address these topics and more: Searching with regular
expressions The Unix command line Python programming and
debugging Creating and editing graphics Databases Performing
analyses on remote servers Working with electronics While most
of the concepts and examples apply to any operating system, the
main narrative focuses on Mac OS X. Where there are differences
for Windows and Linux users, parallel instructions are provided
in the margin and in an appendix. The book is designed to be
used as a self-guided resource for researchers, a companion book
in a course, or as a primary textbook. Practical Computing for
Biologists will free you from the most frustrating and
time-consuming aspects of data processing so you can focus on
the pleasures of scientific inquiry.",
publisher = "Sinauer Associates, Inc.",
edition = "First edition",
month = nov,
year = 2010,
url = "http://practicalcomputing.org/"
}
@ARTICLE{Wilson2016-kh,
title = "Software Carpentry: lessons learned",
author = "Wilson, Greg",
abstract = "Since its start in 1998, Software Carpentry has evolved from a
week-long training course at the US national laboratories into a
worldwide volunteer effort to improve researchers' computing
skills. This paper explains what we have learned along the way,
the challenges we now face, and our plans for the future.",
journal = "F1000 Research",
volume = 3,
month = jan,
year = 2016,
doi = "10.12688/F1000RESEARCH.3-62.V2"
}
@ARTICLE{Searls2014-ac,
title = "A new online computational biology curriculum",
author = "Searls, David B",
abstract = "A recent proliferation of Massive Open Online Courses (MOOCs) and
other web-based educational resources has greatly increased the
potential for effective self-study in many fields. This article
introduces a catalog of several hundred free video courses of
potential interest to those wishing to expand their knowledge of
bioinformatics and computational biology. The courses are
organized into eleven subject areas modeled on university
departments and are accompanied by commentary and career advice.",
journal = "PLoS Computational Biology",
volume = 10,
number = 6,
pages = "e1003662",
month = jun,
year = 2014,
doi = "10.1371/journal.pcbi.1003662"
}
@BOOK{Felsenstein2003-wm,
title = "Inferring Phylogenies",
author = "Felsenstein, Joseph",
abstract = "Phylogenies (evolutionary trees) are basic to thinking about and
analyzing differences between species. Statistical,
computational, and algorithmic work on them has been ongoing for
four decades, with great advances in understanding. Yet no book
has summarized this work until now. Inferring Phylogenies
explains clearly the assumptions and logic of making inferences
about phylogenies, and using them to make inferences about
evolutionary processes. It is an essential text and reference
for anyone who wants to understand how phylogenies are
reconstructed and how they are used. As phylogenies are inferred
with various kinds of data, this book concentrates on some of
the central ones: discretely coded characters, molecular
sequences, gene frequencies, and quantitative traits. Also
covered are restriction sites, RAPDs, and microsatellites.
Inferring Phylogenies is intended for graduate-level courses,
assuming some knowledge of statistics, mathematics (calculus and
fundamental matrix algebra), molecular sequences, and
quantitative genetics.",
publisher = "Sinauer Associates",
edition = "Second edition",
month = sep,
year = 2003
}
@BOOK{Durbin1998-ru,
title = "Biological Sequence Analysis: Probabilistic Models of Proteins
and Nucleic Acids",
author = "Durbin, Richard and Eddy, Sean R and Krogh, Anders and
Mitchison, Graeme",
abstract = "Probablistic models are becoming increasingly important in
analyzing the huge amount of data being produced by large-scale
DNA-sequencing efforts such as the Human Genome Project. For
example, hidden Markov models are used for analyzing biological
sequences, linguistic-grammar-based probabilistic models for
identifying RNA secondary structure, and probabilistic
evolutionary models for inferring phylogenies of sequences from
different organisms. This book gives a unified, up-to-date and
self-contained account, with a Bayesian slant, of such methods,
and more generally to probabilistic methods of sequence
analysis. Written by an interdisciplinary team of authors, it is
accessible to molecular biologists, computer scientists, and
mathematicians with no formal knowledge of the other fields, and
at the same time presents the state of the art in this new and
important field.",
publisher = "Cambridge University Press",
edition = "First edition",
month = may,
year = 1998,
}
@ARTICLE{Searls2012-ab,
title = "An online bioinformatics curriculum",
author = "Searls, David B",
abstract = "Online learning initiatives over the past decade have become
increasingly comprehensive in their selection of courses and
sophisticated in their presentation, culminating in the recent
announcement of a number of consortium and startup activities
that promise to make a university education on the internet, free
of charge, a real possibility. At this pivotal moment it is
appropriate to explore the potential for obtaining comprehensive
bioinformatics training with currently existing free video
resources. This article presents such a bioinformatics curriculum
in the form of a virtual course catalog, together with editorial
commentary, and an assessment of strengths, weaknesses, and
likely future directions for open online learning in this field.",
journal = "PLoS Computational Biology",
volume = 8,
number = 9,
pages = "e1002632",
month = sep,
year = 2012,
doi = "10.1371/journal.pcbi.1002632"
}