Preface
This monograph presents an introduction to using the Wolfram Language for
Bioinformatics. The content stems from many years of using the Wolfram
Language, previously as Mathematica, in different fields: initially as an under-
graduate, doing differential equations homework as a freshman, nuclear structure
calculations, as a graduate student in theoretical physics calculating Feynman
diagrams and working out quantum dynamics in a system, as a postdoc in genetics
initially parsing database information and mapped data, and expanding analysis in
my own laboratory to mass spectrometry, transcriptomes, protein data, microarray
analysis, and more. The intent of this material is to put together various training
problems I have used, primarily to get students to begin thinking about a problem,
and really look at the details of their solution.
The work builds gradually from basic concepts and introduction of the Wolfram
Language and coding paradigms in Mathematica, to buil ding explicit working
examples derived from typical research appli cations using Wolfram Language
code. The topics were driven from the daily bioinformatics needs of a broad
audience that I have come to contact with during our research endeavors in
genetics: the experimental user looking to understand and visualize their data, a
beginner bioinformatician acquiring coding expertise in providing biological
research solutions, and the practicing expert bioinformatician working on omics
that wishes to expand their toolset to utilizing the Wolfram Language, particularly
for prototyping solutions.
The Wolfram Language offers an alternative coding solution, particularly for
physical or mathematical scien ces researchers that may wish to expand their
investigation repertoire to include bioinformatics. While R and lately Python may
be the languages of choice in bioinformatics for many tasks, particularly because of
free availability, I strongly believe that further availability of bioinformatics solu-
tions in multiple languages facilitates thinking about a problem in multiple ways.
Every programmer has their own opinion on their favorite language to code in, but I
believe there should not be monopolies in this sense. Having worked extensively
with R, Python, MATLAB, Swift, Objective C, C/C++, FORTRAN, UNIX, I also
have language favorites for different usages and have adapted a lot of the material in
评论0