300

As soon as more complex calculations are the focus (instead of lists, data, web servers,

databases or sequence properties), more languages such as C or C++ (computer languages

that are also used intensively and developed further today, newer is e.g. c#, pronounced: c

sharp, and similar more) and Fortran (Formula Translation) are used in bioinformatics,

old but constantly modernised. For example, Fortran 2003 is object-oriented, and Fortran

2008 even allows “concurrent programming”, i.e. parallel, instead of serial

programming.

MATLAB

Allows complex computations to be efficiently expressed in this language in a mathe­

matical way.

MATLAB is matrix-based. Linear algebra in MATLAB looks like linear algebra in a

textbook. This makes the code for these calculations easier to write, read, and analyze, and

easy to manage. Numerical analyses are also easy to write. Another advantage is that com­

putations are distributed across multiple processors (“cores”), making them much faster.

This makes parallelization easy. More information can be found here https://

de.mathworks.com/.

Programming Language R

If, on the other hand, the calculations are of a more statistical nature, i.e. deal directly with

the analysis of large amounts of data, R is often used in bioinformatics:

R is also very easy to learn by following the link, installing R right there and learning

it too. R is freely available and very useful for statistical analysis and graphical representa­

tion of biological data (results and graphs can also be used for scientific publications). It is

command line based and can be used on different platforms and operating systems (e.g.

Windows, Linux). In short, R is a really nice and easy to learn programming language, best

try it yourself (there are also numerous online codes to use). Moreover, it is interconnected

with other programming languages and platforms, such as Bioconductor, for even more

specialized data analysis.

A good example of high-throughput data analysis is Bioconductor (https://www.bio­

conductor.org), which now has 1881 (as of August 4, 2020) software packages (https://

www.bioconductor.org/packages/devel/BiocViews.html).

https://de.mathworks.com/products/matlab.html

https://www.r-­project.org

19  Tutorial: An Overview of Important Databases and Programs