Bioinformatics of Brain Diseases

199

of gene evolution, and the modeling and understanding of protein structure

and functions. There are countless databases and tools in this area to help

understand the big data which is the result of analysis of numerous characters

of hundreds of large molecules in a single run.

To understand the brain however, we need more than genomics and pro-

teomics. Imaging of the brain is also an important aspect of brain research.

So, understanding the brain requires combining various data types including

as gene expression, atlases of brain anatomy, positron emission tomography

(PET), and magnetic resonance imaging (MRI). This field is also called neu-

roinformatics [3]. This area is an expanded use of analogous technologies cru-

cial for the progress of bioinformatics, however, applied to broader, diverse

types of data at various levels of function.

It should be noted that programming languages are at the core of bioinfor-

matics. They are utilized in the development of novel tools for the processing

of biological data as well as in every facet of bioinformatics, from data anal-

ysis to visualization. Coding is also necessary to address the broad spectrum

and intricate nature of challenges that arise in the field of bioinformatics. The

most used programming languages in this area are R programming, Python,

and Perl [4, 5].

8.2

Analyzing the Brain Transcriptome

One of the basic bioinformatics applications in this area is analyzing the brain

transcriptome which is the set of coding and non-coding RNA scripts expressed

in the brain. Researchers are interested in the transcriptome since it correlates

well with cellular responses. In this chapter, we will focus on two approaches

to obtain transcriptomic data: hybridization-based microarrays and RNA-seq

(Figure 8.1) [6].

8.2.1

Microarrays

Microarrays were invented by a group of scientists with the leadership of

bioenterpreneur Alejandro (Alex) Zaffaroni in the late 1980s [7]. They are

traditional hybridization techniques that lets us study a plethora of genes.

In this technique a myriad of DNA sequences is deposited on a glass slide

called a chip. Each DNA fragment has its own location on the chip. The

technique is based on the fact that mRNA will be translated to proteins,

thus if we analyze mRNA we will be able to get genetic information or the

gene expression. Considering that the degrading of mRNA is quick, it is being

converted into a cDNA (complementary DNA) form which is labeled with

fluorochrome dyes Cy3 (green) and Cy5 (red). The approach is based on the

idea that complementary sequences will bind to one another (Figure 8.1A) [8].