Bioinformatics of Brain Diseases

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The abovementioned techniques and resources will assist in less invasive

understanding of the researched diseases since both microarray and RNA-seq

experiments on brain diseases mostly depend on data obtained through inva-

sive sampling such as tissue from different areas of the brain which obviously

is usually taken from a deceased person/animal.

The swift rise of various big data analysis methodologies, including ar-

tificial intelligence tools, may result in the creation of personalized patient-

tailored diagnoses. In the future, in silico diagnostics is anticipated to be

similar, reliable, less subject to variation, objective, and error-free [108].

8.7

Future Perspectives

Understanding the microscopic and macroscopic phenotypes of the healthy

and the diseased brain and integrating them is difficult but necessary. Using

microarray and RNA-seq high throughput technologies helped us move faster

than ever before in elucidating the abovementioned neurological conditions.

Nonetheless, both techniques have limitations that prevent us from estab-

lishing a solid genetic mechanism for the studied diseases and disorders. For

instance, brain tissue samples are collected postmortem hence there may be a

small sample size for each experiment. Another issue we may face is that ev-

ery microarray platform has its own probe sets and annotations so comparing

them also means annotation conversions are necessary. Some of the informa-

tion may be lost during these conversions. Even in the same platform a gene

may be assigned multiple probes, and this may cause wrongful identification

of a gene, miRNA etc. RNA-seq does not rely on specific probes so this issue

may be non-existent while using this technique. Still quality control issues

surrounding the samples in the first place plus the cost of running an exper-

iment with RNA-seq are two major issues currently dealt with. In addition,

the data obtained from both high-throughput technologies as well as other

technologies are increasing so maybe making good use of the information at

hand is the best we can do currently. Knowing the limitations of the current

technology will guide us in making better technologies in the future.

We may be able to accomplish our goal of deciphering the genetic mecha-

nisms more quickly by combining new techniques with the recent discoveries,

like imaging techniques and artificial intelligence systems. Since it is challeng-

ing to collect tissue samples before the patient passes away, the utilization of

human organoids that develop in vitro environments with organ complexity

similar to that found in vivo may be another potential new area of research

especially for diseases and disorders of the brain. The rapidly changing in-

novative technologies give us hope that someday we will have deciphered the

mechanisms that mediate our brain and present personalized therapeutics for

each individual without any invasive experiments.