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Bioinformatics of the Brain

look for peripheral SCZ indicators [61]. Their findings indicated abnormalities

in ATL3 peripheral expression in SCZ.

Extreme mood fluctuations, including mania and depression, are symp-

toms of bipolar disorder (BD), a heritable mental health illness. Choi and

coworkers evaluated microarray data with postmortem tissue samples from

patients with bipolar disorder (BD) and healthy controls. They also raised

issues with this disease’s research limitations, such as the inability of many

studies to converge and the consequent difficulty in drawing general conclu-

sions from individual findings [62]. To this end, they integrated machine learn-

ing techniques to their research which helped identify association of PPAR-G

pathway with BD.

Impairments in social interaction and the appearance of constrained, repet-

itive activities or interests are the hallmarks of autism spectrum disorder

(ASD), a neurodevelopmental condition with a significant hereditary basis

[63]. ASD is extensively studied utilizing microarray techniques, like many

other health conditions. Fajarda and colleagues attempted to develop a strat-

egy for combining microarray datasets in hopes of determination of differen-

tially expressed marker genes for ASD [64]. They used machine learning algo-

rithms in conjunction with statistical analysis of the microarray data. Their

method identified ASD marker genes with 98 % accuracy. In another study,

Sevimoglu evaluated ASD utilizing microarray data on DNA methylation and

gene expression concurrently [65]. 42 genes were found to be differently reg-

ulated and methylated as a result of the research, the majority of which had

not previously been linked to ASD.

Attention deficit hyperactivity disorder (ADHD) is a developmental con-

dition where patients demonstrate continual patterns of lack of attention,

hyperactivity, and/or restlessness. Relationships and daily activities of these

individuals might be substantially impacted by ADHD symptoms. Cabana-

Domínguez and coworkers carried out microarray analysis of ADHD where

they identified seven modules associated with the disorder as well as signifi-

cantly altered signaling pathways using peripheral blood [66]. Another study

done by Mortimer and coworkers assessed gene expression profiles of ADHD

patients and healthy counterparts blood samples [67]. Their study determined

eight candidate genes which were previously unidentified.

8.5.2

RNA-seq Studies

Determining the genetic causes of brain illnesses and disorders has also been

made possible by this relatively new method of detecting and examining the

transcriptome. The development of research in the area has greatly acceler-

ated through the use of NGS technologies. Once again, this demonstrates how

researchers used these experiments to try and elucidate every facet of the com-

plex genetic system.In this section recent RNA-seq studies of brain diseases

and disorders mentioned previously were presented.