xv

ues is the main topic of Chapter 8. We have discussed the high through-

roaches for evaluating brain transcriptomics, the repositories used to

e information collected through them, and the data processing and

ation tools. Each technique’s benefits and drawbacks have been pre-

Additionally, examples of current RNA-seq and microarray research

eurological conditions covered in this book are provided. Several pro-

ave been pointed out that could assist researchers in comprehending

now accessible on brain diseases and disorders, such as combining dif-

methodologies (such as imaging techniques, transcriptomics data, and

intelligence approaches).

analysis of brain health and disease states using graph theory forms

s topics of Chapter 9, which first describes the main graph analysis

ers and complex network models. Then, three main topics in brain

using graph theory which are module detection, brain network motif

and network alignment are reviewed. The final part of this chapter

the brain network alterations due to various neurological disorders

Alzheimer’s disease and Parkinson’s disease.

final chapter covers brain proteomics, or more precisely, the use of

ectrometry (MS) for extensive analysis of the brain proteome. Shotgun

ics is widely used in MS-based proteomics. This technique provides a

hensive protein profile of a tissue or cell and is made possible by high-

on equipment. Additionally, rapid technological developments in bioin-

s have greatly improved the field’s ability to conduct high-throughput

that involve the analysis of massive volumes of data. Proteome analy-

g high-throughput technology holds enormous potential for advancing

erstanding of neurodegenerative disorders such as Alzheimer’s disease

arkinson’s disease, and schizophrenia.

express our gratitude to each and every one of our contributors for

luable work on this book.

Kayhan Erciyes

Maltepe University

Tuba Sevimoglu

University of Health Sciences