Abstract
Data mining, computational biology and statistics are unified to a vast research area Bioinformatics. In this arena of diverse research, protein - protein interaction (PPI) is most crucial for functional biological progress. In this research work an investigation has been done by considering the several modules of data mining process. This investigation helps for the detection and analyzes gene regulatory network and PPI network for anxiety disorders. From this investigation a novel pathway has been found. Numerous studies have been done which exhibits that a strong association among diabetes, kidney disease and stroke for causing most libelous anxiety disorders. So it can be said that this research will be opened a new horizon in the area of several aspects of life science as well as Bioinformatics.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Abbreviations
- DB:
-
= Diabetes
- KD:
-
= Kidney Disease
- ST:
-
= Stroke
- AN:
-
= Anxiety
References
WHO: Depression and Other Common Mental Disorders Global Health Estimates (2017)
Barlow, D.H.: Anxiety and Its Disorders: The Nature and Treatment of Anxiety and Panic. Guilford Publications, New York City (2013)
Anxiety and Depression Association of America (2017)
Mathers, C.D., Loncar, D.: Projections of global mortality and burden of disease from 2002 to 2030. PLoS Med. 3(11), e442 (2006)
National Kidney Foundation (2015)
World Stroke Organization (2015)
Klingström, T., Plewczynski, D.: Protein–protein interaction and pathway databases, a graphical review. Briefings Bioinf. 12(6), 702–713 (2010)
Habib, N., et al.: Design regulatory interaction network for anxiety disorders using R: a bioinformatics approach. Beni-Suef Univ. J. Basic Appl. Sci. 7(3), 326–335 (2018)
Spitzer, R.L., et al.: A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch. Intern. Med. 166(10), 1092–1097 (2006)
Browner, W.S., Lui, L.-Y., Cummings, S.R.: Associations of serum osteoprotegerin levels with diabetes, stroke, bone density, fractures, and mortality in elderly women. J. Clin. Endocrinol. Metab. 86(2), 631–637 (2001)
Lustman, P.J., Clouse, R.E.: Depression in diabetic patients: the relationship between mood and glycemic control. J. Diabetes Complications 19(2), 113–122 (2005)
National Diabetes Statistics Report (2017)
Lee, Y.-J., et al.: Association of depression and anxiety with reduced quality of life in patients with predialysis chronic kidney disease. Int. J. Clin. Pract. 67(4), 363–368 (2013)
Ridker, P.M.: Inflammatory biomarkers and risks of myocardial infarction, stroke, diabetes, and total mortality: implications for longevity. Nutr. Rev. 65, S253–S259 (2007)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Islam, M.R., Ahmed, M.L., Kumar Paul, B., Asaduzzaman, S., Ahmed, K. (2019). Common Gene Regulatory Network for Anxiety Disorder Using Cytoscape: Detection and Analysis. In: Rojas, I., Valenzuela, O., Rojas, F., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2019. Lecture Notes in Computer Science(), vol 11466. Springer, Cham. https://doi.org/10.1007/978-3-030-17935-9_20
Download citation
DOI: https://doi.org/10.1007/978-3-030-17935-9_20
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-17934-2
Online ISBN: 978-3-030-17935-9
eBook Packages: Computer ScienceComputer Science (R0)