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E u r o S c i C o n c o n f e r e n c e o n
Protein, Proteomics and
Computational Biology
Biochemistry & Molecular Biology Journal
ISSN: 2471-8084
D e c e m b e r 0 6 - 0 7 , 2 0 1 8
Am s t e r d a m , N e t h e r l a n d s
Proteomics and Computational Biology 2018
Page 25
It is evident that in etiologies of human complex diseases, genetic factors
play some important roles. Genome-wide association study (GWAS) is a
standard technique to identify heritable genetic basis of complex diseases. In
relation with GWAS, there exist some challenges in selecting input samples
completely randomly, to biologically describe GWAS results, to translate them
into clinical benefits and to compare germline variants achieved from GWAS with
somatic mutations in creating, development and treatment of human complex
diseases. Likelihood-based statistical methods are robust in estimating linkage
disequilibriumwhen factors like non-randomness and population structures exist.
Then the results of GWAS can be used for post-GWAS analyses to predict multiple
biological components like genes, non-coding RNAs and transcription factor
binding sites in association with complex diseases. An integrative analysis seeks
to pool information from multiple GWAS results, somatic mutations and genetic
drug targets of human complex disorders and the results of such analysis can
provide new insight into the genetic and treatments of complex diseases. This
presentation is prepared from the viewpoint that the robust statistical method
can be applied to arrive at valuable results from GWAS and that primarily genetic
information derived from GWAS is subject to further post-GWAS analysis to
provide more biologically informative results in relation with genetics of human
complex diseases that can be applied to real time clinical applications. Then the
results of such analyses can be used to discuss and compare human cancers
and neurodegenerative diseases from a genetic perspective. We concluded that in
spite of the differences between human cancers and neurodegenerative diseases,
the roles of germline and somatic mutations in creating, developments and
treatments of those two kinds of human complex diseases are similar.
Biography
Zahra Mortezaei has completed her Undergraduate in
Mathematics from Amirkabir University of technology
(Tehran Polytecnique), Iran and studied for Mphill degree in
Mathematical physics at University of Nottingham (UK). She
then completed her PhD in Bioinformatics at University of
Birmingham (UK) and the University of Tehran (Iran). She is
working as bioinformatician at human genetic research centre
in Iran. Her recent papers in the field of Bioinformatics are:
• Mortezaei, Z., Lanjanian, H., Masoudi-nejad, A., (2017)
Genomics Candidate novel long noncoding RNAs ,
MicroRNAs and putative drugs for Parkinson’s disease
usingarobustandefficientgenome-wideassociationstudy.
Genomics, 109(3–4):158–164.
• Mortezaei, Z., Cazier, J-B., Mehrabi, A.A., Cheng, C. and
Masoudi-Nejad, A. (2018) Novel Putative Drugs and
Key Initianting Genes for Neurodegenerative Diseases
Determined Using Network-Based Genetic Integrative
Analysis. J Cell Biochem, 1-13.
Efficient Genome-Wide Association Studies and
Post-GWAS Integrative Analyses for Human
Cancer and Neurodegenerative Diseases
Zahra Mortezaei1,2, Ali Masoudi-Nejad1 ,
Mahmood Tavallaei2
1Laboratory of Systems Biology and Bioinformatics (LBB), Institute of Biochemistry and
Biophysics, University of Tehran, Tehran, Iran
2Human Genetic Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran
Zahra Mortezaei et al., Biochem Mol biol J Volume:4
DOI: 10.21767/2471-8084-C5-020