000			02912cam a2200313 a 4500
003			EG-GiCUC
008			191015s2019 ua d f m 000 0 eng d
040			_aEG-GiCUC _beng _cEG-GiCUC
041	0		_aeng
049			_aDeposite
097			_aPh.D
099			_aCai01.18.02.Ph.D.2019.As.C
100	0		_aAshraf Mohamed Hassan Hendam
245	1	2	_aA computational based approach for studying synaptic cell Adhesion / _cAshraf Mohamed Hassan Hendam ; Supervised Hesham Ahmed Hefny , Ahmed Farouk Alsadek
246	1	5	_aاسلوب حسابى لدراسة التصاق الخلايا المتشابكة
260			_aCairo : _bAshraf Mohamed Hassan Hendam , _c2019
300			_a117 Leaves : _bcharts ; _c30cm
502			_aThesis (Ph.D.) - Cairo University - Faculty of Graduate Studies for Statistical Research - Department of Computer and Information Science
520			_aCentral Nervous System is responsible for passing signals from all the body to the brain to process it. Brain consists of neurons which are cells that convey information about the world around us, help us make sense of the world and send commands to our muscles to act. Synaptic cell adhesion is connecting neurons in order to establish a network. Neurexins and Neuroligins proteins are two binding partners which represent the core of the synaptic cell adhesion. Neurexin1 gene is playing an important role in synaptic formation, plasticity and maturity. Studies have reported non-synonymous SNPs in Neurexin1 in some diseases. The current thesis is aiming to apply a computational approach for studying the effects of non-synonymous Single Nucleotide Polymorphisms (SNPs) recoded Neurexin1 in diseases patients. The methodology has been implemented in two steps. The first step aims to identify deleterious SNPs, determine damaged protein features (function, stability) and recognize potential protein regions for future research. The effect on protein function is predicted by PROVEAN, SIFT and PolyPhen-2 tools while protein stability is predicted by MUpro and I-Mutant2.0 tools. Prediction results have identified 2 SNPs to be deleterious by all tools and two additional SNPs have agreement between protein function prediction tools and MUpro from stability tools. Higher deleterious prediction results in the stability tools with the percentages of 72%, 78% than the function tools with 25%, 41% and 47%. Agreement percentage of deleterious prediction between stability tools was 56% while 12.5% in the function tools. The identified regions of Neurexin1 for future research are SP and LNS4
530			_aIssued also as CD
653		4	_aMolecular Dynamic Simulation
653		4	_aNeurexin 1 gene
653		4	_aSynaptic cell Adhesion
700	0		_aAhmed Farouk Alsadek , _eSupervisor
700	0		_aHesham Ahmed Hefny , _eSupervisor
905			_aAsmaa _eCataloger
905			_aNazla _eRevisor
942			_2ddc _cTH
999			_c74538 _d74538