Modeling neurotransmitter binding to receptors in the brain.

A non-deterministic model based on the assumption that the binding of a neurotransmitter to its receptor is a Markov process is developed. This model is capable of describing the kinetic processes that occur when a neurotransmitter binds to its receptor in the normal unpathological condition and in...

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Bibliographic Details
Main Author: Elkarmi, Ali Zuhair
Other Authors: Fares, Y. (degree committee member.), Foster, B. G. (degree committee member.), Miller, G. E. (degree committee member.), O'Brien, E. M. (degree committee member.)
Format: Thesis Book
Language:English
Published: 1987.
Subjects:
Online Access:Link to ProQuest copy
Link to OAKTrust copy

MARC

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099 |a 1987  |a Dissertation  |a E43 
100 1 |a Elkarmi, Ali Zuhair. 
245 1 0 |a Modeling neurotransmitter binding to receptors in the brain. 
264 1 |c 1987. 
300 |a vii, 90 leaves :  |b illustrations ;  |c 29 cm 
336 |a text  |b txt  |2 rdacontent 
337 |a unmediated  |b n  |2 rdamedia 
338 |a volume  |b nc  |2 rdacarrier 
500 |a Typescript (photocopy). 
500 |a Vita. 
502 |b Ph. D. in Bioengineering  |c Texas A & M University  |d 1987 
504 |a Includes bibliographical references (leaves 71-81). 
520 3 |a A non-deterministic model based on the assumption that the binding of a neurotransmitter to its receptor is a Markov process is developed. This model is capable of describing the kinetic processes that occur when a neurotransmitter binds to its receptor in the normal unpathological condition and in related disease situations. The model assumes the presence of four states and develops their transition probability function, the expected number of visits to a certain state, the probability of ever reaching a certain state and a number of related statistical properties. Furthermore, the model explains the probable causes of related disease situations and develops their transition probability function and related statistical properties. The model parameters of the normal condition are generated by a computer simulation program and are compared to those of the disease situation. The results of these sample calculations supported the model assumptions for the normal and disease situations. 
650 0 |a Biomedical engineering  |x Mathematical models. 
650 0 |a Neurotransmitter receptors. 
650 0 |a Neurotransmitters. 
650 4 |a Major bioengineering. 
655 7 |a Academic theses  |2 lcgft 
700 1 |a Fares, Y.,  |e degree committee member. 
700 1 |a Foster, B. G.,  |e degree committee member. 
700 1 |a Hyman, W. A.,  |e degree supervisor. 
700 1 |a Miller, G. E.,  |e degree committee member. 
700 1 |a O'Brien, E. M.,  |e degree committee member. 
710 2 |a Texas A & M University,  |e degree granting institution. 
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