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July 2013

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"Diane St. Germain" <[log in to unmask]>
Date:
Wed, 24 Jul 2013 14:46:52 +0000
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To: Giorgio Ascoli <[log in to unmask]>, Padmanabhan Seshaiyer <[log in to unmask]>, BIOSCIENCES <[log in to unmask]>, "[log in to unmask]" <[log in to unmask]>, "[log in to unmask]" <[log in to unmask]>, SSB Faculty <[log in to unmask]> cc: Jennifer Bazaz <[log in to unmask]>
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"Diane St. Germain" <[log in to unmask]>
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Thesis Defense Announcement
To:  The George Mason University Community

Candidate: Sean Mackesey

Program: Master of Science in Bioinformatics & Computational Biology



Date:   Thursday August 1, 2013

Time:   2:00 p.m.

Place:  George Mason University
             Fairfax<http://www.gmu.edu/resources/welcome/Directions-to-GMU.html> Campus

             Krasnow Institute, Room 229



Title: "Estimation of the Population Sizes of Neuronal Types of the Hippocampome Knowledge Base in the Dentate Gyrus"
Thesis Director: Dr. Giorgio Ascoli
Thesis Committee:  Dr. Iosif Vaisman, Dr. Padmanabhan Seshaiyer
A copy of the thesis will be available in the Johnson Center Library.  All are invited to attend the defense.
ABSTRACT
The Hippocampome is a new knowledge base of the rodent hippocampus that aims to compile and collate the mass of published information regarding this structure. The foundation of the Hippocampome is a set of morphologically distinct cell types, defined by the presence of axons and dendrites within specific compartments of the hippocampal formation.  Primary aims of the Hippocampome include the creation of a standard classification scheme for hippocampal neurons and the establishment of a central repository for data regarding the hippocampus.  The present project attempts to derive such population estimates for the 18 Hippocampome neuron types with somata in the dentate gyrus, one of the hippocampal formation's major constituents.  Data from morphological and stereological studies was taken from the literature and represented as a system of equations constraining the population sizes of the dentate gyrus neuron types.  A simulated annealing algorithm was used to optimize the system and thereby provide estimates for the population sizes. It is hoped that this work serve as a pilot for future, larger scale attempts to derive population estimates for all Hippocampome types.

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