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Computational inference of biomolecu...

Varadan, Vinay.

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Computational inference of biomolecular systems for synaptic connectivity.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Computational inference of biomolecular systems for synaptic connectivity./
Author:	Varadan, Vinay.
Description:	148 p.
Notes:	Adviser: Dimitris Anastassiou.
Contained By:	Dissertation Abstracts International68-09B.
Subject:	Biology, Bioinformatics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3285190
ISBN:	9780549271642

Computational inference of biomolecular systems for synaptic connectivity.
Varadan, Vinay.

Computational inference of biomolecular systems for synaptic connectivity. - 148 p.

Adviser: Dimitris Anastassiou.

Thesis (Ph.D.)--Columbia University, 2007.

This thesis presents novel computational approaches to infer biomolecular systems for synaptic specificity. The specific issues addressed in this thesis are the identification of biologic mechanisms that select mutually exclusive alternatively spliced exons, and, the integration of neuronal connectivity information with gene expression data to identify synergistic gene sets associated with synapses. We use the well-described neural network of the model C. elegans organism to outline an information-theoretic methodology that not only identifies gene sets most associated with the phenotype ab initio, but also provides insight into the way in which these genes may interact with each other in the context of the specific phenotype. This systems-based methodology combines the modeling power of multivariate analysis along with the descriptive power of decomposing gene sets into interacting components that can help provide insights into molecular pathways associated with biological outcomes.

ISBN: 9780549271642Subjects--Topical Terms:

1018415
Biology, Bioinformatics.

Computational inference of biomolecular systems for synaptic connectivity.
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020 $a 9780549271642
035 $a (UMI)AAI3285190
035 $a AAI3285190
040 $a UMI $c UMI
100 1 $a Varadan, Vinay. $3 1278908
245 1 0 $a Computational inference of biomolecular systems for synaptic connectivity.
300 $a 148 p.
500 $a Adviser: Dimitris Anastassiou.
500 $a Source: Dissertation Abstracts International, Volume: 68-09, Section: B, page: 6201.
502 $a Thesis (Ph.D.)--Columbia University, 2007.
520 $a This thesis presents novel computational approaches to infer biomolecular systems for synaptic specificity. The specific issues addressed in this thesis are the identification of biologic mechanisms that select mutually exclusive alternatively spliced exons, and, the integration of neuronal connectivity information with gene expression data to identify synergistic gene sets associated with synapses. We use the well-described neural network of the model C. elegans organism to outline an information-theoretic methodology that not only identifies gene sets most associated with the phenotype ab initio, but also provides insight into the way in which these genes may interact with each other in the context of the specific phenotype. This systems-based methodology combines the modeling power of multivariate analysis along with the descriptive power of decomposing gene sets into interacting components that can help provide insights into molecular pathways associated with biological outcomes.
590 $a School code: 0054.
650 4 $a Biology, Bioinformatics. $3 1018415
650 4 $a Biology, Neuroscience. $3 1017680
650 4 $a Engineering, Electronics and Electrical. $3 626636
690 $a 0317
690 $a 0544
690 $a 0715
710 2 $a Columbia University. $3 571054
773 0 $t Dissertation Abstracts International $g 68-09B.
790 $a 0054
790 1 0 $a Anastassiou, Dimitris, $e advisor
791 $a Ph.D.
792 $a 2007
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3285190