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Predicting transcription factor complexesa novel approach to data integration in systems biology /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Predicting transcription factor complexesby Thorsten Will.
Reminder of title:	a novel approach to data integration in systems biology /
Author:	Will, Thorsten.
Published:	Wiesbaden :Springer Fachmedien Wiesbaden :2015.
Description:	xix, 142 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Transcription factors.
Online resource:	http://dx.doi.org/10.1007/978-3-658-08269-7
ISBN:	9783658082697 (electronic bk.)

Predicting transcription factor complexesa novel approach to data integration in systems biology /
Will, Thorsten.

Predicting transcription factor complexesa novel approach to data integration in systems biology /[electronic resource] :by Thorsten Will. - Wiesbaden :Springer Fachmedien Wiesbaden :2015. - xix, 142 p. :ill., digital ;24 cm. - BestMasters. - BestMasters..

Protein Complex Prediction -- Protein-Protein Interaction Networks -- Domain-Domain Interaction Networks -- Combinatorial Algorithms -- Algorithm Engineering.

In his master thesis Thorsten Will proposes the substantial information content of protein complexes involving transcription factors in the context of gene regulatory networks, designs the first computational approaches to predict such complexes as well as their regulatory function and verifies the practicability using data of the well-studied yeast S.cereviseae. The novel insights offer extensive capabilities towards a better understanding of the combinatorial control driving transcriptional regulation. Contents Protein Complex Prediction Protein-Protein Interaction Networks Domain-Domain Interaction Networks Combinatorial Algorithms Algorithm Engineering Target Groups Computational biologists and biologists working with gene regulatory networks Computer scientists interested in biological issues The Author Currently, the author is pursuing his Ph.D. at the Center for Bioinformatics in Saarbrucken, Germany.

ISBN: 9783658082697 (electronic bk.)

Standard No.: 10.1007/978-3-658-08269-7doiSubjects--Topical Terms:

202406
Transcription factors.

LC Class. No.: QP552.T68

Dewey Class. No.: 572.8845

Predicting transcription factor complexesa novel approach to data integration in systems biology /
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245 1 0 $a Predicting transcription factor complexes $h [electronic resource] : $b a novel approach to data integration in systems biology / $c by Thorsten Will.
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520 $a In his master thesis Thorsten Will proposes the substantial information content of protein complexes involving transcription factors in the context of gene regulatory networks, designs the first computational approaches to predict such complexes as well as their regulatory function and verifies the practicability using data of the well-studied yeast S.cereviseae. The novel insights offer extensive capabilities towards a better understanding of the combinatorial control driving transcriptional regulation. Contents Protein Complex Prediction Protein-Protein Interaction Networks Domain-Domain Interaction Networks Combinatorial Algorithms Algorithm Engineering Target Groups Computational biologists and biologists working with gene regulatory networks Computer scientists interested in biological issues The Author Currently, the author is pursuing his Ph.D. at the Center for Bioinformatics in Saarbrucken, Germany.
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