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Predicting Transcription Factor Complexes [electronic resource] : A Novel Approach to Data Integration in Systems Biology / by Thorsten Will.

By: Will, Thorsten [author.]Contributor(s): SpringerLink (Online service)Material type: TextTextSeries: BestMastersPublisher: Wiesbaden : Springer Fachmedien Wiesbaden : Imprint: Springer Spektrum, 2015Edition: 1st ed. 2015Description: XIX, 142 p. 29 illus. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783658082697Subject(s): Bioinformatics | Bioinformatics  | Computational biology  | Biomathematics | Bioinformatics | Computer Appl. in Life Sciences | Mathematical and Computational BiologyAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 570.285 LOC classification: QH324.2-324.25Online resources: Click here to access online
Contents:
Protein Complex Prediction -- Protein-Protein Interaction Networks -- Domain-Domain Interaction Networks -- Combinatorial Algorithms -- Algorithm Engineering.
In: Springer Nature eBookSummary: 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 Saarbrücken, Germany.  .
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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 Saarbrücken, Germany.  .

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