Will, Thorsten.
Predicting Transcription Factor Complexes A Novel Approach to Data Integration in Systems Biology / [electronic resource] : by Thorsten Will. - 1st ed. 2015. - XIX, 142 p. 29 illus. online resource. - BestMasters, 2625-3577 . - 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 Saarbrücken, Germany. .
9783658082697
10.1007/978-3-658-08269-7 doi
Bioinformatics.
Bioinformatics .
Computational biology .
Biomathematics.
Bioinformatics.
Computer Appl. in Life Sciences.
Mathematical and Computational Biology.
QH324.2-324.25
570.285
Predicting Transcription Factor Complexes A Novel Approach to Data Integration in Systems Biology / [electronic resource] : by Thorsten Will. - 1st ed. 2015. - XIX, 142 p. 29 illus. online resource. - BestMasters, 2625-3577 . - 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 Saarbrücken, Germany. .
9783658082697
10.1007/978-3-658-08269-7 doi
Bioinformatics.
Bioinformatics .
Computational biology .
Biomathematics.
Bioinformatics.
Computer Appl. in Life Sciences.
Mathematical and Computational Biology.
QH324.2-324.25
570.285