Predicting Transcription Factor Complexes A Novel Approach to Data Integration in Systems Biology /

• Κύριος συγγραφέας: Will, Thorsten (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Wiesbaden : Springer Fachmedien Wiesbaden : Imprint: Springer Spektrum, 2015.
• Σειρά: BestMasters
• Θέματα: Life sciences.; Bioinformatics.; Computational biology.; Biomathematics.; Life Sciences.; Computer Appl. in Life Sciences.; Mathematical and Computational Biology.

 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.  . 

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