TY  - GEN
TY  - GEN
T1  - Predicting Transcription Factor Complexes A Novel Approach to Data Integration in Systems Biology
T2  - BestMasters,
A1  - Will, Thorsten.
LA  - English
PP  - Wiesbaden
PB  - Springer Fachmedien Wiesbaden : Imprint: Springer Spektrum
YR  - 2015
ED  - 1st ed. 2015.
UL  - http://discoverylib.upm.edu.my/discovery/Record/978-3-658-08269-7
AB  - 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.  .
OP  - 142
CN  - QH324.2-324.25
SN  - 9783658082697
KW  - Bioinformatics.
KW  - Bioinformatics .
KW  - Computational biology .
KW  - Biomathematics.
KW  - Computer Appl. in Life Sciences.
KW  - Mathematical and Computational Biology.
ER  -