Predicting Transcription Factor Complexes

A Novel Approach to Data Integration in Systems Biology
2015
ISBN: 978-3-658-08268-0
Verlag: Springer

Buch, Englisch, 142 Seiten, Format (B × H): 148 mm x 210 mm, Gewicht: 2205 g

Reihe: BestMasters

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.

Zielgruppe

Research

Autoren/Hrsg.

Will, Thorsten

Fachgebiete

• Mathematik | Informatik EDV | Informatik Angewandte Informatik Bioinformatik
• Naturwissenschaften Biowissenschaften Proteinforschung
• Naturwissenschaften Biowissenschaften Biowissenschaften Genetik und Genomik (nichtmedizinisch)
• Naturwissenschaften Biowissenschaften Angewandte Biologie Bioinformatik

Inhaltsverzeichnis

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

Über Autor(innen)

Currently, the author is pursuing his Ph.D. at the Center for Bioinformatics in Saarbrücken, Germany.