Ebook: Predicting Transcription Factor Complexes: A Novel Approach to Data Integration in Systems 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.

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.