Systems Genetics: Linking Genotypes and Phenotypes(Cambridge Series in Systems Genetics)

Whereas genetic studies have traditionally focused on explaining heritance of single traits and their phenotypes, recent technological advances have made it possible to comprehensively dissect the genetic architecture of complex traits and quantify how genes interact to shape phenotypes. This exciting new area has been termed systems genetics and is born out of a synthesis of multiple fields, integrating a range of approaches and exploiting our increased ability to obtain quantitative and detailed measurements on a broad spectrum of phenotypes. Gathering the contributions of leading scientists, both computational and experimental, this book shows how experimental perturbations can help us to understand the link between genotype and phenotype. A snapshot of current research activity and state-of-the-art approaches to systems genetics are provided, including work from model organisms such as Saccharomyces cerevisiae and Drosophila melanogaster, as well as from human studies.

Table of Contents:
List of contributors; 1. An introduction to systems genetics Florian Markowetz and Michael Boutros; 2. Computational paradigms for analyzing genetic interaction networks Carles Pons, Michael Costanzo, Charles Boone and Chad L. Myers; 3. Mapping genetic interactions across many phenotypes in metazoan cells Christina Laufer, Maximilian Billmann and Michael Boutros; 4. Genetic interactions and network reliability Edgar Delgado-Eckert and Niko Beerenwinkel; 5. Synthetic lethality and chemoresistance in cancer Kimberly Maxfield and Angelique Whitehurst; 6. Joining the dots: network analysis of gene perturbation data Xin Wang, Ke Yuan and Florian Markowetz; 7. High content screening in infectious diseases: new drugs against bugs André P. Mäurer, Peter R. Braun, Kate Holden-Dye and Thomas F. Meyer; 8. Inferring genetic architecture from systems genetics studies Xiaoyun Sun, Stephanie Mohr, Arunachalam Vinayagam, Pengyu Hong and Norbert Perrimon; 9. Bayesian inference for model selection: an application to aberrant signalling pathways in chronic myeloid leukaemia Lisa E. M. Hopcroft, Ben Calderhead, Paolo Gallipoli, Tessa L. Holyoake and Mark A. Girolami; 10. Dynamic network models of protein complexes Yongjin Park and Joel S. Bader; 11. Phenotype state spaces and strategies for exploring them Andreas Hadjiprocopis and Rune Linding; 12. Automated behavioural fingerprinting of C. elegans mutants André E. X. Brown and William R. Schafer; Index.

About the Author :
Florian Markowetz is a Group Leader at Cancer Research UK's Cambridge Research Institute. His research is concerned with developing statistical and mathematical models of complex biological systems and analysing large-scale molecular data. His research interests range from the analysis of molecular clinical data to inference of cellular networks from high-throughput gene perturbation screens and integration of heterogeneous data sources using machines learning techniques and probabilistic graphic models. Michael Boutros is a group leader at the German Cancer Research Centre (DKFZ) in Heidelberg where he heads the Division of Signalling and Functional Genomics. He also holds a Professorship at the University of Heidelberg. His research focuses on the systematic dissection signalling pathways in Drosophila and mammalian cells, which are important during development and cancer. He attempts to define key components of signalling pathways, discovering interaction between pathways, and characterisation of signalling networks under normal and perturbed conditions.

Review :
'Since the completion of the Human Genome Project we hold the 'book of life' in our hands, but for the most part, we do not understand how to interpret it. We lack an understanding of the grammar that it is written in. With this book the authors put together an impressive collection of chapters that provide insights into our current efforts to understand how genetic information is integrated, coordinated and ultimately assembled into biological systems. If you are interested in how to decipher the grammar of life this is a must read!' Frank Buchholz, Technische Universität Dresden, Germany