
Computational Exome and Genome Analysis
Description
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Reviews / Votes
"This book represents a timely contribution to the burgeoning field of exome and genome sequencing data analysis. It covers all pertinent topics ranging from raw data quality control to medical interpretation of genetic mutations, with detailed command line examples as well as in-depth explanations on every step of analysis. Highly recommended to any researchers, scientists, clinicians or students who are interested to learn practical skills on genome analysis."-Kai Wang, Department of Biomedical Informatics, Columbia University
"This book provides a very comprehensive overview of all the fundamentals that are needed to work as a bioinformatician in the field of exome and genome analysis. All of the important processing steps are illustrated with practical examples and code. In addition, the casual writing style makes this book an easy read."
-Christian Gilissen, Department of Human Genetics, Radbound Univeristy Medical Center
"This book is an excellent example of a hybrid between a textbook and an up-to-date research reference on the latest bioinformatics tools available in this eld. Its rigorous and thorough approach makes it a reliable starting point for bioinformaticians and biologists. By including details on methodological aspects of some of the algorithms used for various components of the data analysis and coupling these with fully-commented examples and exercises, this book presents itself as a must-have for novices and experts alike. Given the fast pace of the field, no book can be exhaustive, however, the wide variety of tools presented here recommend it to a wide audience, both as expertise and focused research interests."
-Irina Ioana Mohorianu, Zentralblatt MATH
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Persons
Rosario M. Piro is an Assistant Professor of Bioinformatics at Freie Universitaet Berlin and Charite-Universitaetsmedizin Berlin, Germany. His research is mainly focused on computational neuropathology, including cancer genetics/genomics of brain tumors as well as network analysis and disease gene prediction for neurological disorders; and computational oncology in general, including the development and evolution of cancers in other organs or tissues. His expertise in next-generation sequencing data analysis techniques is complemented by a past research experience in the field of data-intensive distributed computing.
Marten Jaeger is a graduate student in Peter Robinson's group and has developed pipelines for exome and genome sequencing data. Marten's work has involved the development of algorithms for variant annotation, exome prioritization, RNA-seq, and integrative genomics analysis.
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