An introduction to a new paradigm in social, technological, and scientific discourse, this book presents an overview of statistical methods for describing, modeling, and inferring biological networks using genomic and other types of data. It covers a large variety of modern statistical techniques, such as sparse graphical models, state space models, Boolean networks, and hidden Markov models. The authors address gene transcription data, microRNAs, ChIP-chip, and RNAi data. Along with end-of-chapter exercises, the text includes many real-world examples with implementations using a dedicated R package.

Statistics for Biological Networks: How to Infer Networks from Data (Chapman & Hall/CRC Interdisciplinary Statistics)

Science & Math

Wit, Ernst

Vinciotti, Veronica

Purutcuoglu, Vilda

Biological Sciences

Chapman and Hall/CRC

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Books by Vinciotti, Veronica

See the best price to sell, buy, or rent books by Vinciotti, Veronica. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Statistics for Biological Networks: How to Infer Networks from Data (Chapman & Hall/CRC Interdisciplinary Statistics)