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Statistics for Biological Networks: How to Infer Networks from Data

By (author) Ernst Wit, By (author) Veronica Vinciotti, By (author) Vilda Purutcuoglu

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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.

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The Coming Wave: AI, Power and Our Future

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352 pages
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The Order of Time

Carlo Rovelli
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Originally published in Italian: L'ordine del tempo (Milan: Adelphi Edizioni, 2017).

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Helgoland: The Strange and Beautiful Story of Quantum Physics

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