Automated Reasoning for Systems Biology and Medicine
暫譯: 系統生物學與醫學的自動推理
Lio, Pietro, Zuliani, Paolo
- 出版商: Springer
- 出版日期: 2019-06-24
- 售價: $5,910
- 貴賓價: 9.5 折 $5,615
- 語言: 英文
- 頁數: 474
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 3030172961
- ISBN-13: 9783030172961
海外代購書籍(需單獨結帳)
商品描述
This book presents outstanding contributions in an exciting, new and multidisciplinary research area: the application of formal, automated reasoning techniques to analyse complex models in systems biology and systems medicine. Automated reasoning is a field of computer science devoted to the development of algorithms that yield trustworthy answers, providing a basis of sound logical reasoning. For example, in the semiconductor industry formal verification is instrumental to ensuring that chip designs are free of defects (or "bugs"). Over the past 15 years, systems biology and systems medicine have been introduced in an attempt to understand the enormous complexity of life from a computational point of view. This has generated a wealth of new knowledge in the form of computational models, whose staggering complexity makes manual analysis methods infeasible. Sound, trusted, and automated means of analysing the models are thus required in order to be able to trust their conclusions. Above all, this is crucial to engineering safe biomedical devices and to reducing our reliance on wet-lab experiments and clinical trials, which will in turn produce lower economic and societal costs. Some examples of the questions addressed here include: Can we automatically adjust medications for patients with multiple chronic conditions? Can we verify that an artificial pancreas system delivers insulin in a way that ensures Type 1 diabetic patients never suffer from hyperglycaemia or hypoglycaemia? And lastly, can we predict what kind of mutations a cancer cell is likely to undergo? This book brings together leading researchers from a number of highly interdisciplinary areas, including: - Parameter inference from time series - Model selection - Network structure identification - Machine learning - Systems medicine - Hypothesis generation from experimental data - Systems biology, systems medicine, and digital pathology - Verification of biomedical devices
"This book presents a comprehensive spectrum of model-focused analysis techniques for biological systems ...an essential resource for tracking the developments of a fast moving field that promises to revolutionize biology and medicine by the automated analysis of models and data."Prof Luca Cardelli FRS, University of Oxford
商品描述(中文翻譯)
這本書介紹了在一個令人興奮的新興多學科研究領域中的傑出貢獻：將形式化、自動推理技術應用於系統生物學和系統醫學中的複雜模型分析。自動推理是一個計算機科學領域，專注於開發能夠產生可靠答案的算法，提供健全邏輯推理的基礎。例如，在半導體行業中，形式驗證對於確保晶片設計無缺陷（或稱為「錯誤」）至關重要。在過去的15年中，系統生物學和系統醫學被引入，以試圖從計算的角度理解生命的巨大複雜性。這產生了大量的新知識，以計算模型的形式出現，其驚人的複雜性使得手動分析方法變得不可行。因此，需要可靠、可信且自動化的模型分析手段，以便能夠信任其結論。最重要的是，這對於工程安全的生物醫學設備以及減少我們對濕實驗室實驗和臨床試驗的依賴至關重要，這將進一步降低經濟和社會成本。這裡所探討的一些問題包括：我們能否自動調整多種慢性病患者的藥物？我們能否驗證人工胰臟系統以確保1型糖尿病患者不會遭受高血糖或低血糖？最後，我們能否預測癌細胞可能經歷的突變類型？這本書匯集了來自多個高度跨學科領域的領先研究者，包括：- 時間序列的參數推斷 - 模型選擇 - 網絡結構識別 - 機器學習 - 系統醫學 - 從實驗數據生成假設 - 系統生物學、系統醫學和數位病理學 - 生物醫學設備的驗證
「這本書提供了一個針對生物系統的模型聚焦分析技術的全面範疇……是追蹤這個快速發展領域的重要資源，該領域承諾通過模型和數據的自動分析來徹底改變生物學和醫學。」劉卡德利教授，牛津大學
作者簡介
Dr. Paolo Zuliani is a Senior Lecturer at the School of Computing at Newcastle University, UK. He received his Laurea degree in Computer Science from the Università degli Studi di Milano, Italy, and his DPhil in Computer Science from the University of Oxford, UK. Dr. Zuliani's areas of expertise include formal and automated reasoning methods for computing systems, with a focus on probabilistic and quantum systems. He is particularly interested in the verification of biological systems, cyber-physical systems, and quantum programs. Pietro Liò is a Professor of Computational Biology at the Department of Computer Science and Technology at the University of Cambridge, UK. He holds a PhD in Complex Systems and Non Linear Dynamics (University of Firenze, Italy) and a PhD in Genetics (University of Pavia, Italy). His research interests include developing methodologies by integrating bioinformatics, machine learning and modelling approaches. In particular, he is interested in artificial intelligence/machine learning and computational biology methods for biological and health data, predictive models in personalised and precision medicine, machine learning methods for the integration of multi-scale, multi-omics and multi-physics data, and predictive comorbidity models. He is on the steering committee of Cambridge Big Data, the MPhil in Computational Biology and the UK Virtual Physiological Human.
作者簡介(中文翻譯)
保羅·祖利安尼博士（Dr. Paolo Zuliani）是英國紐卡斯爾大學計算學院的高級講師。他在意大利米蘭大學（Università degli Studi di Milano）獲得計算機科學的學士學位，並在英國牛津大學獲得計算機科學的博士學位。祖利安尼博士的專業領域包括計算系統的形式和自動推理方法，特別專注於概率和量子系統。他對生物系統、網絡物理系統和量子程序的驗證特別感興趣。彼得羅·利奧（Pietro Liò）是英國劍橋大學計算機科學與技術系的計算生物學教授。他擁有意大利佛羅倫斯大學的複雜系統與非線性動力學博士學位，以及意大利帕維亞大學的遺傳學博士學位。他的研究興趣包括通過整合生物信息學、機器學習和建模方法來開發方法論。特別是，他對人工智慧/機器學習和計算生物學方法在生物和健康數據中的應用、個性化和精準醫療中的預測模型、多尺度、多組學和多物理數據整合的機器學習方法，以及預測共病模型感興趣。他是劍橋大數據、計算生物學碩士學位（MPhil）和英國虛擬生理人類的指導委員會成員。
