Titlebook: Human Cell Transformation; Role of Stem Cells a Johng S. Rhim,Richard Kremer Book 2012 The Editor(s) (if applicable) and The Author(s), und

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书目名称Human Cell Transformation影响因子(影响力)




书目名称Human Cell Transformation影响因子(影响力)学科排名




书目名称Human Cell Transformation网络公开度




书目名称Human Cell Transformation网络公开度学科排名




书目名称Human Cell Transformation被引频次




书目名称Human Cell Transformation被引频次学科排名




书目名称Human Cell Transformation年度引用




书目名称Human Cell Transformation年度引用学科排名




书目名称Human Cell Transformation读者反馈




书目名称Human Cell Transformation读者反馈学科排名

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Book 2012on the current state of human cell transformation model systems and provides the insight into the molecular and cellular changes involved in the conversion of normal cells to neoplastic cells..Chapters cover all recently developed novel human cell models. In addition, the rapidly growing fields of k

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David J. Lim,Sung K. Moonages they allow a natural specification of problem domains with inherent uncertainty, and from a computational perspective they support efficient algorithms for automatic construction and query answering. This includes belief updating, finding the most probable explanation for the observed evidence,

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Vyomesh Patel,Ramiro Iglesias-Bartolome,Bradford Siegele,Christina A. Marsh,Kantima Leelahavanichkulages they allow a natural specification of problem domains with inherent uncertainty, and from a computational perspective they support efficient algorithms for automatic construction and query answering. This includes belief updating, finding the most probable explanation for the observed evidence,

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Youngmi Ji,Gregory T. Christopherson,Matthew W. Kluk,Orna Amrani,Wesley M. Jackson,Leon J. Nestilied artificial intelligence, offering intuitive, efficient, and reliable methods for diagnosis, prediction, decision making, classification, troubleshooting, and data mining under uncertainty. ..Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis provides a comprehensive

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Guo Li,Xiao-Ai Zhang,Hua Wang,Xin Wang,Chun-Ling Meng,Chu-Yan Chan,David Tai Wai Yew,Kam Sze Tsang,Ke to understand, construct, and analyze probabilistic networ.Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence, offering intuitive, efficient, and reliable methods for diag

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