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Cancer Informatics in the Post Genomic Era
Cancer Informatics in Post-Genomic Era provides both the necessary methodology and practical information tools for analyzing data in the field of medical information science. This, of course, requires analytic tools. Those tools are garnered by developing and assessing methods and systems for the acquisition, processing, and interpretation of patient data, aided by scientific discovery. Key challenges in this field include integrating research and clinical care, sharing data, and establishing partnerships within and across sectors of patient diagnosis and treatment.
Knowledge Discovery in Proteomics
Multi-modal representations, the lack of complete and consistent domain theories, rapid evolution of domain knowledge, high dimensionality, and large amounts of missing information - these are challenges inherent in modern proteomics. As our understanding of protein structure and function becomes ever more complicated, we have reached a point where
Engineering Genetic Circuits
This text presents the modeling, analysis, and design methods for systems biology. It discusses how to examine experimental data to learn about mathematical models, develop efficient abstraction and simulation methods to analyze these models, and use analytical methods to design new circuits. The author reviews basic molecular biology and biochemistry principles, covers several methods for modeling and analyzing genetic circuits, and uses phage lambda as an example throughout to help illustrate the methods. He also explores the emerging area of synthetic biology. iBioSim software, lecture slides, and a password-protected solutions manual are available on the author's website.
Introduction to Biological Networks
The new research area of genomics-inspired network biology lacks an introductory book that enables both physical/computational scientists and biologists to obtain a general yet sufficiently rigorous perspective of current thinking. Filling this gap, Introduction to Biological Networks provides a thorough introduction to genomics-inspired network bi
Data Management of Protein Interaction Networks
Current PPI databases do not offer sophisticated querying interfaces and especially do not integrate existing information about proteins. Current algorithms for PIN analysis use only topological information, while emerging approaches attempt to exploit the biological knowledge related to proteins and kinds of interaction, e.g. protein function, localization, structure, described in Gene Ontology or PDB. The book discusses technologies, standards and databases for, respectively, generating, representing and storing PPI data. It also describes main algorithms and tools for the analysis, comparison and knowledge extraction from PINs. Moreover, some case studies and applications of PINs are also discussed.
Systems Biology
Drawing on the latest research in the field, Systems Biology: Mathematical Modeling and Model Analysis presents many methods for modeling and analyzing biological systems, in particular cellular systems. It shows how to use predictive mathematical models to acquire and analyze knowledge about cellular systems. It also explores how the models are sy
Stochastic Dynamics for Systems Biology
Stochastic Dynamics for Systems Biology is one of the first books to provide a systematic study of the many stochastic models used in systems biology. The book shows how the mathematical models are used as technical tools for simulating biological processes and how the models lead to conceptual insights on the functioning of the cellular processing
Bioinformatics and Computational Biology
Bioinformatics and Computational Biology: Technological Advancements, Applications and Opportunities is an invaluable resource for general and applied researchers who analyze biological data that is generated, at an unprecedented rate, at the global level. After careful evaluation of the requirements for current trends in bioinformatics and computational biology, it is anticipated that the book will provide an insightful resource to the academic and scientific community. Through a myriad of computational resources, algorithms, and methods, it equips readers with the confidence to both analyze biological data and estimate predictions. The book offers comprehensive coverage of the most essenti...
Cellular Potts Models
This work shows how the cellular Potts model can be used as a framework for model building and how extended models can achieve even better biological practicality, accuracy, and predictive power. It focuses on ways to integrate and interface the basic cellular Potts model at the mesoscopic scale with approaches that accurately model microscopic dynamics. These extensions are designed to create a nested and hybrid environment, where the evolution of a biological system is realistically driven by the constant interplay and flux of information between the different levels of description.
Conceptual Modeling: Foundations and Applications
This Festschrift volume, published in honor of John Mylopoulos on the occasion of his retirement from the University of Toronto, contains 25 high-quality papers, written by leading scientists in the field of conceptual modeling. The volume has been divided into six sections. The first section focuses on the foundations of conceptual modeling and contains material on ontologies and knowledge representation. The four sections on software and requirements engineering, information systems, information integration, and web and services, represent the chief current application domains of conceptual modeling. Finally, the section on implementations concentrates on projects that build tools to support conceptual modeling. With its in-depth coverage of diverse topics, this book could be a useful companion to a course on conceptual modeling.
