This book describes the use of models in process engineering. Process engineering is all about manufacturing--of just about anything! To manage processing and manufacturing systematically, the engineer has to bring together many different techniques and analyses of the interaction between various aspects of the process. For example, process engineers would apply models to perform feasibility analyses of novel process designs, assess environmental impact, and detect potential hazards or accidents.
To manage complex systems and enable process design, the behavior of systems is reduced to simple mathematical forms. This book provides a systematic approach to the mathematical development of process models and explains how to analyze those models. Additionally, there is a comprehensive bibliography for further reading, a question and answer section, and an accompanying Web site developed by the authors with additional data and exercises.
* Introduces a structured modeling methodology emphasizing the importance of the modeling goal and including key steps such as model verification, calibration, and validation.
* Focuses on novel and advanced modeling techniques such as discrete, hybrid, hierarchical, and empirical modeling
* Illustrates the notions, tools, and techniques of process modeling with examples and advances applications

Metabolic engineering is a new field with applications in the production of chemicals, fuels, materials, pharmaceuticals, and medicine at the genetic level. The field's novelty is in the synthesis of molecular biology techniques and the tools of mathematical analysis, which allow rational selection of targets for genetic modification through measurements and control of metabolic fluxes. The objective is to identify specific genetics or environmental manipulations that result in improvements in yield and productivities of biotechnological processes.
Key features of the book are pathway integration and the focus on metabolic flux as a fundamental determinant of cell physiology. The book keeps mathematical complexity to a minimum, and provides a glossary of biological terms to facilitate use of the book by a broader spectrum of readers. A web page exists to communicate updates of the codes and homework problems.

Key Features
* Demonstrates metabolic engineering in action with numerous examples of pathway modification
* Includes methods for identifying key enzymes in metabolic networks
* Contains a comprehensive review of metabolic biochemistry
* Discusses metabolic regulation at the gene, enzyme, operon, and cell levels
* Explains concepts of stoichiometry, kinetics, and thermodynamics of metabolic pathways
* Minimizes mathematical complexity
* Links to a Web page to communicate updates of the software code and homework problems

Established in 1960, Advances in Heterocyclic Chemistry is the definitive serial in the area-one of great importance to organic chemists, polymer chemists, and many biological scientists. Written by established authorities in the field, the comprehensive reviews combine descriptive chemistry and mechanistic insight and yield an understanding of how the chemistry drives the properties.

Volume 23 of Advances in Chemical Engineering covers the active field of process synthesis. There are currently three prevelant approaches to complex process synthesis strategies: heuristics-based selection, geometric representation, and optimization methods. This volume addresses a variety of these synthesis strategies for process subsystems, representing only a sample of the state-of-the-art of process synthesis research. The five papers in this volume address quite different process subsystems and application areas but still combine basic concepts related to a systematic approach. All five of the papers develop successful synthesis methods for their respective cutting-edge applications. As a group, the papers serve to highlight many unresolved issues in process synthesis and also provide guidelines for future research.
Key Features
* Considers current approaches to process synthesis problems
* Examines areas of possible future research
* Articles written by leading experts in the field

Volumes 21 and 22 of Advances in Chemical Engineering contain ten prototypical paradigms which integrate ideas and methodologies from artificial intelligence with those from operations research, estimation andcontrol theory, and statistics. Each paradigm has been constructed around an engineering problem, e.g. product design, process design, process operations monitoring, planning, scheduling, or control. Along with the engineering problem, each paradigm advances a specific methodological theme from AI, such as: modeling languages; automation in design; symbolic and quantitative reasoning; inductive and deductive reasoning; searching spaces of discrete solutions; non-monotonic reasoning; analogical learning;empirical learning through neural networks; reasoning in time; and logic in numerical computing. Together the ten paradigms of the two volumes indicate how computers can expand the scope, type, and amount of knowledge that can be articulated and used in solving a broad range of engineering problems.
Key Features
* Sets the foundations for the development of computer-aided tools for solving a number of distinct engineering problems
* Exposes the reader to a variety of AI techniques in automatic modeling, searching, reasoning, and learning
* The product of ten-years experience in integrating AI into process engineering
* Offers expanded and realistic formulations of real-world problems

Advances in Chemical Engineering, Volume 19 reflects the major impact of chemical engineering on medical practice, with chapters covering polymer systems for controlled release, receptor binding and signaling, and transport phenomena in tumors. Other key topics include oil refining, pollution prevention in engineering design, and atmospheric dynamics.

The advent of genome sequencing and associated technologies has transformed biologists' ability to measure important classes of molecules and their interactions. This expanded cellular view has opened the field to thousands of interactions that previously were outside the researchers' reach. The processing and interpretation of these new vast quantities of interconnected data call for sophisticated mathematical models and computational methods. Systems biology meets this need by combining genomic knowledge with theoretical, experimental and computational approaches from a number of traditional scientific disciplines to create a mechanistic explanation of cellular systems and processes.
Systems Biology I: Genomics and Systems Biology II: Networks, Models, and Applications offer a much-needed study of genomic principles and their associated networks and models. Written for a wide audience, each volume presents a timely compendium of essential information that is necessary for a comprehensive study of the subject. The chapters in the two volumes reflect the hierarchical nature of systems biology. Chapter authors-world-recognized experts in their fields-provide authoritative discussions on a wide range of topics along this hierarchy. Volume I explores issues pertaining to genomics that range from prebiotic chemistry to noncoding RNAs. Volume II covers an equally wide spectrum, from mass spectrometry to embryonic stem cells. The two volumes are meant to provide a reliable reference for students and researchers alike.

Familiar sciences of biology, physics, chemistry, cybernetics, and computational methods for dealing with vast new data sets of information at molecular and sub-molecular levels are morphing into new sciences. Some exist beneath our line of sight where laws of nature hover between Newtonian and quantum mechanics. New fields of cyber-, bio-, nanotechnology and systems biology raise arcane new concepts. The completed human genome has led to an explosion of interest in genetics and molecular biology. The view of the genome as a network of interacting computational components is well established and here writers explore it in new ways. These systemic approaches are timely in light of the availability of an increasing number of genomic sequences, and the generation of large volumes of biological data by high-throughput methods. Suitable for two-semesters of study, the works surveys genomics principles in the 13 chapters of Vol I, and networks and models in the 14 chapters of Vol II. Both, as a two-book set, will serve as core foundation titles for Dennis Shasha's Series in Systems Biology, establishing the principles and challenges for this emerging field of study. In each chapter world-renowned experts trail-blazing in their respective fields will review corresponding topics as well as current and planned research. Chapters will treat the integrated study and analysis of biological systems by use of data and information about the system components in their entirety, as opposed to the study of individual components in isolation. Systems Biology courses are popping up all over the place and biology, computer science, and bioinformatics programs are the primary potential takers. The editors plan books for a very wide audience, at the same time providing a comprehensive repository of up-to-date overviews and predictions for a number of inter-related sub-fields within this hierarchy. Intended readers include graduate students plus academic and professional researchers of genomics, bioinformatics, molecular biology, biochemistry, bioengineering, and computer systemic approaches to those fields. By comparison, Shasha's first Systems Biology Series title, Amos's Cellular Biology, is a book for technologists using biology as a vehicle to do something else, whereas this is a book about systems and related technologies in service to biologists. The volume editors plan to review or have reviewed, and to edit the invited chapters for content and consistent conceptual level, each chapter contributing uniquely to the key aspects of the Systems Biology hierarchy. A few chapter contents may date after two years, but the majority will endure for longer-term reference use because they treat methodologies and provide sample applications.