Textbook of Drug Design and Discovery, Third Edition Review

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(More customer reviews)but the content is excellent. For an practicing organic chemist learning medicinal chemistry, I have read/browsed many books, and have settled on this one and Wermuth's "The Practice..." as my 'A-team'.
Unfortunately, the paperback binding will crack & quickly compromise the retention of the pages, but that is not the authors fault. The content is what matters & if you are an Organic Chemist & want to learn Med Chem, I would strongly suggest you start here. I would compare this to the 'Burger' of the old days, before it became an unaffordable encylclopedia.

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Building on the success of the previous editions, Textbook of Drug Design and Discovery has been thoroughly revised and updated to provide a complete source of information on all facets of drug design and discovery for students of chemistry, pharmacy, pharmacology, biochemistry, and medicine.The book follows drug design from the initial lead identification through optimization and structure-activity relationship with reference to the final processes of clinical evaluation and registration. Chapters investigate the design of enzyme inhibitors and drugs for particular cellular targets such as ion channels and receptors, and also explore specific classes of drug such as peptidomimetics, antivirals and anticancer agents. The use of gene technology in pharmaceutical research, computer modeling techniques, and combinatorial approaches are also included.

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Computer Modeling of Chemical Reactions in Enzymes and Solutions (Wiley Professional) Review

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(More customer reviews)This book has become a classic in the field. While we now have more modern and efficient methods (like DFT) the basic approach remains the same, so it is still worth reading.
The book comes with source code in Fortran. Its main problem is that you cannot download the code in the book from the Internet, but you can get revised, more modern versions, so it's not that bad after all. The source in the book is rather limited, oriented to illustrating the points and the calculations, but if you combine it with some other reference, like Allen-Tildesley's (the other major classic), it is enough to proceed with your own implementation (should you be interested in doing one).
The math I found a bit difficult to follow as it does not match similar approaches in other quantum mechanics or molecular mechanics books, but once you get used to it, it is OK.
Coverage is fair for the date it was written and sticks to the title topic covering it very well. It is worth reading to understand many of the modern approaches, how they work and what they mean. Actually, if you are interested in this topic (enzymatic reactions) your only other resource would be to gather a number of other books and combine their contents yourself in your mind. A lot more work than having this one.
To a large extent, modern (as of 2010) work still relies mostly on the approaches exposed in this book, so it is bang for the buck, but it would be advisable to complement it with some readings on modern DFT approaches as these are now slowly taking over the semiempirical approaches described here.

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This practical reference explores computer modeling of enzyme reations--techniques that help chemists, biochemists and pharmaceutical researchers understand drug and enzyme action.

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Process Dynamics: Modeling, Analysis and Simulation Review

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(More customer reviews)This is a very clearly written book. Its contents go from easy to difficult, step by step. It's very good for beginners. For advanced readers, they may want to skip the first several chapters and read from the middle.

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Modeling, analysis and simulation of chemical processes is increasingly central to the work of chemical engineers -- but it is rarely covered in depth in process design guides. This book fills that gap. It is a comprehensive introduction to process modeling and dynamics using the powerful MATLAB and SIMULINK analysis tools.Start by understanding the rationale for process modeling, and why it is becoming so critically important. Then, review all the fundamental numerical techniques involved, including algebraic equations and numerical integration. Walk through linear systems analysis in detail, learning how to linearize non-linear models, solve linear nth Order ODE models, work with Laplace transforms and transfer function analysis, and much more. Finally, learn how to use today's increasingly-important non-linear techniques, such as phase plane analysis, quadratic maps bifurcation behavior, and analysis of chaotic behavior via Lorenz equations.For all chemical engineers, from Ph.D. professionals to non-degreed technicians and students.

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DNA Microarrays and Gene Expression: From Experiments to Data Analysis and Modeling Review

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(More customer reviews)This book tries to combine a practical and theoretical point of view concering microarray expermiments and the data analyis thereof. This is a very honourable goal. Unfortunatelly, it fails. An indicator for this can already be seen in the low number of pages. This book has less than 140 pages (I exclude the last chapter and the appendix). It is clear, that it is impossible to discuss in detail this topic in this limited number of pages. Hence, during reading the chapters one gets the feeling, that one reads short essays which are stringed together. At no point the authors go into detail but give only a short idea and references.
I see no reason, why I should recommend this book to anyone. It is in its current form just immature. My prediction: There will be no second edition because even its basic substance is very weak.
Some words to the last chapter (systems biology). This is indeed the most interesting and best chapter of the book (35 pages) without going into details as the rest of the book. I think according to this chapter one realize under which premise this book was written. Unfortunatelly, combining buzz worlds in short essays is not enough for a good book. Sorry guys, I think you can do better!

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Massive data acquisition technologies--such as genome sequencing, high-throughput drug screening, and DNA arrays--are in the process of revolutionizing biology and medicine. This concise, user-friendly and interdisciplinary guide to DNA microarray technology is an introduction and a reference for both biologists and computational scientists. The authors describe the underlying technologies and offer an awareness of the "noise" and pitfalls present in the data generated. They also provide an idea of the different data mining techniques and algorithms that are available to interpret data, and the advantages and disadvantages of each in differing situations.

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Modeling Biological Systems:: Principles and Applications Review

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(More customer reviews)This book is a complete dissapointment.
It does not offer any real scientific physical models which then can be transformed in an algorithm and being simulated but is is merely a conglomerate of several statistical procedures commonly used in Biology for interpreting data (maybe copied by the author and collected from other books, as nothing that he presents is new!). This book does not offer any scientific, fundamental insight in how to really model and simulate properly complex biological systems, it is also written in a very unscientific, popular style. The mathematical level corresponds to High-School and as the author says in the preface: "The process of modeling biological systems is certainly not a science, but neither is it as unconstrained as the creation of a work of pure art that is evaluated solely on its esthetic content". I think that nonsense speaks for itself. This author should rather write novels instead of cobbling something together that gets the label "scientific" on the cover.
The book is not trash, the author does have collected some of the simplest "models" there are to describe collections of data in statistical terms, but this has NOTHING to do with proper scientific numerical and mathematical modeling and even less with scientific Computing in the field of biological complex systems, e.g. how to simulate membranes, proteins using Quantum Chemistry or Molecular dynamics techniques.
All in all I judge this book as a complete waste of money and as completely superfluous.

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This is the second edition of a textbook currently published by Springer for a course in mathematical modeling and computer simulation for biologists at the advanced undergraduate and introductory graduate level. The audience for this edition is similar to that of the previous one: advanced level courses in computational biology, as well as researchers retooling themselves. This new edition includes a CD-ROM with real examples of models as teaching tools.

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