Our search has the following Google-type functionality:
If you use '+' at the start of a word, that word will be present in the search results.
eg. Harry +Potter
Search results will contain 'Potter'.
If you use '-' at the start of a word, that word will be absent in the search results.
eg. Harry -Potter
Search results will not contain 'Potter'.
If you use 'AND' between 2 words, then both those words will be present in the search results.
eg. Harry AND Potter
Search results will contain both 'Harry' and 'Potter'.
NOTE: AND will only work with single words not phrases.
If you use 'OR' between 2 single words, then either or both of those words will be present in the search results.
eg. 'Harry OR Potter'
Search results will contain just 'Harry', or just 'Potter', or both 'Harry' and 'Potter'.
NOTE: OR will only work with single words not phrases.
If you use 'NOT' before a word, that word will be absent in the search results. (This is the same as using the minus symbol).
eg. 'Harry NOT Potter'
Search results will not contain 'Potter'.
NOTE: NOT will only work with single words not phrases.
If you use double quotation marks around words, those words will be present in that order.
eg. "Harry Potter"
Search results will contain 'Harry Potter', but not 'Potter Harry'.
NOTE: "" cannot be combined with AND, OR & NOT searches.
If you use '*' in a word, it performs a wildcard search, as it signifies any number of characters. (Searches cannot start with a wildcard).
Search results will contain words starting with 'Pot' and ending in 'er', such as 'Potter'.
Systems Biology: Mathematical Modeling and Model Analysis is a rich resource of mathematical methods and approaches that can be utilized to analyze and understand biological systems. It will be particularly attractive to engineers and mathematicians, who want to learn the basics of modern biology in a condensed fashion and then apply the tools of their trades to relevant biological questions.Systems Biology presents key phenomena of molecular biology in a succinct, introductory manner while expecting the reader to have some prior knowledge of basic math, including probabilities, integrals, matrices, differential equations, and Laplace transforms. Building upon this knowledge, Systems Biology devotes a good portion of the material to state-of-the-art model diagnostics and engineering techniques, such as linear systems analysis and control theory, which so far are rarely found in systems biology texts and are therefore a welcome addition to the repertoire of textbook literature. For instance, important topics like identifiability, observability, and robust control are seldom encountered in introductory texts on systems biology but discussed here in some detail. Laudably, all topics are illustrated with step-by-step examples, and many of them are reinforced with exercises. -Eberhard Voit, Georgia Institute of Technology Computational modeling of biological circuits, networks and pathways is one of the most exciting areas in biology today, and Andreas Kremling's Systems Biology: Mathematical Modeling and Model Analysis is a meticulous and far-reaching treatment of this critically important subject. This book clearly aims to be comprehensive without sacrificing depth, and the result is an exhaustive survey of modeling approaches. Each chapter is thoughtfully crafted to draw in novices to the field while still engaging to experts. Additionally, a number of well-designed exercises complement each chapter. I found the sections on model analysis and control theory particularly useful and relevant. -Markus Covert, Stanford University [Systems Biology: Mathematical Modeling & Model Analysis] is a well-structured (the collection and order of chapters is excellent), provides comprehensive material of fundamentals, theory, and applications of methods used in systems biology. It is a user-friendly guide that I believe can serve as a tutorial for students specializing in systems biology as well as a reference work for established researchers in the field. I highly recommend this book to the reader. -Christian T. K.-H. Stadtlander, Journal of Biological Dynamics, November 2017