- R.M.M. Mattheij, S.W. Rienstra, J.H.M. ten Thije Boonkkamp. Partial Differential Equations: Modeling, Analysis, Computation. SIAM (www.siam.org/books), 2005. PDEs are used to describe a large variety of pysical phenomena, from fluid flow to electromagnetic fields, and are indispensable to such disparate fields as aircraft simulation and computer graphics. While most existing texts on PDEs deal with either analytical or numerical aspects of PDEs, this innovative and comprhensive textbook features a unique approach that integrates analysis and numerical solution methods and includes a third componentmodelingto address real-life problems.
- Bo Einarsson (ed.) Accuracy and Reliability in Scientific Computing. SIAM (www.siam.org/books), 2005. Often because of the high states involved, it is essential that results computed using software be accurate, reliable, and robust. Unfortunately, developing accurate and reliable scientific software is notoriously difficult. This book investigates some of the difficulties related to scientific computing and provides insight into how to overcome them and obtain dependable results. The tools to assess existing scientific appications are described, and a variety of techniques that can improve the accuracy and reliability of newly developed aplications is discussed. Accuracy and Reliability in Scientific Computing will help computer scientists address the problems that affect software in general as well as the particular challenges of numerical computionation.
- Evolutionary Dynamics: Exploring the Equations of Life by Martin Nowak Belknap Press: 2006. 384 pp. $35.
- L. Koralov, Y. G. Sinai Probability Theory, Random Processes, Random Fields, 2nd edition, 2006.
- W. Ching, M. K. Ng Markov Chains: Models, Algorithms, and Applications, 2006.
- R. C. Deonier, S. Tavare, M. S. Waterman Computational Genome Analysis, 2005. [bought]
- R. Gentleman, V. Carey, W. Huber, R. Irizarry, S. Dudoit Bioinformatics and Computational Biology Solutions Using R and Bioconductor, 2005.
- R. Nielsen (ed) Statistical Methods in Molecular Evolution, 2005. [For those biologist and mathematicians willing to expand their knowledge in Molecular Evolution, this book is the right source. Chapters were written by leading researchers in their fields and are divided in sections from basic concepts to more advanced methods of molecular analysis. Language is clear, topics well organized. I recommend this book to any grad student, post doc or researcher interested in clear, informative reviews in several areas of Molecular Evolution.]
- M. Kimura. (1983) The Neutral Theory of Molecular Evolution. Cambridge University Press, Cambridge, UK.
- W.-H. Li. (1997) Molecular Evolution. Sinauer Associates, Sunderland, MA.
- J. Gillespie. (1991) The Causes of Molecular Evolution. Oxford University Press, Oxford, UK.
- J. Felsenstein Inferring Phylogenies, 2003. [bought]
- R. D. M. Page and E. C. Holmes Molecular Evolution: A Phylogenetic Approach, 1998.
- P. G. Higgs and T. K. Attwood Bioinformatics and Molecular Evolution, 2005.
- D. Graur and W-H Li Fundamentals of Molecular Evolution, 2000. [This is a very complex, indepth, informative book on molecular and genetic evolution. Explainations of genetic drift, mutation rates, times to fixation, patterns in evolutionary changes. Lots of statistical information on how allele frequencies change. Written for a knowledgable audiance with a good understanding of evolution and genetics. Gives informative understanding of trends in evolution beyond natural selection. Supports neutral theory of evolution quite strongly.]
- M. Nei and S. Kumar Molecular Evolution and Phylogenetics, 2000. [Nei and Kumar's "Molecular Evolution and Phylogenetics" is basically an updated version of Nei's 1987 "Molecular Evolutionary Genetics" book. Accordingly, attention is shifted to reviewing many recent advances in methods of phylogenetic inference with an obvious bias towards distance methods, particularly those which the senior author devised. In fairness, they give decent coverage to the more popular parsimony and likelihood methods as well. The great strength of the book is the number of real examples used to illustrate properties of the methods, and their focus on statistical methodology without miring the reader in detailed mathematics. The disappointment is that while breadth of coverage is tolerable, depth is lacking. Expanding their views on the shortcomings of likelihood in choosing tree topology and likelihood ratio-tests in choosing models of sequence evolution would have been most enlightening, particularly as these issues have been brushed lightly aside by phylo-likelihoodists. Other methods (Hadamard transformations, Bayesian phylogenetic inference) were absent altogether. Further the chapter on molecular clocks was disappointing--old 1980s controversies were rehashed, while there was nothing on methods that relax the assumption of rate constancy while still allowing divergences to be dated. Admittedly some of this is very new and research is ongoing, but there isn't even a hint of these developments in this chapter. Another plus though is the addition of a chapter on inferring ancestral states of molecular sequences. Unlike Molecular Evolutionary Genetics, far too little of the book is devoted to methods at the population level, and what is there again smacks of state-of-the-art 15-20 years ago. I was hoping for much more coverage of microsatellite and AFLP data. There was very little for either, while now rarely-used RFLPs were given extensive coverage. In short, this book was too short, particularly for the price, and I almost gave it 3 stars rather than 4. However, if you are a phylogeneticist, you will probably want to have this book on your shelf. A lighter introduction for the uninitiated would be Rod Page's "Molecular Evolution" or Graur and Li's "Fundamentals of Molecular Evolution". However, my hopes for a good comprehensive text and reference on phylogenetic methods now rest on publication of Joseph Felsenstein's "Inferring Phylogenies".] [bought]
- Uri Alon An Introduction to Systems Biology: Design Principles of Biological Circuits, 2006 [Received via mail; on Sci II 534 corkboard. This new text presents recently discovered design principles that govern the structure and behavior of biological networks and provides a mathematical framework for understanding and event diesing biological circuits. The treatment requires only basic mathematics and includes a review of the necessary backgroun material. It fills a significant need for an intrroudciton to the concepts, principles, and mathematical tools that will form the basis of future developments in the field.]