genetics books

	On Genetic Interests: Family, Ethnicity, and Humanity in an Age of Mass Migration
	By: Frank Kemp Salter ISBN: 1412805961 Publisher: Transaction Publishers Release Date: 13 November, 2006 Bioscience book rank: 62017	the fact is, that the greatest hatred are amoung peoples who are genetically very similar through out human history. (German, English in WWII, Chinese, Japanese, Korean through out history etc). in the worst human conflict, WWII, American, English, Chinese, Russian on one side, German, Italian, Japanese on the other side. i can't see any "genetic" stratification in that. and now, the greatest nation(at least the most powerful one)-- America, have no genetic basis. and Germany, the country that advocated racial purity is not even a entity until a few hundred years ago.(before that, it is loosely connected tribal...) <br /> <br />anecdote evidence aside, quantitatively, traditional ethnic division can only 1% explain human genetic variation(my estimation, no hard data), so if these is a genetic base for ethnic based thinking(racism), it must be a very weak third order effect. it is akin to rate attractiveness among individuals by the body mass based on newton's law. we know it is absurd, even through newton's law is correct. <br /> <br /> The importance of this book is that it explains that racism is rational. That is, by favoring people of one's own race, a person is increasing his fitness. This means that the anti-racists are trying to convince people to lower their fitness and eventually go extinct. In evolutionary terms, racism is adaptive and anti-racism is maladaptive. A further implication is that racists are in harmony with man's nature (indeed, the nature of all living things - to pass on the unique forms of one's genes), and that anti-racists, who go ballistic at any tinge of racism, are psychologically pathological. <br /> While there is some math in the book, it can be understood by the average person who thinks carefully about the definitions of the terms. The reader should consult the glossary in the back of the book and be sure he understands the difference between "individual fitness," "absolute fitness," "relative fitness," and "inclusive fitness." Chapter 2 is the most important and difficult chapter and should be read several times. The need to identify with others like oneself, and to be with one's own kind, is a major component of human nature and so ethnic identity is a powerful force in human affairs. Group members have "ties of blood" that make them "special" and different from outsiders. This is why patriotism is almost always seen as a virtue and an extension of family loyalty. It also explains why ethnic remarks so easily become "fighting words." Culture builds on genetic similarity and is bound together by it. Patriotism is preached in kinship terms. Nations are the "motherland" or the "fatherland" and unions and churches refer to their members as "brothers" and "sisters." <br /> <br />Salter draws out the implications, however politically incorrect, for immigration policies, citizenship law, affirmative action, multiculturalism, and other ways of allocating resources within and between states. There are constraints on how much diversity can be appreciated. <br /> <br />On Genetic Interests extends evolutionary theorizing, including my own Genetic Similarity Theory, to the new ground of interpersonal and ethnic relations such as within-group cohesion and between-group conflict. It discusses studies on likeness in social partners such as spouses and best friends. Most importantly, it applies genetic calculations and finds that the average coefficient of kinship within most ethnic groups is about as high as between half-siblings, aunt and nephew, or grandparent and grandchild. Thus, ethnic nepotism is no mere poor relation of family nepotism-it is virtually a proxy for it. Because we have many more co-ethnics than relatives, the aggregate mass of genes shared with the former dwarfs that shared with the latter. <br /> <br />Frank Salter, a political scientists and ethologist at the Max Planck Institute in Munich, argues persuasively in this book that shared genes are the glue of sociality.On Genetic Interests goes so far as to refer to the mind as having an "innate descent-group module" (p. 102). It uses this concept to explain the universality of ethnic nepotism. This is heartening because many social scientists and sociobiologists alike have been reluctant to even consider applying gene-based similarity to ethnic and national preferences. Following World War II, few political scientists and historians have considered inter-group conflict from a Darwinian viewpoint. Partly in an effort to insure that they are perceived as in no way condoning racism, many evolutionists have minimized the theoretical possibility of a biological underpinning to ethnic, national, and racial favoritism. As the late, great, evolutionary biologist William Hamilton himself remarked in 1987, while noting why kin discrimination even among animals is not more readily expected, "in civilized cultures, nepotism has become an embarrassment." <br /> <br />Social scientists and historians have been quick to condemn the extent to which political leaders or would-be leaders have been able to manipulate ethnic identity. But the questions they never ask, let alone attempt to answer is, "Why is it always so easy?" and "Why can a relatively uneducated political outsider set off a race riot simply by uttering a few well delivered ethnic epithets?" On Genetic Interests provides an illuminating answer. <br /> <br />
	Unlocking Your Genetic History: A Step-by-Step Guide to Discovering Your Family's Medical and Genetic Heritage (National Geneological Society Guide, 6)
	By: Thomas H. Shawker ISBN: 1401601448 Publisher: Thomas Nelson Release Date: 11 August, 2004 Bioscience book rank: 412811	This is the fifth in a new series of instructional volumes sponsored by the National Genealogical Society, and when I read and reviewed the first four in September 2004, I was very impressed. The authors all were well known and trustworthy and their treatment of old subjects (such as basic research principles) and not so old (setting up a genealogy web site) was generally quite well done. But this one is somewhat different. The subject of "genetic genealogy" is still very much unknown territory to almost all genealogists, even the professionals. It's not even a "social science," so one has to acquire a certain amount of new background knowledge even before delving into it. This author is also less likely to be known to most genealogists outside his own specialty: He's a medical doctor, a Section Chief at the National Institutes of Health -- although he has also been president of the Prince George's County Genealogical Society and chairs the NGS committee on Family Health and Heredity, so he certainly can't be called a beginner. Personally, I've been "doing genealogy" for more than three decades, but my background is in history, library science, and archival management, with no training and very little experience in the life sciences. Over the past few years, I've read dozens of articles in all sorts of journals on the subject of applying recent breakthroughs in DNA mapping to family lineages, but even though I've been intrigued by the possibilities, the result has generally been to confuse myself even further. I'm pleased to say that Shawker has supplied an antidote to my ignorance. <br />The first section lays out the reasons you need to know about your family's health history, because "ignorance is not bliss." This is especially true among Acadian families, as in other geographically or culturally isolated populations (Ashkenazic Jews, Amish, Afrikaners, Pacific Islanders) which suffer from a predisposition to assorted diseases and conditions. He follows this with a primer on the nature and process of genetics that is very well written and easy to understand (even for me), with a full explanation of dominant and recessive traits. He includes plenty of case studies, too, from King George III and the Romanovs to Gilda Radner. Then comes a section on compiling a health history, drawing up a medical pedigree, interpreting the results, and being aware of the warning signs for various important and common genetic diseases. <br />The part of the book I read most closely is that which explains in great detail, with many examples and illustrations, how the Y-chromosome is passed on, unchanged, from father to son to grandson, and so on, through the male line, and how the mitochondrial DNA is likewise passed without change from mother to daughter to granddaughter. The famous Thomas Jefferson-Sally Hemmings case provides a good example of how all this works, and how one can use deduction to track lineages that are a mix of males and females. Numerous charts and diagrams also increase one's understanding. Shawker also lays out a strategy for developing a family association DNA project to determine the relationships between groups with identical surnames, and he repeatedly makes the point that no testing program can prove anything: It can only serve as another research tool in conjunction with more traditional genealogical methods. <br />Finally, the author addresses the ethical and legal issues inherent in genetic testing, whether for family research or to identify an inherited tendency to contract a disease, and includes a lengthy guide to other resources on the Internet - especially important in a fast-developing area like this. There's an excellent bibliography, too. Shawker is that rare scientist who can write coherently for the layman and I can recommend this excellent work to any individual or library with an interest in genealogical methodology.
	Genetic Analysis of Complex Traits Using SAS
	By: Arnold M. Sexton ISBN: 1590475070 Publisher: Books by Users Press Release Date: 10 November, 2004 Bioscience book rank: 547658	Regardless of how one feels about SAS as a programming language, it is readily apparent that it is very popular in areas such as financial and biological modeling. This book gives an introduction to how it is used in genetic analysis, and even though each chapter is written by a different author, the book can be useful to those (such as this reviewer) who are not experts in genetics but who may be called upon to apply their mathematical and statistical knowledge to problems in genetics (but using SAS instead of some other programming language to do so). Although the book assumes a thorough knowledge of genetics, it can still be read profitably by anyone who has a background in SAS and some knowledge of genetics. Being an interpreted language, SAS performance can be a problem with many applications, and its value in science is questionable for projects that require heavy computational power. For medium-sized projects though it can be helpful, even though its semantics can be hard to get used to for those who have programmed in more object-oriented environments. <br /> <br />SAS has been used widely to perform statistical studies in genetics using "classical" tools such as multivariate analysis and maximum likelihood, but there is one chapter in this book where Bayesian inference techniques are used for genetic analysis. In addition, and this makes the discussion in the chapter even more valuable, is that the estimation of the posterior distribution is done using Markov chain Monte Carlo (MCMC) techniques. The first genetics problem on which this is done regards two-point linkage analysis where Bayesian inference is used to estimate the recombination rate in a backcross between two completely homozygous lines for each of two loci. Even though this problem has an analytical solution, the authors use a simple Monte Carlo simulation to estimate the posterior mean and variance of the recombination rate to motivate how SAS can be used in this case.It should be pointed out here that the authors use SAS PROC Capability in their code and not all readers have this in their SAS implementation, but it can be replaced by PROC Univariate with no problems. This problem is generalized to the case of where there are three linked marker loci, with Bayesian inference and MCMC (via the Metropolis-Hastings algorithm) used to estimate the loci order and the recombination rates between the markers. The authors give the actual SAS code to implement this analysis, which is very readable (in spite of the ancient and annoying "goto" statements that are used within it). MCMC techniques are essential though in more general problems where analytical solutions are not possible. This is the case for a general genetic map construction that the authors discuss but do not give the explicit SAS code for (but it can be found on the Website that is associated with the book). They discuss briefly the pitfalls in doing MCMC for this case, and give a few alternatives. Bayesian inference is then applied to QTL analysis for the simple case of a single QTL model for backcrossing.
	Human Genetics: Concepts and Applications
	By: Ricki Lewis ISBN: 0072848537 Publisher: McGraw-Hill Higher Education Release Date: January, 2007 Bioscience book rank: 582950
	The Nonlinear Workbook: Chaos, Fractals, Celluar Automata, Neural Networks, Genetic Algorithms, Gene Expression Programming, Support Vector Machine, Wavelets, Hidden Markov M
	By: Willi-Hans Steeb ISBN: 9812562915 Publisher: World Scientific Publishing Company Release Date: 15 July, 2005 Bioscience book rank: 545598	This book is an overview of all of the components of nonlinear dynamics. Nonlinear dynamics is a field of study that enables well-constructed predictive modeling of systems that might be difficult to solve otherwise. Such continuous systems were first widely modeled by ordinary and differential equations, but with the passage of time there are now tools and mathematical models at our disposal that make for a much more concise model of many systems. This workbook tries to touch on all of those mathematical tools. The first six chapters of the book has to do with modeling such complex systems in general, and the rest of the book is a survey of the tools needed to perform complex modeling. The book's format is that of briefly explaining a concept in a few pages, and then presenting a computer program that demonstrates the concept just explained. The explanations are very clear and concise, there are plenty of equations shown, and the accompanying code is well commented. If you want to really drill deeply into any of the concepts then you are going to need some other books. I suggest that for further reading for the mathematically inclined that you pick up "Chaos: An Introduction to Dynamical Systems" by Kathleen Alligood. For scientists that want to see specific problems that can be solved by dynamical systems I suggest the excellent "Nonlinear Dynamics and Chaos: With Applications in Physics, Biology, Chemistry, and Engineering" by Strogatz. The only real complaint I have against this book is that there is uneven coverage of different tools. For example, the author has a great deal to say about neural networks and fuzzy logic, but has very short chapters covering discrete wavelets and cellular automata. More material would have been great, since it is hard to find good books on discrete wavelets and cellular automata in particular. Some readers may also be annoyed that much of the book are code listings of the various demonstration programs. Overall, I would highly recommend it as one of several books that anyone interested in dynamical systems should definitely own. In particular, those individuals interested in the techniques of algorithmic composition of music might find this book a good jumping off point for studying the tools and techniques that make such compositions possible. The topics covered in this book are all important from the standpoint of applications in physics, engineering, computer science, financial engineering, and computational biology. It is written for the person just getting started in these topics, and the author does a fairly good job of discussing them. Readers should not expect, and they will not get, in-depth discussions on these topics, as this would swell the book to 10 times the size. They will however get preparation for moving on to more advanced and complete treatments. <p> Nonlinear and chaotic maps are considered in chapter 1, with elementary definitions given and six different examples of maps discussed. In discussing the calculation of numerical trajectories of maps, the author deals with the problem of large initial values for the maps and how to implement these in SymbolicC++ and Java. He also shows how to write/read data to a file using C, C++, and JAVA. The exception handling capability of JAVA comes out nicely, but no performance comparison between the three languages for simulating the maps is given by the author. The language REDUCE is used to discuss the stability of the fixed points of the logistic equation, but the code would be useless to the reader who did not have REDUCE since some of the function calls are hidden from the reader. Useful programs are given for calculating the Lyapunov and autocorrelation functions. In addition, C++ programs are given for evaluating the correlation integral for the Henon map. The programs he develops in this chapter can serve as a quick benchmark for one's own programs that calculate the same quantities. <p> In chapter 2, the author discusses methods for studying time series, including the Lyapunov and Hurst exponents. These two quantities are of enormous importance in the study of dynamical systems, financial data, and network performance. The C++ program that the author gives for calculating the Hurst exponent will not work for arbitrary time intervals. This is followed in the next chapter by a consideration of autonomous systems of ordinary differential equations. The classification of fixed points is considered, and the important concept of a homoclinic orbit. The author gives a nice JAVA program that finds the homoclinic orbit of an anharmonic differential equation using the Lie series technique. The phase portrait of the Van der Pol oscillator is calculated using the Runge-Kutta technique in a C++ program, along with the Lotka-Volterra system from mathematical biology. <p> Hamiltonian mechanics is discussed in chapter 4, with the important Henon-Heiles model from astrophysics is discussed and JAVA programs given for studying its behavior using the Poincare section technique. Newcomers to this technique will appreciate seeing it done here explicitly. Integrability of Hamiltonian systems using the Lax representation and Floquet theory are also treated, but only at a very rudimentary level. Dissipation is included in the next chapter, and the author discusses the classification of fixed points according to their stability. Lyapunov exponents are again brought into the picture, and the phenomenon of hyperchaos is discussed. Some bifurcation theory is introduced with an example of the Hopf bifurcation. Chapter 6 studies nonlinear driven systems, with the Duffing oscillator treated, and the author gives a useful program for calculating the autocorrelation function of this system. The controlling of chaos with feedback and non-feedback controls is the subject of the next chapter, mostly in the context of difference maps. Fractals finally get introduced in chapter 8, with iterated function systems defined but proofs of their properties omitted. The author gives programs for calculating various popular fractals, such as the dragon, Sierpinski gasket, Koch curve, the Mandelbrot set, and the Julia set. The main disappointment in this chapter is that the author does not give programs for calculating the Hausdorff dimension or capacity, quantities that are notoriously difficult to get a meaningful computational handle on. <p> The author switches gears in the next chapter and discusses cellular automata, which have recently made a comeback, especially in research on quantum computation. The discussion is too brief however, and does not allow the reader to gain an appreciation of the properties of these important objects. Chapter 10 gives a brief overview of some techniques for solving differential equations, such as the Euler method and the Lie series technique. The latter is not commonly treated in beginning books so its inclusion here is helpful. Symplectic integration is also discussed briefly, but the author does not discuss how to check the integrators using backward integration, which is commonly used in conservative systems modeled by symplectic maps. <p> Chapter 11, covering neural networks, is the most well-written in the book, and the newcomer to the field will get a fairly decent introduction to the subject. The supplied programs serve to illustrate some of the important concepts in neural networks, such as the Hopfield model, the Kohonen network, the perceptron learning algorithm, and the back-propagation algorithm. <p> Chapter 12 is an introduction to genetic algorithms, and I find this one particularly nice also, as it does give a rudimentary introduction to what evolutionary algorithms are all about, and gives some elementary genetic programs that find the maximum of one- and two-dimensional maps. He also discusses simulated annealing, and gives a useful program that allows the reader to see clearly how this technique works. <p> The last chapter covers fuzzy sets and fuzzy logic, which has also taken on importance in recent years, especially in data mining and financial engineering. The programs given to illustrate the concepts are particularly interesting from the standpoint of coding in C++, as the author uses friend functions and operating overloading in some of them. The reader gets a good overview of fuzzy reasoning and fuzzy rule-based systems. The information was useful & approprate to the topic. I'd rank it as an average quality refence but a very poor text book.<p>The text is poorly written. The code is simple and easy to understand, but not very object oriented. There is not enough explanation of the code. The code is not electronically available.<p>The treatment was very mathematical but lacking in explanation & application examples. There were plenty of deffinitions, but not enough examples.
	Mental Retardation and Developmental Delay: Genetic and Epigenetic Factors (Oxford Monographs on Medical Genetics)
	By: Moyra Smith ISBN: 0195174321 Publisher: Oxford University Press, USA Release Date: 27 October, 2005 Bioscience book rank: 581111
	Essentials of Genetics Student Handbook & Solutions Manual
	By: Harry Nickla, William S. Klug, Michael R. Cummings ISBN: 0131435248 Publisher: Pearson Prentice Hall Release Date: March, 2004 Bioscience book rank: 643245
	Individuals, Families, and the New Era of Genetics: Biopsychosocial Perspectives
	By: Suzanne M. Miller, Susan H. McDaniel, John S. Rolland, Suzanne L. Feetham ISBN: 0393703746 Publisher: W. W. Norton Release Date: 30 May, 2006 Bioscience book rank: 450400
	Genetics (with InfoTrac ): The Continuity of Life
	By: Daniel J. Fairbanks, W. Ralph Andersen ISBN: 0534252729 Publisher: Brooks Cole Release Date: 08 January, 1999 Bioscience book rank: 311608	I am currently taking two biology classes at BYU, both of which use portions of this book, and I have found it to be very straight-forward and useful. Although some may say that I am being preferential since Dr. Fairbanks is a professor here at BYU, I'm not-- this book far outperforms the other texts we have and use, including the much lauded Molecular Cell Biology by Lodish. Dr. Fairbanks's book is well-written, contains clear, concise and easy to understand diagrams and his writing style brings genetics to life. Even a Freshman like I can easily dive into this book and understand the world of genetics. Furthermore, his choice to teach the molecular basis of genetics first is very logical and provides a solid background to later ideas like recombination and epistasis.
	Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
	By: Carlos A. Coello Coello, Gary B. Lamont, David A. Van Veldhuizen ISBN: 0387332545 Publisher: Springer Release Date: 18 September, 2007 Bioscience book rank: 190007