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By: Cindy Campbell-Lashley; MS
ISBN: 0979298539
Publisher: CCL Books
Release Date: 18 March, 2005
Bioscience book rank: 1362357
Genetics is everywhere in the news these days. Increased awareness means increased questions. Many people are asking hard questions of their providers. This book is an excellent resource for general questions as well as specific genetic disorders. We have been using it for years. The 3rd edition is as fabulous as the previous 2. <br />

I am not an educator or health care professional, but I found these visual aids very helpful in furthering my limited understanding of common human genetic topics. I highly recommend it!
By: Seymour Kaufman
ISBN: 1418437468
Publisher: AuthorHouse
Release Date: 13 December, 2004
Bioscience book rank: 1423412
By: Gene S. Fisch
ISBN: 158829045X
Publisher: Humana Press
Release Date: 07 January, 2003
Bioscience book rank: 1396226
By: Dave Unander
ISBN: 0817013172
Publisher: Judson Press
Release Date: December, 2000
Bioscience book rank: 1053190
I read this book about a year ago. I can't believe I'm only getting around to writing a review on it now. The author does a great job of exposing the myth of race. I have been preaching the same thing for years, but when I try to tell people that there is no such thing as race, they don't seem to get it. With this book it's hard not to get it. The author puts all of the facts and arguments together in such a cogent way that it exposes the idea of race as the myth that it is. The idea of race was invented 500 years ago to justify Western Europeans genocide in the colonial world, and there are no phenotypic or genotypic bases for it. If we go back just 600 years we all have several million ancestors. My father was born in Ireland. He was what we call black Irish. My earliest ancestors in Ireland were probably Spanish sailors whose ships sunk with the defeat of the Spanish Armada. So my roots actually go back to Spain, and Spain was occupied for hundreds of years by the Moors (Muslims from Africa). So there is a good chance that my great, great, great, etc. grandfather was also the ancestor of Kunta Kinta. What does that make me? Am I white or Black? How many ancestors do we have to have from a certain region to establish ourselves of one race or the other? <br /> <br />

In Shattering The Myth Of Race: Genetic Realities And Biblical Truths, Dave Unander addresses the concept of race from a Christian perspective while surveying race and economics; slavery and abolition in the United States; the development of genetics as a biological science; DNA comparison studies; and evolutionary genetics as an argument for "racial superiority". Of particular interest is Unander's concluding chapter "A Christian Perspective on Race: Personal Reflections". Very highly recommended reading for personal and group studies, the informative, thoughtful text is enhanced with an epilogue and a list of references.
By: J.F. Samuels, O.J. Bienvenu, A. Pinto, A.J. Fyer
ISBN:
Publisher: Elsevier
Release Date:
Bioscience book rank: 1467665
By: L. E. Ehler, R. Sforza, T. Mateille
ISBN: 085199735X
Publisher: CABI
Release Date: 12 February, 2004
Bioscience book rank: 1405149
By: Donald Pfaff
ISBN: 0674019202
Publisher: Harvard University Press
Release Date: 30 December, 2005
Bioscience book rank: 1066890
By: Robert J. Shprintzen
ISBN: 1565936205
Publisher: Singular
Release Date: 01 October, 1997
Bioscience book rank: 1038285
By: Peter J. Angeline, Kenneth E. Kinnear
ISBN: 0262011581
Publisher: The MIT Press
Release Date: 29 October, 1996
Bioscience book rank: 1297970
By: David Goldberg
ISBN: 1402070985
Publisher: Springer
Release Date: 30 June, 2002
Bioscience book rank: 361492
Genetic Algorithms, GAs, have had a brief flowering of successful application to optimization searches and their limitations have become apparent. One consequence is that a variety of alternative evolutionary computational approaches are being investigated. Another road, much less travelled, is to examine the core mechanisms of the GA concept and try to develop a second generation of improved algorithms. This is difficult work because of the very nature of the core building block theory as first proposed by John Holland. For true inovation, building blocks must be synthesized, evaluated, and combined in sucessive hierarchies, all without external intervention. David Goldberg, a stalwart Holland desciple, has been valiantly trying to extend Holland's main theorem, which applied to infinite populations and hypthetical spaces, to finite populations on real problems. <p>This book is actually a research monograph reporting on the results of this research. The title "The Design of Innovation" sets up a high level of expectation but the subtitle "lessons learned from and for competent GAs" is probably right. The book offers some useful insights into the internal workings of GAs and their implication for understanding true innovation. However, despite the introductory claim of an engineering approach, the book never gets around to actually showing practitioners how to apply the lessons, nor does it give direct evidence that they work as claimed (although references to recent papers which presumably demonstrate success are given). <p>It is perhaps ironic that the goal for GAs has been downgraded from "universal" (as first claimed by Holland) to "competent".<br>Goldberg's concentrates on GAs to the exclusion of other approaches that may be equally competent or even better. A further irony is the stunning admission that "for years GA practitioners have understood that commercial applications often require" combinations of GAs and other local search methods to obtain high-quality solutions in reasonable time. But if this is so, then maybe GAs aren't the best place to start in the first place. <p>Goldberg's ideas about the upcoming golden age of computational innovation in the last chapter are provocative. But the implication that we must await GA improvements for this to happen are a little off-putting.<p>In sum, this book is a well-written research monograph intended to open up further research into the heart and soul of GAs. It should be read by researchers in AI, machine learning, and related fields. However, it will not provide the immediate answers to practitioners who are now running into the limitations of GAs (and other evolutionary or general search techniques).
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