Likelihood, Bayesian and MCMC Methods in Quantitative Genetics

Book Description

Over the last ten years the introduction of computer intensive statistical methods has opened new horizons concerning the probability models that can be fitted to genetic data, the scale of the problems that can be tackled and the nature of the questions that can be posed. In particular, the application of Bayesian and likelihood methods to statistical genetics has been facilitated enormously by these methods. Techniques generally referred to as Markov chain Monte Carlo (MCMC) have played a major role in this process, stimulating synergies among scientists in different fields, such as mathematicians, probabilists, statisticians, computer scientists and statistical geneticists. Specifically, the MCMC "revolution" has made a deep impact in quantitative genetics. This can be seen, for example, in the vast number of papers dealing with complex hierarchical models and models for detection of genes affecting quantitative or meristic traits in plants, animals and humans that have been published recently. This book, suitable for numerate biologists and for applied statisticians, provides the foundations of likelihood, Bayesian and MCMC methods in the context of genetic analysis of quantitative traits. Most students in biology and agriculture lack the formal background needed to learn these modern biometrical techniques. Although a number of excellent texts in these areas have become available in recent years, the basic ideas and tools are typically described in a technically demanding style, and have been written by and addressed to professional statisticians. For this reason, considerable more detail is offered than what may be warranted for a more mathematically apt audience. The book is divided into four parts. Part I gives a review of probability and distribution theory. Parts II and III present methods of inference and MCMC methods. Part IV discusses several models that can be applied in quantitative genetics, primarily from a Bayesian perspective. An effort has been made to relate biological to statistical parameters throughout, and examples are used profusely to motivate the developments. Daniel Sorensen is a Research Professor in Statistical Genetics, at the Department of Animal Breeding and Genetics in the Danish Institute of Agricultural Sciences. Daniel Gianola is Professor in the Animal Sciences, Biostatistics and Medical Informatics, and Dairy Science Departments of the University of Wisconsin-Madison. Gianola and Sorensen pioneered the introduction of Bayesian and MCMC methods in animal breeding. The authors have published and lectured extensively in applications of statistics to quantitative genetics.

Customer Reviews:

Highly recommended!.......2004-08-27

This book contains a wealth of well presented and organized information, which is not easy to find in texts of similar level. I especially enjoyed the style and clarity of presentation. Outstanding!

Average customer rating:

Statistics in Human Genetics - Sham P

Statistics in Human Genetics
Pak Sham
Manufacturer: A Hodder Arnold Publication
ProductGroup: Book
Binding: Paperback

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ASIN: 0340662417

Book Description

This is one of the first introductions to the sophisticated statistical methods that play a key role in research on human genetics. Topics include the estimation of allele frequencies, the testing for Hardy-Weinberg equilibrium, classical and complex segregation analysis, linkage analysis for Mendelian and complex diseases and quantitative traits, the detection of allelic associations, the estimation of heritability for multifactorial traits and path analysis.

Customer Reviews:

Statistics in Human Genetics - Sham P.......2000-05-16

This is an excellent book covering all major areas of genetic epidemiology. Ideal for postrgraduate studies it is well structured and highly detailed. The only criticism would be is that the sections on association studies and segregation analysis are not overly strong, but then this reflects the states of those fields in comparison to linkage analysis

Average customer rating:

clear reading for beginners
Molecular Evolution and Phylogenetics by Masatoshi Nei, Sudhir Kumar
A valuable addition
OK, until something better comes along
Top in its Field

Molecular Evolution and Phylogenetics
Masatoshi Nei , and Sudhir Kumar
Manufacturer: Oxford University Press, USA
ProductGroup: Book
Binding: Paperback

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ASIN: 0195135857

Book Description

During the last ten years, remarkable progress has occurred in the study of molecular evolution. Among the most important factors that are responsible for this progress are the development of new statistical methods and advances in computational technology. In particular, phylogenetic analysis of DNA or protein sequences has become a powerful tool for studying molecular evolution. Along with this developing technology, the application of the new statistical and computational methods has become more complicated and there is no comprehensive volume that treats these methods in depth. Molecular Evolution and Phylogenetics fills this gap and present various statistical methods that are easily accessible to general biologists as well as biochemists, bioinformatists and graduate students. The text covers measurement of sequence divergence, construction of phylogenetic trees, statistical tests for detection of positive Darwinian selection, inference of ancestral amino acid sequences, construction of linearized trees, and analysis of allele frequency data. Emphasis is given to practical methods of data analysis, and methods can be learned by working through numerical examples using the computer program MEGA2 that is provided.

Customer Reviews:

clear reading for beginners.......2007-10-05

this book is realy straightforward, very well-written and really explains the oncept in a very clear way. Excellent choice for non-specialists.

Molecular Evolution and Phylogenetics by Masatoshi Nei, Sudhir Kumar.......2007-03-09

Overall it is a good and complete book on Molecular Evolution, and basic DNA analysis techniques.

A valuable addition.......2003-11-26

I don't look for any one book to answer all my questions. This one carries its weight, though, and maybe a bit more.

The first section gives the clearest and most detailed description of nucleotide sequence comparisons I've seen. I'm no biologist, but it really got me thinking about some new ways to talk about substitution matrices.

The bulk of the book covers what I hoped for originally: phylogenetic trees. The authors choose an unusual approach - it doesn't quite meet the authors' initial promise of math-minimization, but doesn't climb too far up the ivory tower, either. I find it a very practical, usable level of presentation. I'd be nervous about going beyond their formulas, since the math for real understanding isn't all there. Still, the phylogeny discussion covers a lot of material, and covers it well enough for me to write programs about most of it.

The final section addresses population genetics. I have nothing against population genetics, it just never seemed to point where I'm headed. Nei and Kumar corrected my mis-impression. Population gentics is the background model, the null hypothesis, behind the functions that score population differences. It really shows what happens when the tree of life branches out.

The book has some minor weaknesses. It emphasizes nucleotide sequences at the expense of peptides; I can't fault an author for writing what they want as opposed to what I want. On page one, the authors decline an intensely mathematical approach. By page 25, they're up to Poisson and gamma distances. The typography make the section breaks into a "Where's Waldo" experience. Nei's favorite author, based on citations, is Nei. Well, false modesty is no virtue. This book seems authoritative and Nei seems to be an authority, maybe not just in Nei's opinion.

This book really has given me a lot more to work with than most. Education isn't cheap these days, and this book is very educational. I just hope no one asks me to lend it any time soon.

OK, until something better comes along.......2003-02-20

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".

Top in its Field.......2000-09-21

This book is an excellent text and reference for both graduate students and faculty. It covers several topics in molecular evolution and phylogenetic analysis, as the title suggests. It stands as a unique contribution because the authors explain the mathematical and conceptual framework of a given topic in molecular evolution or phylogenetic analysis and give subsequent examples to show how various analytical methods can be applied to the study of that topic. In that context, the explanation of concepts was exceptionally clear, which made it easy to understand potentially difficult subject matter. This book is highly recommended to those wishing to study the analysis of genes and proteins in an evolutionary framework.

Ageless Quest: One Scientist's Search for Genes That Prolong Youth

Average customer rating:

review of seller
--
Great behind the scenes view of scientific research

Ageless Quest: One Scientist's Search for Genes That Prolong Youth
Lenny Guarente
Manufacturer: Cold Spring Harbor Laboratory Press
ProductGroup: Book
Binding: Hardcover

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Accessories:

ASIN: 0879696524

Book Description

Ageless Quest is a personal, sometimes controversial, account of the pursuit of a genetic "cure" for aging by an expert in the field.

The author is the Novartis Professor of Biology at the Massachusetts Institute of Technology.

Aging has always been regarded as a highly complex process with many degenerative changes leading to the cessation of life. But recent research has identified a relatively simple mechanism that governs the pace of aging.

Lenny Guarente's Ageless Quest is a scientific detective story for the baby boom generation. It offers an insider's view of an area of potentially astonishing high reward-and equally high risk.

Customer Reviews:

review of seller.......2007-01-10

Thank you for your very prompt shipment of this book as we specified expediated shipping and this worked out!

--.......2004-01-13

I picked up this book because of the cover. If you care about the scientific story, read it in the review literature. If you want a good read, look elsewhere.

Great behind the scenes view of scientific research.......2002-12-06

As a non-scientist with an interest on what the future may hold for us, I found Ageless Quest to be exceptionally informative, easy to understand, and thought provoking. I had always wondered what went on in those biology research labs, and was grateful to have the "behind the scenes" peek that this book provided. Extremely interesting and enjoyable reading; recommended for all.

Average customer rating:

Another great book from Avise

CAPTIVATING LIFE
AVISE J
Manufacturer: Smithsonian
ProductGroup: Book
Binding: Hardcover

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Writing Papers in the Biological Sciences

ASIN: 1560989572

Book Description

Writing in the tradition of E. O. Wilson and Margaret D. Lowman, Avise recounts his scientific adventures with many animals in the wild and reflects more widely on the artistry of scientific discovery and the allure of the natural world. His story conveys as much about the making of a scientist as it does about the inner workings of science and nature.

Customer Reviews:

Another great book from Avise.......2004-01-18

I read this book after citing Avise's work in my thesis and in papers. I have enjoyed reading other scientist's autobiographies, such as E.O. Wilson's "Naturalist", Geerat Vermeij's "Priveleged Hands", and Eric Pianka's "The Lizard Man Speaks". Avise's autobiography is in the same vein; he recounts his childhood and his entry into academic life. I must say it was reassuring to read that he had difficulty with funding as a new professor! He also describes research he has performed, from coral to birds to turtles, and tells stories on graduate students and colleagues.
Like many scientists who have achieved so much so early in their careers, Avise has a healthy ego. (Obviously! He wrote an autobiography at what age?) However, his little bouts of bragging in the book do not make it unreadable. After I was through reading this book, I gave it to my mother. I think it is written clearly enough for a non-scientist to enjoy it and to understand the basics of phylogeography.

Handbook of Statistical Genetics (2 Volume Set)

Average customer rating:

Good overview of topics on quantitative aspects of genetics

Handbook of Statistical Genetics (2 Volume Set)

Manufacturer: Wiley
ProductGroup: Book
Binding: Hardcover

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Statistical Methods in Genetic Epidemiology

ASIN: 0470848294

Book Description

From the Reviews of the First Edition:
"This magnificent book attempts to catalogue and introduce all aspects of modern statistical genetics...I can thoroughly recommend it."
Short Book Reviews of ISI
"...extremely well written and referenced work, which must come highly recommended..."
Statistical Methods in Medical Research

Provides comprehensive coverage of a thriving area of research
Features nine newly commissioned chapters
All existing chapters have been fully updated with new advances in the field and new references
Now includes a glossary of terms, and a list of acronyms and abbreviations.
Features extensive cross-referencing between chapters.
Each chapter is written by a leading international authority from the field.
Complemented by examples, case studies, and references to useful resources on the web.

Customer Reviews:

Good overview of topics on quantitative aspects of genetics.......2001-05-10

The book is a collection of chapters written by experts in their respective fields. It contains both basic topics of genetics like chromosome maps and protein analysis as well as recent developments in evolutionary genetics like coalescence and phylogenetics. The topics on genetic epidemiology like linkage and association cover the main ideas, but the mathematical subtlities are not adequately explained in some of the cases. Since the target audience of this book are statistical geneticists, it would have been more beneficial if more quantitative insights were given. The chapters by Bruce Weir, Nicholas Schork and Ranajit Chakraborty provide some interesting practical applications of statistical genetics. With lots of controversies going around, it is apt to include the chapter on the ethical issues regarding the use of statistics in genetics.

The Monk in the Garden: The Lost and Found Genius of Gregor Mendel, the Father of Genetics

Average customer rating:

Propagates a pernicious misconception
an odd little book
Beneficial
Grossly Inaccurate History--Not to be trusted
A thoroughly enjoyable read

The Monk in the Garden: The Lost and Found Genius of Gregor Mendel, the Father of Genetics
Robin Marantz Henig
Manufacturer: Mariner Books
ProductGroup: Book
Binding: Paperback

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ASIN: 0618127410

Amazon.com

The Moravian monk and naturalist Gregor Mendel (1822-1884) labored quietly over the years in his abbey's garden, becoming known locally as a reliable meteorologist with an unusually green thumb. He was much more than that, of course, but his transforming experiments in what a later acolyte would call "genetics" were less well known. When he published the results of his many attempts to discover the mechanisms by which traits are passed from one generation to the next--in Mendel's case, in sweet peas--it was in the proceedings of a local scientific study group, and it would take nearly two decades before researchers in more august institutions would in turn discover Mendel's work and apply it to their own revolutionizing biology in the process.

Mendel's life was full of disappointments: he failed his qualifying examinations to teach high school several times, and he had trouble getting the scientific establishment of his day to take him seriously. In her lucid, often moving life of the great (and to all purposes self-taught) scientist, Robin Marantz Henig gives readers a view of the deeply religious man himself and of his work not only in the context of his time but also in light of recent developments in the constantly changing field of genetics. Taking issue with historians of science who have sought to discount Mendel's contributions to the field, she makes a well-defended claim that the monk in his small garden should be honored as a genius: "a man with a vision and the dedication to carry it to its brilliant, radical conclusion." Her book is a fitting, and very welcome, memorial. --Gregory McNamee

Book Description

In THE MONK IN THE GARDEN, award-winning author Robin Marantz Henig vividly evokes a little-known chapter in science, taking us back to the birth of genetics, a field that continues to challenge the way we think about life itself. Shrouded in mystery, Gregor Mendel's quiet life and discoveries make for fascinating reading. Among his pea plants Henig finds a tale filled with intrigue, jealousy, and a healthy dose of bad timing. She "has done a remarkable job of fleshing out the myth with what few facts there are" (Washington Post Book World) and has delivered Mendel's story with grace and glittering prose. THE MONK IN THE GARDEN is both a "classic tale of redemption" (New York Times Book Review) and a science book of the highest literary order.

Customer Reviews:

Propagates a pernicious misconception.......2006-11-29

Henig admittedly takes creative license to fill in some historical gaps, but she goes too far in propagating the misconception that Mendel sent a copy of his paper to Charles Darwin and that Darwin never read it. This urban legend (also brought up by other authors, such as Philip Kitcher) has made its way into newspaper articles and even textbooks. Catalogs of Darwins library in the early 1900's and later made no mention of Mendel's paper. Instead, a secondary source by Focke that mentioned Mendel was in Darwin's library, with the relevant pages uncut. See Andrew Sclater's 2003 article in the Georgia Journal of Science.

an odd little book.......2006-05-23

The Monk In The Garden by, Robin Marantz Henig, is a good book surrounded by a more boring, speculative one. At the core of this "novel," of course, was the explanation of the life and times of Gregor Mendel that helped procure his work on genetics. However, concealing this was much fluff, and unnecessary banter from Henig. The story of the monk growing his peas is a familiar one, to any person having passed a high school biology class, yet the purpose of this novel was to delve further into the unknown to see a side that we have never previously seen. While at times, Henig creates lighthearted descriptions of his rotund body, or widening face, for the most part she generalizes and presupposes that Mendel spent his time looking at objects out windows. For having lived so very long ago, it is amazing someone has been able to so accurately describe their daily life, and without ever meeting them as well? Now if she could only do the same for the many other illusive historical figures.

After reading some reviews, I too picked up on a certain religious bias held by Henig. She seemingly had two agendas in writing this book, both uncovering Mendel's life and work, and discrediting Christianity at any point possible.

While trying to be entertaining, Henig still uses excessively large vocabulary at points, and seems to be mixed up, and frazzled when it comes to her explaining important concepts. Still eagerly trying to explain genetics, Mendel, and how Christianity is wrong, she seems to forget that not everyone reading this book has a PhD in molecular biology. Henig seems to have failed as both a geneticist, and a novelist. Harsh, yet someone publishing a nonfiction book should be 110% sure everything is both correct, and at least factual based on primary resources, not made up chitchat. Plus its just plain boring.

Beneficial.......2005-10-13

I have spent 10 years teaching high school biology, and as such a person, I have a reverence for poor Mendel strugling in his garden.

This book gave me insights into his work, and the work of those who followed, and thus gave me new insight into how to communicate the humanity of these surprised giants to my students; possible giants of the future.

Grossly Inaccurate History--Not to be trusted.......2005-07-29

I'm surprised so many rated this book so highly. As I was reading, I kept asking myself why Henig included so many petty descriptions of Mendel, especially regarding his size: "widening face", "despite his girth", "rotund fellow like Mendel", "his fellow brethren might have been surprised to hear Mendel admit that there was something more important to him than eating", and when Henig calls Mendel "thick-fingered" I looked at the book's cover, and the hand-surgeon in me noticed--normal-sized fingers.

So why does Henig take so many cheap shots, in what's supposed to be a scholarly biography? I've seen plenty of pictures of Mendel, and his size is not conspicuous. Why the constant comments? Why the extensive discussions about the food in the monastery kitchen? And why go on and on about his health difficulties, far in excess of what would be required in a biography? Is there any reason for her almost snide remarks?

But then she did something that made her motives, if not agenda, obvious. On Page 41 she writes a single paragraph that can only be described as outright anti-Catholic bigotry:

" . . . Galileo Galilei, an Italian mathematics professor and devout Catholic (FALSE), faced excommunication (FALSE) for defending those same ideas (i.e., Copernicanism). (FALSE) Official doctrine had changed by then (FALSE) . . . but Galileo . . . refused to renounce his radical ideas (FALSE) . . .

Clearly, Henig is no historian:

1. Galileo was NOT a devout Catholic--he had a mistress who bore him 3 illegitimate children
2. Galileo did not face excommunication, and if Henig had done her homework, she would have known that excommunication was not an option given his crime BECAUSE-->
3. Galileo was NOT brought before the Inquisition for advocating Copernicanism. The Pope had told him NUMEROUS times that the Church did not think Copernicanism was heretical, and that Copernicanism was NOT the issue. The issue was Galileo's insistence that the Church change its interpretation of Scripture to conform to Galileo's REINTERPRETATIONS (at least one of which was wrong), which he had based on Copernicanism. The issue was Galileo's (erroneous) foray into Scriptural re-interpretation, not his astronomy.
4. The Church never took an "official" position on Copernicanism, so it was never an issue of "doctrine", and if Henig had read any reputable historian (Catholic/Protestant/Secular/whatever) she would have known that. (And, no John Paul II did NOT apologize for it in 1992).
5. Of course Galileo renounced his radical ideas. Every junior high school student in America knows he ABJURED--that's why he got house arrest--in his own villa outside Florence. (And no, it was not because he was afraid he'd be tortured--Inquisition rules forbid torture in someone Galileo's age, and he knew that).

One last one: Henig writes: "But natural scientists, if they are intellectually honest, often find themselves taking heretical positions on matters of creation and procreation, positions that challenge the very underpinnings of the Catholic Church." What dishonest nonsense. Here's a (very) brief list of internationally known historians who disagree with Henig: Lindberg, Numbers, Ferngren, Hedley Brooke, Shea, Rowland, Artigas (none of whom, to my knowledge, are Catholics themselves).

I agree with the previous reviewer(s) who mentioned Henig's obvious lack of accuracy when it comes to Christianity, but these errors are so glaring that either she is the most ignorant historian I've read in years, or she's an outright anti-Catholic/Christian bigot.

In either case, these biases/errors/inaccuracies make the book a waste of time. Not that it's not entertaining in parts, but if she can put so many errors/distortions into a single paragraph, the rest of the book is not to be trusted, on any level.

A thoroughly enjoyable read.......2004-12-31

This book is a wonderful historical account of how
Gregor Mendel, the father of modern genetics, came
about to describe the units of heredity.

The story is not only of one monk's personal struggle
to be recognized as a notable and respected scientist
and teacher, but also one of other scientists'
motivations (selfish and unselfish) for scientific
excellence and recognition.

Mendel had to overcome many social and political
challenges along the way to his discovery. Even after
his death, others fought difficult battles for him in
order for Mendel's thoughts to be accepted as the truth,
and to have Mendel himself recognized for his awesome
achievement. The man was truly a genius.

The author does an incredible job compiling the
information available on Mendel, as well as building a
timeline and social environment that allows the reader
to feel as if he/she were truly in the time of Mendel.
This was a thoroughly enjoyable read.

Now the warts...

1. I was a bit disappointed in not getting a more clear
discussion of the concepts Mendel was working with.
The fact that Mendel started out with a clear plan
of attack and then systematically developed a model
that later led to his theory well after he made his
observations was simply posed as a question of whether
he had foresight to do the experiments. It really doesn't
matter, but the answer is obviously yes. He knew what he
was doing. His scientific inquiry and application of
mathematical concepts to the study of heredity was
revolutionary, yet overlooked. He was not ahead of his
time, but rather his peers (and many scientists today)
were (and are) not thinking in Mendel's mathematical terms.
Others were preoccupied with the physical world, but
Mendel was only concerned with the mathematical.
Try to describe the law of gravity to someone and you
will get a nod of understanding as you drop an apple
to the ground. But, try to describe the same using a
mathematical equation...and you will get a blank look,
I guarantee it...just try it for yourself.

2. It seems as if the writer was working with a pencil
(or word processor) in one hand and a thesaurus in the
other. There are so many obscure vocabulary words that
it disrupts the flow of thought. This is just great if
you would like to use the book for teaching high school
students, which may actually be the intent - note the
reference to the author's teenage daughter - but is
very distracting to most other people. In addition, the
flow of thought is interrupted by many long parenthetical
discussions. Sometimes, you just lose sight of the topic.
If you put the book down in mid-chapter, be prepared to
re-read the whole chapter again. I ended up skimming the
entire book several times after reading through the first
time, so I was sure I was getting the whole story.

If you want to use the book as a study guide for the
vocabulary portion of the S.A.T., scrabble championship,
or for jeopardy, you may want to look up the definitions
of words from this short list beforehand:

acerbic
acumen
apogee
apostatic
banal
cacophony
chafed
churlish
comported
dioecious
ecclesiastical
erstwhile
exegesis
heretical
ignominy
imperious
macabre
marshalled
misanthrope
paean
parson
pedagogy
polemic
prescient
propitious
quixotic
rubric
slake
sojourn
stolidity
talisman
tweedy
vituperative
waggish

3. There are some obvious mistakes (typographical or
otherwise) that a geneticist would see immediately, but
may be confusing for someone trying to learn genetics
and reading this book. For example, on page 90, there is
a discussion of dominance that had me scratching my head,
and I have Ph.D. in molecular genetics! Also, on page
240, line 8, replace the word "phenotype" with "genotype"
and you will understand the authors point.

4. Skip the epilogue. Why pontificate about what might be
if Mendel had not done his gardening? Would we be better off
without atomic warheads? What about antibiotics? Hmmm....
Wait...the book is about something entirely different.

Geographical Genetics (MPB-38) (Monographs in Population Biology)

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Geographical Genetics (MPB-38) (Monographs in Population Biology)
Bryan K. Epperson
Manufacturer: Princeton University Press
ProductGroup: Book
Binding: Paperback

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ASIN: 0691086699

Book Description

Population genetics has made great strides in applying statistical analysis and mathematical modeling to understand how genes mutate and spread through populations over time. But real populations also live in space. Streams, mountains, and other geographic features often divide populations, limit migration, or otherwise influence gene flow. This book rigorously examines the processes that determine geographic patterns of genetic variation, providing a comprehensive guide to their study and interpretation.

Geographical Genetics has a unique focus on the mathematical relationships of spatial statistical measures of patterns to stochastic processes. It also develops the probability and distribution theory of various spatial statistics for analysis of population genetic data, detailing exact methods for using various spatial features to make precise inferences about migration, natural selection, and other dynamic forces. The book also reviews the experimental literature on the types of spatial patterns of genetic variation found within and among populations. And it makes an unprecedented strong connection between observed measures of spatial patterns and those predicted theoretically. Along the way, it introduces readers to the mathematics of spatial statistics, applications to specific population genetic systems, and the relationship between the mathematics of space-time processes and the formal theory of geographical genetics.

Written by a leading authority, this is the first comprehensive treatment of geographical genetics. It is a much-needed guide to the theory, techniques, and applications of a field that will play an increasingly important role in population biology and ecology.

Exploding the Gene Myth: How Genetic Information Is Produced and Manipulated by Scientists, Physicians, Employers, Insurance Companies, Educators, and Law Enforcers

Average customer rating:

Earth-Shaking Paradigm Shift from a Very Prominent Biologist
Rhetoric Against a Needed Science
A brilliantly written book
The work of a good scientist, an abysmal social commentator
The author breaks ranks to reveal the truth about genetics.

Exploding the Gene Myth: How Genetic Information Is Produced and Manipulated by Scientists, Physicians, Employers, Insurance Companies, Educators, and Law Enforcers
Ruth Hubbard , and Elijah Wald
Manufacturer: Beacon Press
ProductGroup: Book
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ASIN: 0807004316

Book Description

How Genetic Information Is Produced and Manipulated by Scientists, Physicians, Employers, Insurance Companies, Educators, and Law Enforcers With a new Preface "With their rich array of citations and examples . . . [Hubbard and Wald] show how the marriage of science and business . . . has created that most treacherous of American progeny: commerce masquerading as human liberation." -Daniel Callahan, The New York Times Book Review

Customer Reviews:

Earth-Shaking Paradigm Shift from a Very Prominent Biologist.......2004-10-28

Ruth Hubbard is a professor emerita of biology at Harvard and a member of the Council for Responsible Genetics, a prominent national bioethics board. In this book (co-written with her son-in-law, Elijah Wald), she takes everything you think you know about genes, genetic health care screening, DNA fingerprinting, the Human Genome Project, and the search for a gay gene and other behavior-related genes, and blows your mind by explaining, point by point, exactly how unreliable, meaningless, and discriminatory each of these much-lauded technologies is. After reading this book, you'll never read a newspaper article about the latest genetic study the same way again. Don't miss it.

Rhetoric Against a Needed Science.......2001-11-18

Ruth Hubbard uses the rhetoric of exaggeration to try to convince us to abandon genetic research. But if genes didn't matter then monkeys could talk and if environment didn't matter then we wouldn't have schools. Obviously they BOTH matter.

Let us use the objective methods of science to document the specifics of what is genetically determined and what is environmentally determined.

Any serious AIDS researcher knows that without genetic research we have no chance of defeating AIDS. Obviously we need to study genetics to maintain progress against disease.

A brilliantly written book.......1999-10-28

Dr. Hubbard gives her readers much to think about, and she backs up everything she's written. She explains how the popularly-held reductionist view of genetics does not tell the whole story. Her book explains how the public often only hears one side of the story when it comes to the potential of the latest genetic technologies.

The work of a good scientist, an abysmal social commentator.......1999-08-29

Hubbard does deserve credit for throwing some skepticism on "the next big thing" in science, genetic technology. Unfortunately, she combines her skeptical analysis with her hopelessly egalitarian political views, obscuring any positive contributions this book could have. Hubbard goes through every expected cliche - Nazi imagery (social pundits never tire of this), playing the "race card, and discouraging scientific progress as "unneccessary". Read this book only if you wish to glimpse the future of awful politically-correct rhetoric.

The author breaks ranks to reveal the truth about genetics........1998-10-02

A 5-star book. If there weren't so much hype about gene therapy there would be no need for this book. But bad science and misinformation coming from those with commercial or political interests has given the American public the idea that gene therapy has possibilities. To date, gene therapy has not cured one disease. Ruth Hubbard finally breaks ranks to reveal the truth about genetics.

Average customer rating:

Misleading title!
Great all-around review of probability
Disappointing overview
Pretty good overview
guide into the right direction

Statistical Methods in Bioinformatics
Warren J. Ewens , and Gregory R. Grant
Manufacturer: Springer
ProductGroup: Book
Binding: Hardcover

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Accessories:

ASIN: 0387952292

Book Description

Advances in computers and biotechnology have had an immense impact on the biomedical fields, with broad consequences for humanity. Correspondingly, new areas of probability and statistics are being developed specifically to meet the needs of this area. There is now a necessity for a text that introduces probability and statistics in the bioinformatics context. This book also describes some of the main statistical applications in the field, including BLAST, gene finding, and evolutionary inference, much of which has not yet been summarized in an introductory textbook format. This book grew out of a need to teach bioinformatics to graduate students at the University of Pennsylvania. At the same time however, it is organized to appeal to a wider audience. In particular it should appeal to any biologist or computer scientist who wants to know more about the statistical methods of the field, as well as to a trained statistician who wishes to become involved in bioinformatics. The earlier chapters introduce the concepts of probability and statistics at an elementary level, and will be accessible to students who have only had introductory calculus and linear algebra. Later chapters are immediately accessible to the trained statistician. Only a basic understanding of biological concepts is assumed, and all concepts are explained when used or can be understood from the context. Several chapters contain material independent of that in other chapters, so that the reader interested in certain areas can proceed directly to those areas.

Warren Ewens is Professor of Biology at the University of Pennsylvania. He is the author of two books, Population Genetics and Mathematical Population Genetics, and has served on the editorial boards of Theoretical Population Biology, GENETICS, Proceeding of the Royal Society B and SIAM Journal in Mathematical Biology. He was recently awarded the Gold Medal of the Australian Statistical Society and elected as Fellow of the Royal Society. His research interests are in evolutionary population genetics, linkage analysis for human diseases, and bioinformatics.

Gregory Grant is a bioinformatics researcher at the University of Pennsylvania in the Computational Biology and Informatics Laboratory (CBIL), where he has been since 1998. In 1995 he received a Ph.D. in Mathematics from the University of Maryland and in 1999 a Masters in Computer Science from the University of Pennsylvania. His research interests are in bioinformatics in general and in particular in the statistical analysis of gene expression data and significance testing methods for IBD-mapping.

Customer Reviews:

Misleading title!.......2004-12-12

A better title for this book would be 'How Blast works' because this book is centered around this topic. If you expect a general overview of statistical methods used in bioinformtics you should buy another book (e.g. Hastie, Baldi, Pevzner, Duda, Eddy which provide more general methods). If you want to know in mathematical detail how blast works, this is your book. I think the level is advanced and one needs some mathematical background to appreciate it (certainly not to recommend for biologists).

I don't think it is a really bad book but I think it gives a wrong impression of (statistical) methods in bioinformatics. Another reviewer wrote ...This is one of the books I have been waiting for. For a population geneticist who wants to learn bioinformatics, most texts are unacceptable: They present heuristic methods in a cookbook fashion, with little reference to what is going on biologically as well as mathematically....
This is exactly the problem with this book!! Bioinformatics is more machine learning than statistics and more heuristic then exact.

Great all-around review of probability .......2004-08-17

The book's title says 'Statistical Methods', but all of statistics is derived from probability theory. That's really where Ewens and Grant start, with the best high-density review of probability I know.

The first two chapters cover probabilities of one and many variables, respectively. This includes several topics that other authors equently skip, including conditional and marginal probabilities, probability- and moment-generating functions, a little about entropy, distributions of sums, and extreme value statistics. All that takes about 100 pages. Two later chapters cover statistical inference (parameter estimation, hypothesis testing, and Bayesian techniques), two more cover stochastic processes including Markov models, a short chapter includes hidden Markov models and their training, and another chapter covers sampling techniques: bootstraps, permutation tests and such.

If the book contained only that material, it would still be a valuable review and summary of basic probability. It's way too dense to be a beginner's text. That's OK, those chapters were really intended as a review and as a statement of the terms and notation used in the book's real objectives: models of biological systems.

The chapters on biological applications are interspersed with chapters on basics, so that each application is presented as soon as its elements are covered. Those chapters describe statistical properties of a single DNA or protein string, relationships between two strings, BLAST and its scoring models, mutation modeling, and construction of phylogenetic trees. Coverage of each topic is brief but very dense. A surprising amount of information is packed into each brief chapter, and it's surprisingly readable. Still, these are big topics. Ewens and Grant don't and don't try to present any topic to its full depth. Instead, they give enough discussion that a determined reader can learn the basics, and can understand more advanced discussions of specific topics.

The book does require a determined reader with some background in probability - this shouldn't be anyone's first book, unless you have a very skilled teacher. The prepared and careful reader will be very well rewarded, however. Despite the book's title about statistics and bioinformatics, this is a reference you may use for probability models in any field. It's certainly one that I keep coming back to.

//wiredweird

Disappointing overview.......2003-11-12

This book is a tremendous disappointment, given other Amazon reviews and the impressive Table of Contents. I picked several topics about which I know something: Likelihoods, P-values, bootstraps. I would have had NO idea about either of these subjects based on the poor delivery in this book. Topics are not well introduced, there are virtually no examples, and the introduction/discussion of most topics is wordy and not informative.

A topic such as the two-sample t-statistic is scattered throughout the book, with the main part not even cited in the index!

Unfortunately there are not a lot of books in the field of Statistics in Bioinformatics. However, I would recommend "The Elements of Statistical Learning" (Hastie et al.) for classifiers etc (Duda and Hart's classic is also good). I would recommend "Biostatistical Analysis" by Zar for a general coverage, and Terry Speed's "stat Labs: Mathematical Statistics ..." which is not comprehensive but has good lab examples with associated statistical analysis.

Pretty good overview.......2002-09-19

This book is a timely introduction to the mathematical statistics used in computational biology and bioinformatics. The authors have done a superb job in the overview of a subject that students of biology and bioinformatics can rely on for study and for reference. The mathematics is done at an advanced undergraduate level, but the authors are pragmatic in their approach, and interlace the discussion with biological applications immediately after the appropriate mathematical background has been developed. It thus seems appropriate to discuss the quality of the presentation with these applications in mind.

Chapter one begins, appropriately, with an introduction to probability theory, with a consideration of discrete probability distributions of one variable beginning the chapter. The Bernoulli, binomial, uniform, geometric, generalized geometric, and Poisson distributions are discussed. The authors point out the use of geometric-like distributions in the BLAST application. The also caution the reader as to the difference between the mean and the average of a random variable. They then move on to consider continuous distributions, discussing briefly the uniform, Normal, exponential, gamma, and beta distributions. Moment-generating functions are also introduced, and they prove a "convexity" theorem for these functions that is important in the BLAST application. The authors also introduce the relative entropy and generalized support statistics, the later also being used in BLAST.

The next chapter is an overview of probability theory in many random variables. The results in chapter one are discussed in this context, and the authors give an interesting application to the sequencing of EST libraries. The authors also point out that the variance of the maximum of a collection random variables is finite as the number of variables increases, a fact that is used quite often in bioinformatics. Transformations of random variables are also discussed, with the goal of showing how these can be used to find the density function of a single random variable, this also being important in BLAST.

The most important subject of the book begins in chapter 3, wherein the authors introduce statistical inference. They begin with a very brief discussion of the differences between the frequentist and Bayesian approaches to statistical inference and then move on to classical hypothesis testing and nonparametric tests. This chapter is of great value to those readers, for example biologists/would-be bioinformaticists who are approaching statistics for the first time.

Chapter 4 introduces concepts that are of upmost importance in probabilistic computational biology, namely Markov chains. The discussion in this chapter sets up the strategies used in the next chapter on analyzing a single DNA sequence and a latter chapter on hidden Markov models. Shotgun sequencing is discussed as a tool to determine the an actual DNA sequence, and the authors discuss the probabilistic issues that arise in the reconstruction of long DNA sequences from shorter sequences. Missing in this chapter is a mathematical analysis of the advantages/disadvantages between shotgun and whole genome sequencing strategies.

Chapter 6 then generalizes the analysis of chapter 5 to multiple DNA and protein sequences. It is here that one begins to talk about alignments between sequences, which bring about some very subtle mathematical problems in computational biology. The computational complexity of the (global) alignment problem entails the use of softer techniques, such as dynamic programming, which is discussed in this chapter. The (local) alignment problem is also discussed in some detail, using the linear gap model. The alignment problem and the issues with scoring for protein sequences are also discussed in detail. The reader first encounters the famous PAM and BLOSUM matrices in this chapter. The authors do not discuss any connections with the protein folding problem, unfortunately.

The next chapter introduces the basic probability theory behind the BLAST algorithm, namely random walks. They do so with emphasis on moment generating functions, which might be a little abstract for the biologist reader.

The authors return to tatistical estimation and hypothesis testing in chapter 8, with maximum liklihood and fixed sample size tests discussed in some detail. Again connecting with the BLAST algorithm, the sequential probability ratio test is treated.

The authors finally get down to the BLAST algorithm in chapter 9, using an older version of the software (1.4). The connection of the algorithm with random walks and how to assign scores is immediately apparent, as is the ability of BLAST to do database queries against a chosen sequence. The algorithm is compared with the sequential analysis discussed in the last chapter.

The authors return to Markov chains in chapter 10, and give some numerical examples. In addition, they treat the important topic of Markov chain Monte Carlo via the Hastings-Metropolis algorithm, Gibbs sampling, and simulated annealing. An application of simulated annealing to the double digest problem is described. The authors also spend a litte time discussing continuous-time Markov chains.

Hidden Markov models are finally discussed in chapter 11. These have been the most effective tools in sequence analysis and the authors give a nice overview of their construction and properties in this chapter. The Pfam package is discussed as a software implementation of HMMs for determining protein domains. Unfortunately, they do not discuss the excellent package HMMER for implementing HMMs in sequence analysis.

Chapter 12 discusses computationally intensive methods in classical inference. One of these methods, the bootstrap procedure, which is used for large sample sizes, is described. Used to estimate confidence intervals in situations where there is not enough information to employ classical methods, the authors detail a method using quantiles to estimate the confidence interval for the standard deviation of the expression intensity of a gene. This is followed by a return to the multiple testing problem of chapter 3 in the context of the data analysis of expression arrays.

I did not read the last two chapters on evolutionary models and phylogenetic tree estimation so I will omit their review.

guide into the right direction.......2001-09-06

This is one of the books I have been waiting for. For a population geneticist who wants to learn bioinformatics, most texts are unacceptable: They present heuristic methods in a cookbook fashion, with little reference to what is going on biologically as well as mathematically.

This book is the first exception I know of. It builds, and rests on, solid foundations of genetic stochastic processes and still goes all the way to real-life problems. Let me illustrate this by means of an example, rather than enumerating all the topics in the book.

Chap. 14, entitled `phylogenetic tree estimation' (as opposed to the more common term `phylogenetic tree reconstruction' - not without reason, I presume) builds on, and is firmly interlaced with, Chap. 13 about `evolutionary models', which systematizes the zoo (if not jungle) of substitution models in both discrete and continuous time. On this basis, the overview of tree-building methods makes a lot of sense. Even better, it does not stop here, but presents an application (to real sequence data), followed by a careful analysis of where the various methods agree, and where - and maybe why - they disagree. This way, it clears away some common misconceptions; in particular, it presents a careful analysis of what bootstrap does and what it does not in this context. The chapter closes with a discussion of unresolved problems (like inhomogeneity of substitution rates), and methods and possible pitfalls related to testing of nested and non-nested hypotheses in tree estimation.

The book is written in an informal style without being imprecise, which makes it pleasant reading. It is particularly suitable for teaching at a high level. This is enhanced by realistic (and even real-life) examples that furnish the text, as well as carefully chosen exercises at the end of each chapter.

Certainly, this first edition of `Statistical Methods in Bioinformatics' cannot be the last word in this fast-moving field. But it is an excellent guide into the `right' direction.

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