توضیحاتی در مورد کتاب :
سوال اساسی ما این است: با توجه به مجموعه ای از توالی های DNA، چه نیروهای زمینه ای مسئول الگوهای مشاهده شده تغییرپذیری هستند؟ برای نزدیک شدن به این سوال، تعدادی از مدلهای احتمال را معرفی و تحلیل میکنیم: مدل رایت-فیشر، مدل ادغامکننده، مدل آللهای نامحدود و مدل مکانهای نامحدود. ما عوارض ناشی از اندازه جمعیت غیر ثابت، نوترکیب، تقسیم جمعیت، و سه شکل انتخاب طبیعی را مطالعه میکنیم: انتخاب جهت، انتخاب متعادل، و انتخاب پسزمینه. این نتایج نظری زمینه را برای بررسی تست های آماری مختلف برای تشخیص انحرافات از "تکامل خنثی" فراهم می کند. فصل آخر تکامل کل ژنوم ها را با وارونگی های کروموزومی، جابه جایی های متقابل و تکثیر ژنوم مورد مطالعه قرار می دهد. در سراسر کتاب، این نظریه در ارتباط نزدیک با دادههای بیش از 60 مطالعه تجربی از ادبیات زیستشناسی که استفاده از این نتایج را نشان میدهد، توسعه مییابد. این کتاب برای ریاضیدانان و زیست شناسان نوشته شده است. ما هیچ دانش قبلی از مفاهیم زیست شناسی و فقط دانش اولیه احتمال را فرض نمی کنیم: یک دوره یک ترم کارشناسی و آشنایی با زنجیره های مارکوف و فرآیندهای پواسون. ریک دورت دکترای خود را دریافت کرد. در تحقیقات عملیاتی از دانشگاه استنفورد در سال 1976. او قبل از آمدن به کرنل در سال 1985 در بخش ریاضیات UCLA تدریس کرد. او نویسنده شش کتاب و 125 مقاله تحقیقاتی است و پدر دانشگاهی بیش از 30 دکترا است. دانش آموزان علایق فعلی او استفاده از مدل های احتمال در ژنتیک و بوم شناسی و کاهش میانگین و واریانس امتیاز گلف او است.
فهرست مطالب :
Preface
Contents
Basic Models
ATGCs of life
Wright-Fisher model
The coalescent
Shape of the genealogical tree
Infinite alleles model
Hoppe\'s urn, Ewens\' sampling formula
Chinese restaurants and sufficient statistics
Branching process viewpoint
Infinite sites model
Segregating sites
Nucleotide diversity
Pairwise differences
Folded site frequency spectrum
Moran model
Fixation probability and time
Site frequency spectrum mean
Estimation and Hypothesis Testing
Site frequency spectrum covariance
Estimates of
Hypothesis testing overview
Difference statistics
Tajima\'s D
Fu and Li\'s D
Fay and Wu\'s H
Conditioning on Sn
The HKA test
McDonald-Kreitman test
Recombination
Two loci
Sample of size 2
Sample of size n
m loci
Samples of size 2
Samples of size n
Pairwise differences
Linkage disequilibrium
Ancestral recombination graph
Simulation
Two approximate algorithms
Counting recombinations
Estimating recombination rates
Equations for the two-locus sampling distribution
Simulation methods
Composite likelihood estimation of
Haplotypes and hot spots
Population Complications
Large family sizes
Population growth
Exponential growth
Sudden population expansion
Founding effects and bottlenecks
Effective population size
Matrix migration models
Strobeck\'s theorem
Fast migration limit
Symmetric island model
Identity by descent
Mean and variance of coalescence times
Effective population sizes
Large n limit
Fixation indices
Stepping Stone Model
d = 1, Exact results
d = 1 and 2, Fourier methods
d = 2, Coalescence times
Random walk results
Samples of size 2
Fixation indices FST
d = 2, Genealogies
Simulation results
d = 1, Continuous models
d = 2, Continuous models
Natural Selection
Directional selection
Fixation probability
Time to fixation
Three phases of the fixation process
Ancestral selection graph
Balancing selection
Background selection
Muller\'s ratchet
Evolutionary advantages of recombination
Sex, epistasis, and Kondrashov
Hitchhiking
Better approximations
Recurrent sweeps
Nucleotide diversity
Genealogies
Segregating sites
Diffusion Processes
Infinitesimal mean and variance
Examples of diffusions
Transition probabilities
Hitting probabilities
Stationary measures
Occupation times
Green\'s functions
Examples
Conditioned processes
Boundary behavior
Site frequency spectrum
Poisson random field model
Fluctuating selection
Multidimensional Diffusions
K allele model
Fixation probabilities and time
Stationary distributions
Recombination
A clever change of variables
Time-dependent behavior
Equilibrium when there is mutation
Hill-Robertson interference
Gene duplication
Watterson\'s double recessive null model
Subfunctionalization
Genome Rearrangement
Inversions
Breakpoint graph
Hurdles
When is parsimony reliable?
Phase transition
Bayesian approach
Nadeau and Taylor\'s analysis
Genomic distance
Graph distance
Bayesian estimation
Midpoint problem
Genome duplication
Yeast
Maize
Arabidopsis thaliana
References
Index
توضیحاتی در مورد کتاب به زبان اصلی :
Our basic question is: Given a collection of DNA sequences, what underlying forces are responsible for the observed patterns of variability? To approach this question we introduce and analyze a number of probability models: the Wright-Fisher model, the coalescent, the infinite alleles model, and the infinite sites model. We study the complications that come from nonconstant population size, recombination, population subdivision, and three forms of natural selection: directional selection, balancing selection, and background selection. These theoretical results set the stage for the investigation of various statistical tests to detect departures from "neutral evolution." The final chapter studies the evolution of whole genomes by chromosomal inversions, reciprocal translocations, and genome duplication. Throughout the book, the theory is developed in close connection with data from more than 60 experimental studies from the biology literature that illustrate the use of these results. This book is written for mathematicians and for biologists alike. We assume no previous knowledge of concepts from biology and only a basic knowledge of probability: a one semester undergraduate course and some familiarity with Markov chains and Poisson processes. Rick Durrett received his Ph.D. in operations research from Stanford University in 1976. He taught in the UCLA mathematics department before coming to Cornell in 1985. He is the author of six books and 125 research papers, and is the academic father of more than 30 Ph.D. students. His current interests are the use of probability models in genetics and ecology, and decreasing the mean and variance of his golf score.