0387952292

[Bioinformatics]에 적용하기 위한 [Statistics]. 약간 어렵게 쓰여짐.

[Sefiroth/2003-04-17]부터 매주 한쳅터씩 스터디 진행

Preface

  • It is our belief that there is a need for a book that introduces probability, statistics, and stochastic process in the context of bioinformatics.
  • The material in this text assumes:
    • little or no background in biology
    • introductory courses in calculus and linear algebra
    • no computer science knowledge
  • Why are probability and statistics so important in bioinformatics?
    • Bioinformatics involves the analysis of biological data.
    • Many chance mechanisms are involved in the creation of these data, most importantly the many random processes inherent in biological evolution and the randomness inherent in any sampling process.
  • Our aim is to give an introductory account of som of the probability theory, statistics, and stochastic process theory appropriate to computational biology and bioinformatics.
  • This is not a "how-to" book ...
  • We do not cover aspects of the statistical thoery in genetics associated with disease finding and linkage analysis. This subject deserves an entire book on its own.
  • Nor do we discuss the increasingly important applications of bioinformatics in the stochastic theory of evolutionary population genetics. Again, all these topics deserve a complete treatment of their own.

  • errata http://www.textbook-errata.org

쳅터별 발제자

chapter

title

스터디날짜

발제자

페이지수

[StatisticalMethodsInBioinformatics/Chap1]

Probability Theory (1) : One random variable

[Sefiroth/2003-04-17]

SangeunChi

54

[StatisticalMethodsInBioinformatics/Chap2]

Probability Theory (2) : Many random variable

[Sefiroth/2003-04-24]

SangeunChi

50

[StatisticalMethodsInBioinformatics/Chap3]

Statistics (1) : An introduction to statistical inference

[Sefiroth/2003-05-01]

DrPepper

24

[StatisticalMethodsInBioinformatics/Chap4]

Stochastic processes (1) : Poisson processes and MarkovChain

[Sefiroth/2003-05-15]

[jtoh]

18

[StatisticalMethodsInBioinformatics/Chap5]

The analysis of one [DNA] sequence

[Sefiroth/2003-05-22]

[mutant]

34

[StatisticalMethodsInBioinformatics/Chap6]

The analysis of multiple [DNA] or [Protein] sequence

[Sefiroth/2003-05-29]

SangeunChi

38

[StatisticalMethodsInBioinformatics/Chap7]

Stochastic processes (2) : Random walks

[Sefiroth/2003-06-05]

ThreeColoredLearning

18

[StatisticalMethodsInBioinformatics/Chap8]

Statistics (2) : Classical estimation and hypothesis

[Sefiroth/2003-06-12]

ThreeColoredLearning

32

[StatisticalMethodsInBioinformatics/Chap9]

[BLAST]

.

[yong27]

34

[StatisticalMethodsInBioinformatics/Chap10]

Stochastic processes (3) : MarkovChain

.

[picxenk]

21

[StatisticalMethodsInBioinformatics/Chap11]

HiddenMarkovModels

.

[destine] ;

22

[StatisticalMethodsInBioinformatics/Chap12]

Computationally intensive methods

.

[sushy]

16

[StatisticalMethodsInBioinformatics/Chap13]

Evolutionary models

.

[glanze]

20

[StatisticalMethodsInBioinformatics/Chap14]

PhylogeneticTree estimation

.

[neosphere]

38

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