生物统计学和生物信息学最新进展

商家名称	信用等级	购买信息	订购本书
		生物统计学和生物信息学最新进展
		生物统计学和生物信息学最新进展

基本信息·出版社：高等教育出版社
·页码：272 页
·出版日期：2008年12月
·ISBN：9787040247558
·条形码：9787040247558
·版本：第1版
·装帧：精装
·开本：16
·正文语种：英语
·丛书名：统计前沿
·外文书名：New Developmentsin Biostafistics and Bioinformatics

内容简介 《生物统计学和生物信息学最新进展(精装)》presents an overview of recent developments in biostatistics and bioinformatics. Written by active researchers in these emerging areas, it is intended to give graduate students and new researchers an idea of where the frontiers of biostatistics and bioinformatics are as well as a forum to learn common techniques in use, so that they can advance the fields via developing new techniques and new results. Extensive references are provided so that researchers can follow the threads to learn more comprehensively what the literature is and to conduct their own research. In particulars, the book covers three important and rapidly advancing topics in biostatistics: analysis of survival and longitudinal data, statistical methods for epidemiology.
编辑推荐 《生物统计学和生物信息学最新进展(精装)》是由高等教育出版社出版的。
目录
Preface
Part I Analysis of Survival and Longitudinal Data
hapter 1 Non- and Semi- Parametri Modeling in Survival Analysis
1 Introdu tion
2 ox's type of models
3 Multivariate ox's type of models
4 Model sele tion on ox's models
5 Validating ox's type of models
6 Transformation models
7 on luding remarks
Referen es
hapter 2 Additive-A elerated Rate Model for Re urrent Event
1 Introdu tion
2 Inferen e pro edure and asymptoti properties
3 Assessing additive and a elerated ovariates
4 Simulation studies
5 Appli ation
6 Remarks
A knowledgements
Appendix
Referen es
hapter 3 An Overview on Quadrati Inferen e Fun tion Approa hes for Longitudinal Data
1 Introdu tion
2 The quadrati inferen e fun tion approa h
3 Penalized quadrati inferen e fun tion
4 Some appli ations of QIF
5 Further resear h and on luding remarks
A knowledgements
Referen es
hapter 4 Modeling and Analysis of Spatially orrelated Data
1 Introdu tion
2 Basi on epts of spatial pro ess
3 Spatial models for non-normal/dis rete data
4 Spatial models for ensored out ome data
5 on luding remarks
Referen es

Part II Statisti al Methods for Epidemiology
hapter 5 Study Designs for Biomarker-Based Treatment Sele tion
1 Introdu tion
2 Definition of study designs
3 Test of hypotheses and sample size al ulation
4 Sample size al ulation
5 Numeri al omparisons of effi ien y
6 on lusions
A knowledgements
Appendix
Referen es
hapter 6 Statisti al Methods for Analyzing Two-Phase Studies
1 Introdu tion
2 Two-phase ase- ontrol or ross-se tional studies
3 Two-phase designs in ohort studies
4 on lusions
Referen es
Part III Bioinformati s
hapter 7 Protein Intera tion Predi tions from Diverse Sour es
1 Introdu tion
2 Data sour es useful for protein intera tion predi tions
3 Domain-based methods
4 lassifi ation methods
5 omplex dete tion methods
6 on lusions
A knowledgements
Referen es
hapter 8 Regulatory Motif Dis overy: From De oding to Meta-Analysis
1 Introdu tion
2 A Bayesian approa h to motif dis overy
3 Dis overy of regulatory modules
4 Motif dis overy in multiple spe ies
5 Motif learning on hiP- hip data
6 Using nu leosome positioning information in motif dis overy
7 on lusion
Referen es
hapter 9 Analysis of an er Genome Alterations Using Single Nu leotide Polymorphism (SNP) Mi roarrays
1 Ba kground
2 Loss of heterozygosity analysis using SNP arrays
3 opy number analysis using SNP arrays
4 High-level analysis using LOH and opy number data
5 Software for an er alteration analysis using SNP arrays
6 Prospe ts
A knowledgements
Referen es
hapter 10 Analysis of hiP- hip Data on Genome Tiling Mi roarrays
1 Ba kground mole ular biology
2 A hiP- hip experiment
3 Data des ription and analysis
4 Follow-up analysis
5 on lusion
Referen es
Subje t Index
Author Index
……
序言 The first eight years of the twenty-first century has witted the explosion of datacollection, with relatively low costs. Data with curves, images and movies are fre-quently collected in molecular biology, health science, engineering, geology, clima-tology, economics, finance, and humanities. For example, in biomedical research,MRI, fMRI, microarray, and proteomics data are frequently collected for eachsubject, involving hundreds of subjects; in molecular biology, massive sequencingdata are becoming rapidly available; in natural resource discovery and agricul-ture, thousands of high-resolution images are collected; in business and finance,millions of transactions are recorded every day. Frontiers of science, engineering,and humanities differ in the problems of their concerns, but nevertheless share acommon theme: massive or complex data have been collected and new knowledgeneeds to be discovered. Massive data collection and new scientific research havestrong impact on statistical thinking, methodological development, and theoreti-cal studies. They have also challenged traditional statistical theory, methods, andcomputation. Many new insights and phenomena need to be discovered and newstatistical tools need to be developed.
With this background, the Center for Statistical Research at the ChineseAcademy of Science initiated the conference series "International Conference onthe Frontiers of Statistics" in 2005. The aim is to provide a focal venue for re-searchers to gather, interact, and present their new research findings, to discussand outline emerging problems in their fields, to lay the groundwork for future col-laborations, and to engage more statistical scientists in China to conduct researchin the frontiers of statistics. After the general conference in 2005, the 2006 Inter-national Conference on the Frontiers of Statistics, held in Changchun, focused onthe topic "Biostatistics and Bioinformatics". The conference attracted many topresearchers in the area and was a great success. However, there are still a lot ofChinese scholars, particularly young researchers and graduate students, who werenot able to attend the conference. This hampers one of the purposes of the con-ference series. However, an Mternative idea was born: inviting active researchersto provide a bird-eye view on the new developments in the frontiers of statistics,on the theme topics of the conference series. This will broaden significantly thebenefits of statistical research, both in China and worldwide. The edited books inthis series aim at promoting statistical research that has high societal impacts andprovide not only a concise overview on the recent developments in the frontiers ofstatistics, but also useful references to the literature at large, leading readers trulyto the frontiers of statistics.
文摘 插图：


We assume that patients can be divided into twogroups based on an assay of a biomarker. This biomarker could be a compositeof hundreds of molecular and genetic factors, for example, but in this case wesuppose that a cutoff value has been determined that dichotomizes these values.In our example the biomarker is the expression of guanylyl cyclase C （GCC） in thelymph nodes of patients. We assume that we have an estimate of the sensitivityand specificity of the biomarker assay. The variable of patient response is takento be continuous-valued; it could represent a measure of toxicity to the patient,quality of life, uncensored survival time, or a composite of several measures. Inour example we take the endpoint to be three-year disease recurrence.
We consider five study designs, each addressing its own set of scientific ques-tions, to study how patients in each marker group fare with each treatment. Al-though consideration of which scientific questions are to be addressed by the studyshould supersede consideration of necessary sample size, we give efficiency com-parisons here for those cases in which more than one design would be appropriate.One potential goal is to investigate how treatment assignment and patient markerstatus affect outcome, both separately and interactively. The marker under con-sideration is supposedly predictive: it modifies the treatment effect. We may wantto verify its predictive value and to assess its prognostic value, that is, how wellit divides patients receiving the same treatment into different risk groups. Eachstudy design addresses different aspects of these overarching goals.
This paper is organized as follows:
1. Definition of study designs
2. Test of hypotheses
3. Sample size calculation
4. Numerical comparison of efficiency
5. Conclusions
2 Definition of study designs
The individual study designs are as follows.
2.1 Traditional design
To
……

查看更多 下一篇