 |
 |
 |
 |
 |
 |
||
 |
 |
 |
 |
 |
| 查看: 7864 | 回復(fù): 166 | ||||||||||
| 【獎勵】 本帖被評價145次，作者1949stone增加金幣 114.2 個 | ||||||||||
1949stone榮譽(yù)版主 (知名作家)
|
[資源]
生物信息學(xué) 分子生物學(xué) Bioinformatics and Biomarker Discovery
|
|||||||||
|
Author and guest contributor biographies xi Acknowledgements xv Preface xvii 1 Biomarkers and bioinformatics 1 1.1 Bioinformatics, translational research and personalized medicine 1 1.2 Biomarkers: fundamental definitions and research principles 2 1.3 Clinical resources for biomarker studies 5 1.4 Molecular biology data sources for biomarker research 6 1.5 Basic computational approaches to biomarker discovery: key applications and challenges 7 1.6 Examples of biomarkers and applications 10 1.7 What is next? 12 2 Review of fundamental statistical concepts 15 2.1 Basic concepts and problems 15 2.2 Hypothesis testing and group comparison 19 2.3 Assessing statistical significance in multiple-hypotheses testing 20 2.4 Correlation 23 2.5 Regression and classification: basic concepts 23 2.6 Survival analysis methods 26 2.7 Assessing predictive quality 28 2.8 Data sample size estimation 32 2.9 Common pitfalls and misinterpretations 34 3 Biomarker-based prediction models: design and interpretation principles 37 3.1 Biomarker discovery and prediction model development 37 3.2 Evaluation of biomarker-based prediction models 38 3.3 Overview of data mining and key biomarker-based classification techniques 40 3.4 Feature selection for biomarker discovery 47 3.5 Critical design and interpretation factors 52 4 An introduction to the discovery and analysis of genotype-phenotype associations 57 4.1 Introduction: sources of genomic variation 57 4.2 Fundamental biological and statistical concepts 60 4.3 Multi-stage case-control analysis 64 4.4 SNPs data analysis: additional concepts, approaches and applications 64 4.5 CNV data analysis: additional concepts, approaches and applications 68 4.6 Key problems and challenges 69 Guest commentary on chapter 4: Integrative approaches to genotype-phenotype association discovery 73 Ana Dopazo References 76 5 Biomarkers and gene expression data analysis 77 5.1 Introduction 77 5.2 Fundamental analytical steps in gene expression profiling 79 5.3 Examples of advances and applications 82 5.4 Examples of the roles of advanced data mining and computational intelligence 84 5.5 Key limitations, common pitfalls and challenges 85 Guest commentary on chapter 5: Advances in biomarker discovery with gene expression data 89 Haiying Wang, Huiru Zheng Unsupervised clustering approaches 90 Module-based approaches 91 Final remarks 92 References 92 6 Proteomics and metabolomics for biomarker discovery: an introduction to spectral data analysis 93 6.1 Introduction 93 6.2 Proteomics and biomarker discovery 94 6.3 Metabolomics and biomarker discovery 97 6.4 Experimental techniques for proteomics and metabolomics: an overview 99 6.5 More on the fundamentals of spectral data analysis 100 viii CONTENTS 6.6 Targeted and global analyses in metabolomics 101 6.7 Feature transformation, selection and classification of spectral data 102 6.8 Key software and information resources for proteomics and metabolomics 106 6.9 Gaps and challenges in bioinformatics 107 Guest commentary on chapter 6: Data integration in proteomics and metabolomics for biomarker discovery 111 Kenneth Bryan Data integration and feature selection 112 References 114 7 Disease biomarkers and biological interaction networks 115 7.1 Network-centric views of disease biomarker discovery 115 7.2 Basic concepts in network analysis 118 7.3 Fundamental approaches to representing and inferring networks 119 7.4 Overview of key network-driven approaches to biomarker discovery 120 7.5 Network-based prognostic systems: recent research highlights 124 7.6 Final remarks: opportunities and obstacles in network-based biomarker research 127 Guest commentary on chapter 7: Commentary on ‘disease biomarkers and biological interaction networks’ 131 Zhongming Zhao Integrative approaches to biomarker discovery 132 Pathway-based analysis of GWA data 133 Integrative analysis of networks and pathways 134 References 134 8 Integrative data analysis for biomarker discovery 137 8.1 Introduction 137 8.2 Data aggregation at the model input level 141 8.3 Model integration based on a single-source or homogeneous data sources 141 8.4 Data integration at the model level 144 8.5 Multiple heterogeneous data and model integration 145 8.6 Serial integration of source and models 148 8.7 Component- and network-centric approaches 151 8.8 Final remarks 152 Guest commentary on chapter 8: Data integration: The next big hope? 155 Yves Moreau References 158 9 Information resources and software tools for biomarker discovery 159 9.1 Biomarker discovery frameworks: key software and information resources 159 CONTENTS ix 9.2 Integrating and sharing resources: databases and tools 161 9.3 Data mining tools and platforms 166 9.4 Specialized information and knowledge resources 168 9.5 Integrative infrastructure initiatives and inter-institutional programmes 168 9.6 Innovation outlook: challenges and progress 169 10 Challenges and research directions in bioinformatics and biomarker discovery 173 10.1 Introduction 173 10.2 Better software 175 10.3 The clinical relevance of new biomarkers 176 10.4 Collaboration 177 10.5 Evaluating and validating biomarker models 178 10.6 Defining and measuring phenotypes 181 10.7 Documenting and reporting biomarker research 181 10.8 Intelligent data analysis and computational models 184 10.9 Integrated systems and infrastructures for biomedical computing 185 10.10 Open access to research information and outcomes 186 10.11 Systems-based approaches 187 10.12 Training a new generation of researchers for translational bioinformatics 188 10.13 Maximizing the use of public resources 189 10.14 Final remarks 189 Guest commentary (1) on chapter 10: Towards building knowledge-based assistants for intelligent data analysis in biomarker discovery 193 Riccardo Bellazzi References 196 Guest commentary (2) on chapter 10: Accompanying commentary on ‘challenges and opportunities of bioinformatics in disease biomarker discovery’ 197 Gary B. Fogel Introduction 197 Biocyberinfrastructure 198 Government Regulations on biomarker discovery 198 Computational intelligence approaches for biomarker discovery 199 Open source data, intellectual property, and patient privacy 199 Conclusions 200 References 200 References 203 Index 223 x CONTENTS |
回復(fù)此樓» 本帖附件資源列表
-
歡迎監(jiān)督和反饋：小木蟲僅提供交流平臺，不對該內(nèi)容負(fù)責(zé)。
本內(nèi)容由用戶自主發(fā)布，如果其內(nèi)容涉及到知識產(chǎn)權(quán)問題，其責(zé)任在于用戶本人，如對版權(quán)有異議，請聯(lián)系郵箱：xiaomuchong@tal.com - 附件 1 : Bioinformatics and Biomarker Discovery.pdf
2012-02-12 19:28:48, 1.73 M
» 收錄本帖的淘帖專輯推薦
 專業(yè)電子書 | Learning English | 分子生物實(shí)驗(yàn)及蛋白純化結(jié)晶相關(guān)鏈接 | 生物信息學(xué) |
| 生命書籍 | 科研輔助 | Nitrification | 劉安安 |
» 本帖已獲得的紅花（最新10朵）
凌波麗» 猜你喜歡
不合理蛙科研實(shí)驗(yàn)中的趣事：實(shí)驗(yàn)器材的 “烏龍”
已經(jīng)有0人回復(fù)
-
不合理蛙科研實(shí)驗(yàn)中的趣事：和實(shí)驗(yàn)材料的 “斗智斗勇”
已經(jīng)有0人回復(fù)
-
化學(xué)工程及工業(yè)化學(xué)論文潤色/翻譯怎么收費(fèi)?
已經(jīng)有257人回復(fù)
-
蛋白質(zhì)檢測：精準(zhǔn)分析，解鎖生物分子的密碼
已經(jīng)有0人回復(fù)
-
不合理蛙科研實(shí)驗(yàn)之小鼠實(shí)驗(yàn)：嚴(yán)謹(jǐn)設(shè)計(jì)，解析生命機(jī)制的重要載體
已經(jīng)有0人回復(fù)
-
不合理蛙科研實(shí)驗(yàn)之重金屬檢測：精準(zhǔn)篩查，守護(hù)健康與環(huán)境的防線
已經(jīng)有0人回復(fù)
-
不合理蛙科研實(shí)驗(yàn)之“蛙測重金屬我背鍋三千”
已經(jīng)有0人回復(fù)
-
不合理蛙科研實(shí)驗(yàn)之“鼠逃三次我發(fā)三篇SCI”
已經(jīng)有0人回復(fù)
-
納米粒度分析
已經(jīng)有3人回復(fù)
-
林科院林化所招收材料與化工專業(yè)碩士，坐標(biāo)南京
已經(jīng)有0人回復(fù)
» 本主題相關(guān)商家推薦: (我也要在這里推廣)
» 本主題相關(guān)價值貼推薦，對您同樣有幫助:
- 10th International Symposium on Bioinformatics Research and Applications
已經(jīng)有53人回復(fù)
- 關(guān)于data mining and knowledge discovery的投稿
已經(jīng)有9人回復(fù)
- 求軟件 Integromics Biomarker Discovery for TIBCO Spotfire
已經(jīng)有3人回復(fù)
- 生物信息學(xué)國內(nèi)學(xué)者TOPs【歡迎交流】
已經(jīng)有11人回復(fù)
- 【分享】【想出國的蟲子們進(jìn)來啦】【出國口語】【已搜索無重復(fù)】
已經(jīng)有16人回復(fù)
- 【課后答案】-新世紀(jì)研究生英語聽說教程習(xí)題答案
已經(jīng)有53人回復(fù)
- F1000：七大細(xì)胞生物學(xué)論文---ebiotrade
已經(jīng)有6人回復(fù)
27樓2012-02-13 13:29:18
33樓2012-02-13 19:45:42
簡單回復(fù)
florayo2樓
2012-02-12 19:53
回復(fù)
五星好評 
2012-02-12 19:54
回復(fù)
五星好評 頂一下，感謝分享！
ivxy4樓
2012-02-12 21:00
回復(fù)
五星好評 頂一下，感謝分享！
yjl1555樓
2012-02-13 00:07
回復(fù)
五星好評 頂一下，感謝分享！
hxs-5206樓
2012-02-13 05:34
回復(fù)
五星好評 頂一下，感謝分享！
2012-02-13 05:51
回復(fù)
五星好評 
cnliu518樓
2012-02-13 06:03
回復(fù)
五星好評 頂一下，感謝分享！
jinhx879樓
2012-02-13 07:16
回復(fù)
五星好評 頂一下，感謝分享！
daweizhou10樓
2012-02-13 07:38
回復(fù)
五星好評 頂一下，感謝分享！
tswangan11樓
2012-02-13 07:59
回復(fù)
五星好評 頂一下，感謝分享！
ymmno612樓
2012-02-13 08:05
回復(fù)
五星好評 頂一下，感謝分享！
ymmno613樓
2012-02-13 08:06
回復(fù)
頂一下，感謝分享！
lufuhao14樓
2012-02-13 08:30
回復(fù)
五星好評 頂一下，感謝分享！
zouhongs15樓
2012-02-13 08:52
回復(fù)
五星好評 頂一下，感謝分享！
maxiaohu16樓
2012-02-13 09:17
回復(fù)
三星好評 頂一下，感謝分享！
jy201217樓
2012-02-13 09:37
回復(fù)
五星好評 頂一下，感謝分享！
diandong18樓
2012-02-13 10:36
回復(fù)
五星好評 頂一下，感謝分享！
hxq32019樓
2012-02-13 10:59
回復(fù)
五星好評 頂一下，感謝分享！
sjshvdc20樓
2012-02-13 11:10
回復(fù)
五星好評 頂一下，感謝分享！
csxu2010060821樓
2012-02-13 11:46
回復(fù)
五星好評 頂一下，感謝分享！
csxu2010060822樓
2012-02-13 11:46
回復(fù)
頂一下，感謝分享！
liyy95623樓
2012-02-13 11:53
回復(fù)
五星好評 頂一下，感謝分享！
thinktwice24樓
2012-02-13 12:17
回復(fù)
五星好評 頂一下，感謝分享！
stephenreal25樓
2012-02-13 13:09
回復(fù)
五星好評 頂一下，感謝分享！
ljsh26樓
2012-02-13 13:18
回復(fù)
五星好評 頂一下，感謝分享！
wenzi633728樓
2012-02-13 13:54
回復(fù)
五星好評 頂一下，感謝分享！
wangli101829樓
2012-02-13 14:47
回復(fù)
五星好評 頂一下，感謝分享！
wacke30樓
2012-02-13 16:19
回復(fù)
五星好評 頂一下，感謝分享！
蘿卜絲兒31樓
2012-02-13 18:29
回復(fù)
五星好評 頂一下，感謝分享！
tssy7732樓
2012-02-13 18:48
回復(fù)
五星好評 頂一下，感謝分享！
liygmail34樓
2012-02-13 22:12
回復(fù)
五星好評 頂一下，感謝分享！
常小晶35樓
2012-02-14 08:57
回復(fù)
五星好評 頂一下，感謝分享！
joblee36樓
2012-02-14 09:28
回復(fù)
五星好評 頂一下，感謝分享！
diaoruiying37樓
2012-02-14 11:04
回復(fù)
五星好評 頂一下，感謝分享！
panl23438樓
2012-02-14 11:05
回復(fù)
五星好評 頂一下，感謝分享！
coolsc39樓
2012-02-14 15:47
回復(fù)
五星好評 頂一下，感謝分享！
藍(lán)索道人40樓
2012-02-14 17:30
回復(fù)
五星好評 頂一下，感謝分享！
小啊東41樓
2012-02-14 18:41
回復(fù)
五星好評 頂一下，感謝分享！
zhoujunbo42樓
2012-02-14 18:47
回復(fù)
頂一下，感謝分享！
topstone43樓
2012-02-14 19:03
回復(fù)
五星好評 頂一下，感謝分享！
西安事變44樓
2012-02-14 19:58
回復(fù)
五星好評 頂一下，感謝分享！
bjhg12845樓
2012-02-14 20:27
回復(fù)
一般 頂一下，感謝分享！
yanranbaobao46樓
2012-02-15 11:14
回復(fù)
五星好評 頂一下，感謝分享！
heta10147樓
2012-02-15 21:52
回復(fù)
五星好評 頂一下，感謝分享！
飛鴛48樓
2012-02-16 08:11
回復(fù)
三星好評 頂一下，感謝分享！
zhoujing200749樓
2012-02-16 08:40
回復(fù)
五星好評 頂一下，感謝分享！
yinjj50樓
2012-02-16 09:16
回復(fù)
五星好評 頂一下，感謝分享！
相關(guān)版塊跳轉(zhuǎn)
我要訂閱樓主 1949stone 的主題更新
| 最具人氣熱帖推薦 [查看全部] | 作者 | 回/看 | 最后發(fā)表 | |
|---|---|---|---|---|
|
[考研] 085700資源與環(huán)境308求調(diào)劑 +3 | 墨墨漠 2026-03-18 | 3/150 |
|
|---|---|---|---|---|
|
|
[考研] 求材料調(diào)劑 +8 | 隔壁陳先生 2026-03-12 | 8/400 |
|
|
|
[考研] 344求調(diào)劑 +6 | knight344 2026-03-16 | 7/350 |
|
|
|
[考研] 一志愿985，本科211，0817化學(xué)工程與技術(shù)319求調(diào)劑 +7 | Liwangman 2026-03-15 | 7/350 |
|
|
[考研] 材料與化工一志愿南昌大學(xué)327求調(diào)劑推薦 +8 | Ncdx123456 2026-03-13 | 9/450 |
|
|
|
[考研]
 0854，計(jì)算機(jī)類招收調(diào)劑
+3
|
胡辣湯放糖 2026-03-15 | 6/300 |
|
|
|
[考研] 299求調(diào)劑 +5 | △小透明* 2026-03-17 | 5/250 |
|
|
|
[考研] 301求調(diào)劑 +9 | yy要上岸呀 2026-03-17 | 9/450 |
|
|
|
[考研] 材料與化工專碩調(diào)劑 +5 | heming3743 2026-03-16 | 5/250 |
|
|
|
[考研] 275求調(diào)劑 +4 | 太陽花天天開心 2026-03-16 | 4/200 |
|
|
|
[考研] 304求調(diào)劑 +4 | ahbd 2026-03-14 | 4/200 |
|
|
|
[考研] 0703一志愿211 285分求調(diào)劑 +5 | ly3471z 2026-03-13 | 5/250 |
|
|
|
[考研] 22408總分284求調(diào)劑 +3 | InAspic 2026-03-13 | 3/150 |
|
|
|
[考研] 294求調(diào)劑 +3 | Zys010410@ 2026-03-13 | 4/200 |
|
|
|
[考研] 255求調(diào)劑 +3 | 李嘉慧， 2026-03-12 | 4/200 |
|
|
|
[考研] 求材料調(diào)劑 085600英一數(shù)二總分302 前三科235 精通機(jī)器學(xué)習(xí) 一志愿哈工大 +4 | 林yaxin 2026-03-12 | 4/200 |
|
|
|
[考研] 0856材料與化工301求調(diào)劑 +5 | 奕束光 2026-03-13 | 5/250 |
|
|
|
[考研] 307求調(diào)劑 +5 | 超級伊昂大王 2026-03-12 | 5/250 |
|
|
|
[考研] 工科278分求調(diào)劑 +5 | 周慢熱啊 2026-03-12 | 7/350 |
|
|
|
[考研] 277求調(diào)劑 +4 | anchor17 2026-03-12 | 4/200 |
|