Frontiers in Computational and Systems Biology

1. Front Matter

   Pages I-XXV

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2. Analysis of Combinatorial Gene Regulation with Thermodynamic Models

   • Chieh-Chun Chen, Sheng Zhong

   Pages 1-17

3. RNA Secondary Structure Prediction and Gene Regulation by Small RNAs

   • Ye Ding

   Pages 19-37

4. Some Critical Data Quality Control Issues of Oligoarrays

   • Wenjiang J. Fu, Ming Li, Yalu Wen, Likit Preeyanon

   Pages 39-59

5. Stochastic-Process Approach to Nonequilibrium Thermodynamics and Biological Signal Transduction

   • Hao Ge

   Pages 61-81

6. Granger Causality: Theory and Applications

   • Shuixia Guo, Christophe Ladroue, Jianfeng Feng

   Pages 83-111

7. Transcription Factor Binding Site Identification by Phylogenetic Footprinting

   • Haiyan Hu, Xiaoman Li

   Pages 113-131

8. Learning Network from High-Dimensional Array Data

   • Li Hsu, Jie Peng, Pei Wang

   Pages 133-156

9. Computational Methods for Predicting Domain–Domain Interactions

   • Hyunju Lee, Ting Chen, Fengzhu Sun

   Pages 157-173

10. Irreversible Stochastic Processes, Coupled Diffusions and Systems Biochemistry

    • Pei-Zhe Shi, Hong Qian

    Pages 175-201

11. Probability Modeling and Statistical Inference in Periodic Cancer Screening

    • Dongfeng Wu, Gary L. Rosner

    Pages 203-218

12. On Construction of the Smallest One-sided Confidence Intervals and Its Application in Identifying the Minimum Effective Dose

    • Weizhen Wang

    Pages 219-230

13. Group Variable Selection Methods and Their Applications in Analysis of Genomic Data

    • Jun Xie, Lingmin Zeng

    Pages 231-248

14. Modeling Protein-Signaling Networks with Granger Causality Test

    • Wenqiang Yang, Qiang Luo

    Pages 249-257

15. DNA Copy Number Profiling in Normal and Tumor Genomes

    • Nancy R. Zhang

    Pages 259-281

16. Spatial Disease Surveillance: Methods and Applications

    • Tonglin Zhang

    Pages 283-300

17. From QTL Mapping to eQTL Analysis

    • Wei Zhang, Jun S. Liu

    Pages 301-329

18. An Evaluation of Gene Module Concepts in the Interpretation of Gene Expression Data

    • Xianghua Zhang, Hongyu Zhao

    Pages 331-349

19. Readout of Spike Waves in a Microcolumn

    • Xuejuan Zhang

    Pages 351-369

20. False Positive Control for Genome-Wide ChIP-Chip Tiling Arrays

    • Yu Zhang

    Pages 371-381

Biological and biomedical studies have entered a new era over the past two decades thanks to the wide use of mathematical models and computational approaches. A booming of computational biology, which sheerly was a theoretician’s fantasy twenty years ago, has become a reality. Obsession with computational biology and theoretical approaches is evidenced in articles hailing the arrival of what are va- ously called quantitative biology, bioinformatics, theoretical biology, and systems biology. New technologies and data resources in genetics, such as the International HapMap project, enable large-scale studies, such as genome-wide association st- ies, which could potentially identify most common genetic variants as well as rare variants of the human DNA that may alter individual’s susceptibility to disease and the response to medical treatment. Meanwhile the multi-electrode recording from behaving animals makes it feasible to control the animal mental activity, which could potentially leadto the development of useful brain–machine interfaces. - bracing the sheer volume of genetic, genomic, and other type of data, an essential approach is, ?rst of all, to avoid drowning the true signal in the data. It has been witnessed that theoretical approach to biology has emerged as a powerful and st- ulating research paradigm in biological studies, which in turn leads to a new - search paradigm in mathematics, physics, and computer science and moves forward with the interplays among experimental studies and outcomes, simulation studies, and theoretical investigations.

• Computational Biology
• Probability
• Statistics
• System Biology
• algorithms
• genome

From the reviews:

“This mosaic of reviews and research precisely reflects the dynamic field of computational and systems biology. All of the major organizational levels of life are represented … . Each chapter has a brief introduction to a biological subject, a review of the main mathematical and statistical models for that particular topic, and a description of the main applications and conclusions. There are an abundant number of references for each chapter. … This compilation … is likely to inspire generations of students, researchers, and readers.” (Adrian Pasculescu, ACM Computing Reviews, January, 2011)

• Centre for Scientific Computing, Dept. Computer Science & Mathematics, Warwick University, Coventry, United Kingdom

  Jianfeng Feng

• Dept. Epidemiology, Michigan State University, East Lansing, USA

  Wenjiang Fu

• Dept. Biological Sciences, University of Southern California, Los Angeles, USA

  Fengzhu Sun

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