Frontiers in Computational and Systems Biology
Gebonden Engels 2010 2010e druk 9781849961950Samenvatting
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 lead to 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.
Specificaties
Lezersrecensies
Inhoudsopgave
Chieh-Chun Chen and Sheng Zhong
RNA Secondary Structure Prediction and Gene Regulation by Small RNAs
Ye Ding
Some Critical Data Quality Control Issues of Oligoarrays
Wenjiang J. Fu, Ming Li, Yalu Wen and Likit Preeyanon
Stochastic-process Approach to Nonequilibrium Thermodynamics and Biological Signal Transduction
Hao Ge
Granger Causality: Theory and Applications
Shuixia Guo, Christophe Ladroue and Jianfeng Feng
Transcription Factor Binding Site Identification by Phylogenetic Footprinting
Haiyan Hu and Xiaoman Li
Learning Network from High-dimensional Array Data
Li Hsu, Jie Peng and Pei Wang
Computational Methods for Predicting Domain-Domain Interactions
Hyunju Lee, Ting Chen and Fengzhu Sun
Irreversible Stochastic Processes, Coupled Diffusions and Systems Biochemistry
Pei-Zhe Shi and Hong Qian
Probability Modeling and Statistical Inference in Periodic Cancer Screening
Dongfeng Wu and Gary L. Rosner
On Construction of the Smallest One-sided Confidence Intervals and its Application in Identifying the Minimum Effective Dose
Weizhen Wang
Group Variable Selection Methods and Their Applications in Analysis of Genomic Data
Jun Xie and Lingmin Zeng
Modeling Protein-Signaling Networks with Granger Causality Test
Wenqiang Yang and Qiang Luo
DNA Copy Number Profiling in Normal and Tumor Genomes
Nancy R. Zhang
Spatial Disease Surveillance: Methods and Applications
Tonglin Zhang
From QTL Mapping to eQTL Analysis
Wei Zhang and Jun S Liu
An Evaluation of Gene Module Concepts in the Interpretation of Gene Expression Data
Xianghua Zhang and Hongyu Zhao
Readout of Spike Waves in a Microcolumn
Xuejuan Zhang
False Positive Control for Genome-wide ChIP-chip Tiling Arrays
Yu Zhang
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