生物信息学中的数学方法引论
生物信息学中的数学方法引论作者:伊萨耶夫 开 本:32开 书号ISBN:9787030313812 定价:138.0 出版时间:2011-06-01 出版社:科学出版社 |
生物信息学中的数学方法引论 本书特色
This book looks at the mathematical foundations of the models currently iuse. This is crucial for the correct interpretatioof the outputs of the models. A bioinformaticiashould be able not only to use software packages, but also to know the mathematics behind these packages. From this point of view, mathematics departments throughout the world have a major role to play ibioinformatics educatioby teaching courses othe mathematical foundations of the subject. Based othe courses taught by the author the book combines several topics ibiological sequence analysis with mathematical and statistical material required for such analysis.
生物信息学中的数学方法引论 内容简介
POD产品说明: 1. 本产品为按需印刷(POD)图书,实行先付款,后印刷的流程。您在页面购买且完成支付后,订单转交出版社。出版社根据您的订单采用数字印刷的方式,单独为您印制该图书,属于定制产品。 2. 按需印刷的图书装帧均为平装书(含原为精装的图书)。由于印刷工艺、彩墨的批次不同,颜色会与老版本略有差异,但通常会比老版本的颜色更准确。原书内容含彩图的,统一变成黑白图,原书含光盘的,统一无法提供光盘。 3. 按需印刷的图书制作成本高于传统的单本成本,因此售价高于原书定价。 4. 按需印刷的图书,出版社生产周期一般为15个工作日(特殊情况除外)。请您耐心等待。 5. 按需印刷的图书,属于定制产品,不可取消订单,无质量问题不支持退货。
生物信息学中的数学方法引论 目录
part Ⅰ sequence analysis1 introduction: biological sequences
2 sequence alignment
2.1 sequence similarity
2.2 dynamic programming: global alignment
2.3 dynamic programming: local alignment
2.4 alignment with affine gap model
2.5 heuristic alignment algorithms
2.5.1 fasta
2.5.2 blast
2.6 significance of scores
2.7 multiple alignment
2.7.1 msa
2.7.2 progressive alignment
exercises
3 markov chains and hiddemarkov models
3.1 markov chains
3.2 hiddemarkov models
3.3 the viterbi algorithm
3.4 the forward algorithm
3.5 the backward algorithm and posterior decoding
3.6 parameter estimatiofor hmms
3.6.1 estimatiowhepaths are known
3.6.2 estimatiowhepaths are unknown
3.7 hmms with silent states
3.8 profile hmms
3.9 multiple sequence alignment by profile hmms
exercises
proteifolding
4.1 levels of proteistructure
4.2 predictioby profile hmms
4.3 threading
4.4 molecular modeling
4.5 lattice hp-model
exercises
5 phylogenetic reconstruction
5.1 phylogenetic trees
5.2 parsimony methods
5.3 distance methods
5.4 evolutionary models
5.4.1 the jukes-cantor model
5.4.2 the kimura model
5.4.3 the felsensteimodel
5.4.4 the hasegawa-kishino-yano (hky) model
5.5 maximum likelihood method
5.6 model comparison
exercises
part Ⅱ mathematical background for sequence analysis
6 elements of probability theory
6.1 sample spaces and events
6.2 probability measure
6.3 conditional probability
6.4 random variables
6.5 integratioof random variables
6.6 monotone functions othe real line
6.7 distributiofunctions
6.8 commotypes of random variables
6.8.1 the discrete type
6.8.2 the continuous type
6.9 commodiscrete and continuous distributions
6.9.1 the discrete case
6.9.2 the continuous case
6.10 vector-valued random variables
6.11 sequences of random variables
exercises
7 significance of sequence alignment scores
7.1 the problem
7.2 random walks
7.3 significance of scores
exercises
elements of statistics
8.1 statistical modeling
8.2 parameter estimation
8.3 hypothesis testing
8.4 significance of scores for global alignments
exercises
9 substitutiomatrices
9.1 the general form of a substitutiomatrix.
9.2 pam substitutiomatrices
9.3 blosum substitutiomatrices
exercises
references
自然科学 数学 数学理论
在线阅读
- 最新内容
- 相关内容
- 网友推荐
- 图文推荐
[家长教育] 孩子为什么会和父母感情疏离? (2019-07-14) |
[教师分享] 给远方姐姐的一封信 (2018-11-07) |
[教师分享] 伸缩门 (2018-11-07) |
[教师分享] 回家乡 (2018-11-07) |
[教师分享] 是风味也是人间 (2018-11-07) |
[教师分享] 一句格言的启示 (2018-11-07) |
[教师分享] 无规矩不成方圆 (2018-11-07) |
[教师分享] 第十届全国教育名家论坛有感(二) (2018-11-07) |
[教师分享] 贪玩的小狗 (2018-11-07) |
[教师分享] 未命名文章 (2018-11-07) |