語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Handbook of Statistical Bioinformatics
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Handbook of Statistical Bioinformatics/ edited by Henry Horng-Shing Lu, Bernhard Schölkopf, Martin T. Wells, Hongyu Zhao.
其他作者:
Zhao, Hongyu.
面頁冊數:
VIII, 410 p. 80 illus., 67 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Biomedical Research. -
電子資源:
https://doi.org/10.1007/978-3-662-65902-1
ISBN:
9783662659021
Handbook of Statistical Bioinformatics
Handbook of Statistical Bioinformatics
[electronic resource] /edited by Henry Horng-Shing Lu, Bernhard Schölkopf, Martin T. Wells, Hongyu Zhao. - 2nd ed. 2022. - VIII, 410 p. 80 illus., 67 illus. in color.online resource. - Springer Handbooks of Computational Statistics,2197-9804. - Springer Handbooks of Computational Statistics,.
Preface -- Part I Single-cell Analysis -- Computational and statistical methods for single-cell RNA sequencing data -- Pre-processing, dimension reduction, and clustering for single-cell RNA-seq data -- Integrative analyses of single-cell multi-omics data: a review from a statistical perspective -- Approaches to marker gene identification from single-cell RNA-sequencing data -- Model-based clustering of single-cell omics data -- Deep learning methods for single cell omics data -- Part II Network Analysis -- Probabilistic Graphical Models for Gene Regulatory Networks -- Additive conditional independence for large and complex biological structures -- Integration of Boolean and Bayesian Networks -- Computational methods for identifying microRNA-gene regulatory modules -- Causal inference in biostatistics -- Bayesian Balance Mediation Analysis in Microbiome Studies -- Part III Systems Biology -- Identifying genetic loci associated with complex trait variability -- Cell Type Specific Analysis for Gene Expression and DNA Methylation -- Recent development of computational methods in the field of epitranscriptomics -- Estimation of Tumor Immune Signatures from Transcriptomics Data -- Cross-Linking Mass Spectrometry Data Analysis -- Cis-regulatory Element Frequency Modules and their Phase Transition across Hominidae -- Improving tip-dating and rooting a viral phylogeny by modeling evolutionary rate as a function of time.
Now in its second edition, this handbook collects authoritative contributions on modern methods and tools in statistical bioinformatics with a focus on the interface between computational statistics and cutting-edge developments in computational biology. The three parts of the book cover statistical methods for single-cell analysis, network analysis, and systems biology, with contributions by leading experts addressing key topics in probabilistic and statistical modeling and the analysis of massive data sets generated by modern biotechnology. This handbook will serve as a useful reference source for students, researchers and practitioners in statistics, computer science and biological and biomedical research, who are interested in the latest developments in computational statistics as applied to computational biology.
ISBN: 9783662659021
Standard No.: 10.1007/978-3-662-65902-1doiSubjects--Topical Terms:
643481
Biomedical Research.
LC Class. No.: QH323.5
Dewey Class. No.: 570.15195
Handbook of Statistical Bioinformatics
LDR
:03711nam a22003975i 4500
001
1086312
003
DE-He213
005
20221208144727.0
007
cr nn 008mamaa
008
221228s2022 gw | s |||| 0|eng d
020
$a
9783662659021
$9
978-3-662-65902-1
024
7
$a
10.1007/978-3-662-65902-1
$2
doi
035
$a
978-3-662-65902-1
050
4
$a
QH323.5
072
7
$a
PBT
$2
bicssc
072
7
$a
SCI086000
$2
bisacsh
072
7
$a
PBT
$2
thema
082
0 4
$a
570.15195
$2
23
245
1 0
$a
Handbook of Statistical Bioinformatics
$h
[electronic resource] /
$c
edited by Henry Horng-Shing Lu, Bernhard Schölkopf, Martin T. Wells, Hongyu Zhao.
250
$a
2nd ed. 2022.
264
1
$a
Berlin, Heidelberg :
$b
Springer Berlin Heidelberg :
$b
Imprint: Springer,
$c
2022.
300
$a
VIII, 410 p. 80 illus., 67 illus. in color.
$b
online resource.
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
347
$a
text file
$b
PDF
$2
rda
490
1
$a
Springer Handbooks of Computational Statistics,
$x
2197-9804
505
0
$a
Preface -- Part I Single-cell Analysis -- Computational and statistical methods for single-cell RNA sequencing data -- Pre-processing, dimension reduction, and clustering for single-cell RNA-seq data -- Integrative analyses of single-cell multi-omics data: a review from a statistical perspective -- Approaches to marker gene identification from single-cell RNA-sequencing data -- Model-based clustering of single-cell omics data -- Deep learning methods for single cell omics data -- Part II Network Analysis -- Probabilistic Graphical Models for Gene Regulatory Networks -- Additive conditional independence for large and complex biological structures -- Integration of Boolean and Bayesian Networks -- Computational methods for identifying microRNA-gene regulatory modules -- Causal inference in biostatistics -- Bayesian Balance Mediation Analysis in Microbiome Studies -- Part III Systems Biology -- Identifying genetic loci associated with complex trait variability -- Cell Type Specific Analysis for Gene Expression and DNA Methylation -- Recent development of computational methods in the field of epitranscriptomics -- Estimation of Tumor Immune Signatures from Transcriptomics Data -- Cross-Linking Mass Spectrometry Data Analysis -- Cis-regulatory Element Frequency Modules and their Phase Transition across Hominidae -- Improving tip-dating and rooting a viral phylogeny by modeling evolutionary rate as a function of time.
520
$a
Now in its second edition, this handbook collects authoritative contributions on modern methods and tools in statistical bioinformatics with a focus on the interface between computational statistics and cutting-edge developments in computational biology. The three parts of the book cover statistical methods for single-cell analysis, network analysis, and systems biology, with contributions by leading experts addressing key topics in probabilistic and statistical modeling and the analysis of massive data sets generated by modern biotechnology. This handbook will serve as a useful reference source for students, researchers and practitioners in statistics, computer science and biological and biomedical research, who are interested in the latest developments in computational statistics as applied to computational biology.
650
2 4
$a
Biomedical Research.
$3
643481
650
2 4
$a
Data Analysis and Big Data.
$3
1366136
650
2 4
$a
Computational and Systems Biology.
$3
1365723
650
2 4
$a
Statistics and Computing.
$3
1366004
650
1 4
$a
Biostatistics.
$3
783654
650
0
$a
Biology—Research.
$3
1365799
650
0
$a
Medicine—Research.
$3
1365798
650
0
$a
Quantitative research.
$3
635913
650
0
$a
Bioinformatics.
$3
583857
650
0
$a
Mathematical statistics—Data processing.
$3
1366001
650
0
$a
Biometry.
$3
598268
700
1
$a
Zhao, Hongyu.
$4
edt
$4
http://id.loc.gov/vocabulary/relators/edt
$3
788105
700
1
$a
Wells, Martin T.
$4
edt
$4
http://id.loc.gov/vocabulary/relators/edt
$3
783121
700
1
$a
Schölkopf, Bernhard.
$e
editor.
$4
edt
$4
http://id.loc.gov/vocabulary/relators/edt
$3
1393056
700
1
$a
Lu, Henry Horng-Shing.
$4
edt
$4
http://id.loc.gov/vocabulary/relators/edt
$3
788103
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9783662659014
776
0 8
$i
Printed edition:
$z
9783662659038
830
0
$a
Springer Handbooks of Computational Statistics,
$x
2197-9790
$3
1282210
856
4 0
$u
https://doi.org/10.1007/978-3-662-65902-1
912
$a
ZDB-2-SMA
912
$a
ZDB-2-SXMS
950
$a
Mathematics and Statistics (SpringerNature-11649)
950
$a
Mathematics and Statistics (R0) (SpringerNature-43713)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入