語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Comparative gene finding = models, a...
~
Axelson-Fisk, Marina.
FindBook
Google Book
Amazon
博客來
Comparative gene finding = models, algorithms and implementation /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Comparative gene finding/ by Marina Axelson-Fisk.
其他題名:
models, algorithms and implementation /
作者:
Axelson-Fisk, Marina.
出版者:
London :Springer London : : 2015.,
面頁冊數:
xx, 382 p. :ill., digital ;24 cm.
內容註:
Introduction -- Single Species Gene Finding -- Sequence Alignment -- Comparative Gene Finding -- Gene Structure Submodels -- Parameter Training -- Implementation of a Comparative Gene Finder -- Annotation Pipelines for Next Generation Sequencing Projects.
Contained By:
Springer eBooks
標題:
Genomics - Data processing. -
電子資源:
http://dx.doi.org/10.1007/978-1-4471-6693-1
ISBN:
9781447166931 (electronic bk.)
Comparative gene finding = models, algorithms and implementation /
Axelson-Fisk, Marina.
Comparative gene finding
models, algorithms and implementation /[electronic resource] :by Marina Axelson-Fisk. - 2nd ed. - London :Springer London :2015. - xx, 382 p. :ill., digital ;24 cm. - Computational biology,v.201568-2684 ;. - Computational biology ;v.20..
Introduction -- Single Species Gene Finding -- Sequence Alignment -- Comparative Gene Finding -- Gene Structure Submodels -- Parameter Training -- Implementation of a Comparative Gene Finder -- Annotation Pipelines for Next Generation Sequencing Projects.
This unique text/reference presents a concise guide to building computational gene finders, and describes the state of the art in computational gene finding methods, with a particular focus on comparative approaches. Fully updated and expanded, this new edition examines next-generation sequencing (NGS) technology, including annotation pipelines for NGS data. The book also discusses conditional random fields, enhancing the broad coverage of topics spanning probability theory, statistics, information theory, optimization theory, and numerical analysis. Topics and features: Introduces the fundamental terms and concepts in the field, and provides an historical overview of algorithm development Discusses algorithms for single-species gene finding, and approaches to pairwise and multiple sequence alignments, then describes how the strengths in both areas can be combined to improve the accuracy of gene finding Explores the gene features most commonly captured by a computational gene model, and explains the basics of parameter training Illustrates how to implement a comparative gene finder, reviewing the different steps and accuracy assessment measures used to debug and benchmark the software Examines NGS techniques, and how to build a genome annotation pipeline, discussing sequence assembly, de novo repeat masking, and gene prediction (NEW) Postgraduate students, and researchers wishing to enter the field quickly, will find this accessible text a valuable source of insights and examples. A suggested course outline for instructors is provided in the preface. Dr. Marina Axelson-Fisk is an Associate Professor at the Department of Mathematical Sciences of Chalmers University of Technology, Gothenburg, Sweden.
ISBN: 9781447166931 (electronic bk.)
Standard No.: 10.1007/978-1-4471-6693-1doiSubjects--Topical Terms:
722506
Genomics
--Data processing.
LC Class. No.: QH447
Dewey Class. No.: 572.860285
Comparative gene finding = models, algorithms and implementation /
LDR
:03032nmm m2200349 m 4500
001
2001552
003
DE-He213
005
20151110092938.0
006
m d
007
cr nn 008maaau
008
151215s2015 enk s 0 eng d
020
$a
9781447166931 (electronic bk.)
020
$a
9781447166924 (paper)
024
7
$a
10.1007/978-1-4471-6693-1
$2
doi
035
$a
978-1-4471-6693-1
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QH447
072
7
$a
PSA
$2
bicssc
072
7
$a
UB
$2
bicssc
072
7
$a
COM014000
$2
bisacsh
082
0 4
$a
572.860285
$2
23
090
$a
QH447
$b
.A969 2015
100
1
$a
Axelson-Fisk, Marina.
$3
1085387
245
1 0
$a
Comparative gene finding
$h
[electronic resource] :
$b
models, algorithms and implementation /
$c
by Marina Axelson-Fisk.
250
$a
2nd ed.
260
$a
London :
$b
Springer London :
$b
Imprint: Springer,
$c
2015.
300
$a
xx, 382 p. :
$b
ill., digital ;
$c
24 cm.
490
1
$a
Computational biology,
$x
1568-2684 ;
$v
v.20
505
0
$a
Introduction -- Single Species Gene Finding -- Sequence Alignment -- Comparative Gene Finding -- Gene Structure Submodels -- Parameter Training -- Implementation of a Comparative Gene Finder -- Annotation Pipelines for Next Generation Sequencing Projects.
520
$a
This unique text/reference presents a concise guide to building computational gene finders, and describes the state of the art in computational gene finding methods, with a particular focus on comparative approaches. Fully updated and expanded, this new edition examines next-generation sequencing (NGS) technology, including annotation pipelines for NGS data. The book also discusses conditional random fields, enhancing the broad coverage of topics spanning probability theory, statistics, information theory, optimization theory, and numerical analysis. Topics and features: Introduces the fundamental terms and concepts in the field, and provides an historical overview of algorithm development Discusses algorithms for single-species gene finding, and approaches to pairwise and multiple sequence alignments, then describes how the strengths in both areas can be combined to improve the accuracy of gene finding Explores the gene features most commonly captured by a computational gene model, and explains the basics of parameter training Illustrates how to implement a comparative gene finder, reviewing the different steps and accuracy assessment measures used to debug and benchmark the software Examines NGS techniques, and how to build a genome annotation pipeline, discussing sequence assembly, de novo repeat masking, and gene prediction (NEW) Postgraduate students, and researchers wishing to enter the field quickly, will find this accessible text a valuable source of insights and examples. A suggested course outline for instructors is provided in the preface. Dr. Marina Axelson-Fisk is an Associate Professor at the Department of Mathematical Sciences of Chalmers University of Technology, Gothenburg, Sweden.
650
0
$a
Genomics
$x
Data processing.
$3
722506
650
1 4
$a
Computer Science.
$3
626642
650
2 4
$a
Computational Biology/Bioinformatics.
$3
898313
650
2 4
$a
Bioinformatics.
$3
553671
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer eBooks
830
0
$a
Computational biology ;
$v
v.20.
$3
2145318
856
4 0
$u
http://dx.doi.org/10.1007/978-1-4471-6693-1
950
$a
Computer Science (Springer-11645)
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9270031
電子資源
11.線上閱覽_V
電子書
EB QH447 .A969 2015
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入