國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Mathematica for bioinformaticsa Wolf...

Mias, George.

Mathematica for bioinformaticsa Wolfram language approach to omics /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Mathematica for bioinformaticsby George Mias.
其他題名:	a Wolfram language approach to omics /
作者:	Mias, George.
出版者:	Cham :Springer International Publishing :2018.
面頁冊數:	xvi, 384 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Life sciences.
電子資源:	http://dx.doi.org/10.1007/978-3-319-72377-8
ISBN:	9783319723778$q(electronic bk.)

Mathematica for bioinformaticsa Wolfram language approach to omics /
Mias, George.

Mathematica for bioinformaticsa Wolfram language approach to omics /[electronic resource] :by George Mias. - Cham :Springer International Publishing :2018. - xvi, 384 p. :ill., digital ;24 cm.

1 Introduction to Bioinformatics -- 2. A Mathematica Primer for Bioinformaticians -- 3. Statistics for Genomic Analysis -- 4. Genomic Sequences -- 5. Databases -- 6. Transcriptomics -- 7. Proteomics -- 8. Metabolomics -- 9. Systems Biology -- 10. Networks -- 11. Time Series Analysis -- 12. Omics Integration and Systems Medicine -- 13. Bioinformatics Development with Mathematica.

This book offers a comprehensive introduction to using Mathematica and the Wolfram Language for Bioinformatics. The chapters build gradually from basic concepts and the introduction of the Wolfram Language and coding paradigms in Mathematica, to detailed worked examples derived from typical research applications using Wolfram Language code. The coding examples range from basic sequence analysis, accessing genomic databases, and differential gene expression, to time series analysis of longitudinal omics experiments, multi-omics integration and building dynamic interactive bioinformatics tools using the Wolfram Language. The topics address the daily bioinformatics needs of a broad audience: experimental users looking to understand and visualize their data, beginner bioinformaticians acquiring coding expertise in providing biological research solutions, and practicing expert bioinformaticians working on omics who wish to expand their toolset to include the Wolfram Language.

ISBN: 9783319723778$q(electronic bk.)

Standard No.: 10.1007/978-3-319-72377-8doiSubjects--Topical Terms:

215795
Life sciences.

LC Class. No.: QH324.2 / .M53 2018

Dewey Class. No.: 570.285

Mathematica for bioinformaticsa Wolfram language approach to omics /
LDR:02389nmm a2200337 a 4500 001 533333
003 DE-He213
005 20180830172628.0
006 m d
007 cr nn 008maaau
008 181205s2018 gw s 0 eng d
020 $a 9783319723778$q(electronic bk.)
020 $a 9783319723761$q(paper)
024 7 $a 10.1007/978-3-319-72377-8 $2 doi
035 $a 978-3-319-72377-8
040 $a GP $c GP
041 0 $a eng
050 4 $a QH324.2 $b .M53 2018
072 7 $a PS $2 bicssc
072 7 $a UB $2 bicssc
072 7 $a SCI086000 $2 bisacsh
072 7 $a COM018000 $2 bisacsh
082 0 4 $a 570.285 $2 23
090 $a QH324.2 $b .M618 2018
100 1 $a Mias, George. $3 808969
245 1 0 $a Mathematica for bioinformatics $h [electronic resource] : $b a Wolfram language approach to omics / $c by George Mias.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2018.
300 $a xvi, 384 p. : $b ill., digital ; $c 24 cm.
505 0 $a 1 Introduction to Bioinformatics -- 2. A Mathematica Primer for Bioinformaticians -- 3. Statistics for Genomic Analysis -- 4. Genomic Sequences -- 5. Databases -- 6. Transcriptomics -- 7. Proteomics -- 8. Metabolomics -- 9. Systems Biology -- 10. Networks -- 11. Time Series Analysis -- 12. Omics Integration and Systems Medicine -- 13. Bioinformatics Development with Mathematica.
520 $a This book offers a comprehensive introduction to using Mathematica and the Wolfram Language for Bioinformatics. The chapters build gradually from basic concepts and the introduction of the Wolfram Language and coding paradigms in Mathematica, to detailed worked examples derived from typical research applications using Wolfram Language code. The coding examples range from basic sequence analysis, accessing genomic databases, and differential gene expression, to time series analysis of longitudinal omics experiments, multi-omics integration and building dynamic interactive bioinformatics tools using the Wolfram Language. The topics address the daily bioinformatics needs of a broad audience: experimental users looking to understand and visualize their data, beginner bioinformaticians acquiring coding expertise in providing biological research solutions, and practicing expert bioinformaticians working on omics who wish to expand their toolset to include the Wolfram Language.
650 0 $a Life sciences. $3 215795
650 0 $a Microarrays. $3 342827
650 0 $a Bioinformatics. $3 194415
650 0 $a Systems biology. $3 282663
650 0 $a Biometry. $3 182039
650 0 $a Metabolism. $3 192797
650 0 $a Computational biology. $3 210438
650 1 4 $a Life Sciences. $3 273679
650 2 4 $a Computer Appl. in Life Sciences. $3 274180
650 2 4 $a Metabolomics. $3 558411
650 2 4 $a Systems Biology. $3 245824
650 2 4 $a Computational Biology/Bioinformatics. $3 274833
650 2 4 $a Biostatistics. $3 339693
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-72377-8
950 $a Biomedical and Life Sciences (Springer-11642)