Cis/transgene optimization : systematic discovery of novel gene expression elements using bioinformatics and computational biology approaches /
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| Author / Creator: | Kadkhodaei, Saeid, author. |
|---|---|
| Imprint: | Cham, Switzerland : Springer, [2018] |
| Description: | 1 online resource |
| Language: | English |
| Series: | SpringerBriefs in systems biology SpringerBriefs in systems biology. |
| Subject: | |
| Format: | E-Resource Book |
| URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/11655125 |
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| 100 | 1 | |a Kadkhodaei, Saeid, |e author. | |
| 245 | 1 | 0 | |a Cis/transgene optimization : |b systematic discovery of novel gene expression elements using bioinformatics and computational biology approaches / |c Saeid Kadkhodaei, [and 10 others]. |
| 264 | 1 | |a Cham, Switzerland : |b Springer, |c [2018] | |
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 490 | 1 | |a SpringerBriefs in systems biology | |
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Intro; Preface; Acknowledgements; Contents; Acronyms; 1 Introduction; 1.1 Overview; 1.2 Scaffold/Matrix Attachment Regions (S/MARs); 1.3 Translation Initiation Site (TIS); 1.4 Signal Peptides; 1.5 Gene Optimization; References; 2 Systematic Strategies; 2.1 MARs (Fig. 2.1a); 2.1.1 S/MARs Data Mining, Motif Search, and Comparison in Databases; 2.1.2 Heatmap Cluster and Correlation Plot; 2.1.3 Scatter Plot for Correlation; 2.1.4 Design, Evaluation, and Synthesis of an Artificial MAR Sequence; 2.2 Translation Initiation Site (Fig. 2.1b); 2.2.1 Data Mining of the Microalgae MRNAs in Databases. | |
| 505 | 8 | |a 2.2.2 In Silico Analysis of the Full-Length mRNAs2.3 Signal Peptide Prediction (Fig. 2.1c); 2.4 Gene Optimization (Fig. 2.1d); 2.5 Microalgae Transformation; References; 3 Outcomes Assessment; 3.1 Scaffold/Matrix Attachment Regions (S/MARs); 3.1.1 Statistical Analysis of the S/MARs Structure; 3.1.2 Significant Motifs; 3.1.3 Intercorrelation Analysis; 3.1.4 Clustering Pattern Analysis; 3.1.5 Motif Mapping; 3.1.6 CpG Islands; 3.2 Translation Initiation Site (TIS); 3.3 Signal Peptide (SP) Prediction; 3.4 Gene Optimization; 3.4.1 Codon Optimization; 3.4.2 mRNA Secondary Structure. | |
| 505 | 8 | |a 3.5 Transformation3.5.1 Transformation Techniques; References; 4 Conceptual Models; 4.1 Scaffold/Matrix Attachment Regions (S/MARs); 4.2 Translation Initiation Site (TIS); 4.3 Signal Peptide Prediction; 4.4 Gene Optimization; 4.4.1 Codon Optimization; 4.4.2 mRNA Secondary Structure; 4.4.3 Additional Optimization Parameters; 4.5 Transformation; 4.6 Summary; References; Appendix A; Appendix B; Appendix C; Appendix D; Appendix E; Appendix F; Appendix G; Appendix H; Appendix I: The Detailed Methodology of the Transformation Procedure; Appendix J; Appendix K; Appendix L; Appendix M; Appendix N. | |
| 505 | 8 | |a Appendix OAppendix P; Appendix Q; Appendix R; Appendix S; Appendix T; Appendix U; Appendix V; Index. | |
| 588 | 0 | |a Online resource; title from digital title page (viewed on July 19, 2018). | |
| 520 | |a This book is a practical review which focuses on computational analysis and on in silicoapproaches towards the systematic discovery of various key functional gene expression elements in microalgae as a model. So far, in this regard very little information is available. Efficient stepwise procedures for analysing the matrix attachment regions (MARs) are outlined, as well as for translation initiation sites (TIS), signal peptide (SP) sequences, gene optimization and transformation systems. These outlines can be efficiently deployed as practical models for the systematic discovery of key expression elements and for the optimization of cis/transgenes in other micro/organisms. The first chapter is an introduction on the key gene expression elements analysed in this book, including scaffold/matrix attachment regions, translation initiation sites, signal peptides as well as gene optimization. Chapter 2 focuses on systematic strategies and computational approaches toward in silico analysis of each factor. The analyses outcomes is assessed individually in chapter 3 followed by developing the specific conceptual models for each element in Chapter 4. The concluding remarks are discussed in Chapter 5. This work is of interest to computational and experimental biologists interested in transcriptional regulation analysis as well as to researchers and scientists who wish to consider the use of bioinformatics and computational biology in design, analysis, or regulatory reviews of key gene expression elements for the production of recombinant proteins experiments. | ||
| 650 | 0 | |a Recombinant proteins. |0 http://id.loc.gov/authorities/subjects/sh90005744 | |
| 650 | 0 | |a Transgenes |x Expression. |0 http://id.loc.gov/authorities/subjects/sh99010677 | |
| 650 | 0 | |a Genomics. |0 http://id.loc.gov/authorities/subjects/sh2002000809 | |
| 650 | 7 | |a SCIENCE |x Chemistry |x Industrial & Technical. |2 bisacsh | |
| 650 | 7 | |a TECHNOLOGY & ENGINEERING |x Chemical & Biochemical. |2 bisacsh | |
| 650 | 7 | |a Life sciences: general issues. |2 bicssc | |
| 650 | 7 | |a Proteins. |2 bicssc | |
| 650 | 7 | |a Biology, life sciences. |2 bicssc | |
| 650 | 7 | |a Genomics. |2 fast |0 (OCoLC)fst00940228 | |
| 650 | 7 | |a Recombinant proteins. |2 fast |0 (OCoLC)fst01091505 | |
| 650 | 7 | |a Transgenes |x Expression. |2 fast |0 (OCoLC)fst01154665 | |
| 655 | 4 | |a Electronic books. | |
| 776 | 0 | 8 | |i Print version: |t CIS/TRANSGENE OPTIMIZATION. |d [Place of publication not identified] : SPRINGER INTERNATIONAL PU, 2018 |z 331990390X |z 9783319903903 |w (OCoLC)1029648003 |
| 830 | 0 | |a SpringerBriefs in systems biology. |0 http://id.loc.gov/authorities/names/n2013180242 | |
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