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Книга Cis/Transgene Optimization Saeid Kadkhodaei

Cis/Transgene Optimization

Systematic Discovery of Novel Gene Expression Elements Using Bioinformatics and Computational Biology Approaches

Автор: Saeid Kadkhodaei, Arbakariya Ariff, Farahnaz Sadat Golestan Hashemi, Morvarid Akhavan Rezaei, Sahar Abbasiliasi, Joo Shun Tan, Hamid Rajabi Memari, Faruku Bande, Ali Baradaran, Mahdi Moradpour
Език: Английски език
Корици: С меки корици
Издател: Springer International Publishing AG
Наличност: Външен склад в ограничено количество
Изпращаме след 13-18 дни
59.25 € 115.87 лв
This book is a practical review which focuses on computational analysis and on in silico approaches...

Информация за книгата

Автор
Saeid Kadkhodaei, Arbakariya Ariff, Farahnaz Sadat Golestan Hashemi, Morvarid Akhavan Rezaei, Sahar Abbasiliasi, Joo Shun Tan, Hamid Rajabi Memari, Faruku Bande, Ali Baradaran, Mahdi Moradpour
Език
Английски език
Корици
Книга - С меки корици
Издадена
2018
страници
120
EAN
9783319903903
ISBN
331990390X
Enbook ID
19254932
Издател
Springer International Publishing AG
Теглоt
454
Размери
155 x 235 x 9

Пълно описание

This book is a practical review which focuses on computational analysis and on in silico approaches 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.

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