Protein engineering techniques : gateways to synthetic protein universe / Krishna Mohan Poluri, Khushboo Gulati
By: Poluri, Krishna Mohan, autor
Contributor(s): Gulati, Khushboo, autor
Material type:
E-bookSeries: (SpringerBriefs in applied sciences and technology, Forensic and medical bioinformatics, 2191-530X).Publisher: Singapore : Springer, [2017]Description: 1 recurso en línea.ISBN: 9789811027321; 9811027323.Subject: Ingeniería biomédica
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|---|
LIBRO-E NO PRÉSTAMO
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Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | TP248.65.P76 2017 EB (Browse shelf(Opens below)) | Acceso electrónico | eBook.20022550 |
Browsing Madrid Digital shelves, Shelving location: Acceso Electrónico (UEM) Close shelf browser (Hides shelf browser)
| TP248.65 .P76 2012 EB Recombinant Protein Production in Yeast : Methods and Protocols | TP248.65 .P76 2014 EB Protein Downstream Processing : Design, Development and Application of High and Low-Resolution Methods | TP248.65 .P76 2015 EB Insoluble Proteins : Methods and Protocols | TP248.65.P76 2017 EB Protein engineering techniques : gateways to synthetic protein universe | TP248.65 .P76 2017 EB Computational Protein Design | TP248.65 .P76 2018 EB Recombinant Protein Expression in Mammalian Cells : Methods and Protocols | TP248.65 .P76 2018 EB Protein Engineering : Methods and Protocols |
SpringerLink
World of Proteins: Structure-Function relationships and Engineering techniques -- Expanding the Synthetic Protein universe by guided Evolutionary Concepts -- Rationale Designing of Novel Proteins through Computational Approaches -- Generating the Fancy Protein Basket with De novo Approach -- Biotechnological Applications of Protein Engineering Methods.
This brief provides a broad overview of protein-engineering research, offering a glimpse of the most common experimental methods. It also presents various computational programs with applications that are widely used in directed evolution, computational and de novo protein design. Further, it sheds light on the advantages and pitfalls of existing methodologies and future perspectives of protein engineering techniques.
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