Translational Bioinformatics for Therapeutic Development
 
A termék adatai:

ISBN13:9781071608487
ISBN10:1071608487
Kötéstípus:Keménykötés
Terjedelem:317 oldal
Méret:254x178 mm
Súly:831 g
Nyelv:angol
Illusztrációk: 9 Illustrations, black & white; 66 Illustrations, color
238
Témakör:

Translational Bioinformatics for Therapeutic Development

 
Kiadás sorszáma: 1st ed. 2021
Kiadó: Humana
Megjelenés dátuma:
Kötetek száma: 1 pieces, Book
 
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Kiadói listaár:
EUR 213.99
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Kedvezmény(ek): 20% (kb. 17 660 Ft)
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  példányt

 
Rövid leírás:

This volume introduces Translational Bioinformatics as it relates to therapeutic development, and addresses the techniques needed to effectively translate large data sets to relevant biological networks. Chapters detail clinical informatics infrastructure, and leverage pathology, immunology, pharmacology, genomic, proteomic, and metabolomic informatics approaches.   Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, application details for both the expert and non-expert reader, and tips on troubleshooting and avoiding known pitfalls.



 



Authoritative and practical, Translational Bioinformatics for Therapeutic Development: Methods and Protocols aims to ensure success in the study of Translational Bioinformatics.

Hosszú leírás:

This volume introduces Translational Bioinformatics as it relates to therapeutic development, and addresses the techniques needed to effectively translate large data sets to relevant biological networks. Chapters detail clinical informatics infrastructure, and leverage pathology, immunology, pharmacology, genomic, proteomic, and metabolomic informatics approaches.   Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, application details for both the expert and non-expert reader, and tips on troubleshooting and avoiding known pitfalls.



 



Authoritative and practical, Translational Bioinformatics for Therapeutic Development: Methods and Protocols aims to ensure success in the study of Translational Bioinformatics.

Tartalomjegyzék:

1. Development and Optimization of Clinical Informatics Infrastructure to Support Bioinformatics at an Oncology Center



Randa M. Perkins and Joseph Markowitz



 



2. Leveraging Pathology Informatics Concepts to Achieve Discrete Lab Data for Clinical Use and Translational Research



Mandy Flannery O?Leary



 



3. Cohort Identification for Translational Bioinformatics Studies



Tiffany A. Lin, Zeynep Eroglu, Rodrigo Carvajal, and Joseph Markowitz



 



4. Transitioning Clinical Practice Guidelines into the Electronic Health Record through Clinical Pathways



Sharjeel M. Hooda and Karen K. Fields



 



5. Variable Selection for Time-to-Event Data



Ai Ni and Chi Song



 



6. Binary Classification for Failure Risk Assessment



Ali Foroughi pour, Ian Loveless, Grzegorz Rempala and Maciej Pietrzak



 



7. Challenges and Opportunities of Genomic Approaches in Therapeutics Development



Jaimie S. Gray and Moray J. Campbell



 



8. Accessible Pipeline for Translational Research using TCGA: Examples of Relating Gene Mechanism to Disease Specific Outcomes



Anders E. Berglund, Ryan M Putney, Jordan H. Creed, Garrick Aden-Buie, Travis A. Gerke, and Robert J. Rounbehler



 



9. Statistical and Bioinformatics Analysis of Data from Bulk and Single-Cell RNA Sequencing Experiments



 Xiaoqing Yu, Farnoosh Abbas-Aghababazadeh, Y. Ann Chen, and Brooke L. Fridley



 



10. Investigating Inter- and Intra-Sample Diversity of  Single-Cell RNA Sequencing Datasets



Meghan C. Ferrall-Fairbanks and Philipp M. Altrock



 



11. Managing a Large-scale Multi-Omics Project: A Team Science Case Study in Proteogenomics



Paul A. Stewart, Eric A. Welsh, Bin Fang, Victoria Izumi, Tania Mesa, Chaomei Zhang, Sean Yoder, Guolin Zhang, Ling Cen, Fredrik Pettersson, Yonghong Zhang, Zhihua Chen, Chia-Ho Cheng, Ram Thapa, Zachary Thompson, Melissa Avedon, Marek Wloch, Michelle Fournier, Katherine M. Fellows, Jewel M. Francis, James J. Saller, Theresa A. Boyle, Y. Ann Chen, Eric B. Haura, Jamie K. Teer, Steven A. Eschrich, and John M. Koomen



 



12. Synergistic Drug Combination Prediction by Integrating Multi-omics Data in Deep Learning Models



Tianyu Zhang, Liwei Zhang, Philip R.O. Payne, and Fuhai Li



 



13. Introduction to Multi-Parametric Flow Cytometry and Analysis of High-Dimensional Data



James Sun, Jodi L. Kroeger, and Joseph Markowitz



 



14. High Dimensional Flow Cytometry Analysis of Regulatory Receptors on Human T cells, NK cells, and NKT Cells*



Ryosuke Nakagawa, Jason Brayer, Nicole Restrepo, James J. Mulé, and Adam W Mailloux



 



15. Quantitative Analysis of Bile Acid with UHPLC-MS/MS



Yuan Tian, Jingwei Cai, Erik L. Allman, Philip B. Smith, and Andrew D. Patterson



 



16. Sample Preparation and Data Analysis for NMR?based Metabolomics



Tapas K. Mal, Yuan Tian, and Andrew D. Patterson