Translational Bioinformatics for Therapeutic Development

ISBN-13: 9781071608517 / Angielski / Miękka / 2021

Opis

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.

Spis treści

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