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Translational Bioinformatics for Therapeutic Development

Overview of attention for book
Translational Bioinformatics for Therapeutic Development
Springer US

Table of Contents

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    Book Overview
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    Chapter 1 Development and Optimization of Clinical Informatics Infrastructure to Support Bioinformatics at an Oncology Center
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    Chapter 2 Leveraging Pathology Informatics Concepts to Achieve Discrete Lab Data for Clinical Use and Translational Research
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    Chapter 3 Cohort Identification for Translational Bioinformatics Studies
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    Chapter 4 Transitioning Clinical Practice Guidelines into the Electronic Health Record through Clinical Pathways
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    Chapter 5 Variable Selection for Time-to-Event Data
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    Chapter 6 Binary Classification for Failure Risk Assessment
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    Chapter 7 Challenges and Opportunities of Genomic Approaches in Therapeutics Development
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    Chapter 8 Accessible Pipeline for Translational Research Using TCGA: Examples of Relating Gene Mechanism to Disease-Specific Outcomes
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    Chapter 9 Statistical and Bioinformatics Analysis of Data from Bulk and Single-Cell RNA Sequencing Experiments
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    Chapter 10 Investigating Inter- and Intrasample Diversity of Single-Cell RNA Sequencing Datasets
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    Chapter 11 Managing a Large-Scale Multiomics Project: A Team Science Case Study in Proteogenomics
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    Chapter 12 Synergistic Drug Combination Prediction by Integrating Multiomics Data in Deep Learning Models
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    Chapter 13 Introduction to Multiparametric Flow Cytometry and Analysis of High-Dimensional Data
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    Chapter 14 High-Dimensional Flow Cytometry Analysis of Regulatory Receptors on Human T Cells, NK Cells, and NKT Cells
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    Chapter 15 Quantitative Analysis of Bile Acid with UHPLC-MS/MS
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    Chapter 16 Sample Preparation and Data Analysis for NMR-Based Metabolomics
Attention for Chapter 14: High-Dimensional Flow Cytometry Analysis of Regulatory Receptors on Human T Cells, NK Cells, and NKT Cells
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