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Translational Bioinformatics for Therapeutic Development

Overview of attention for book
Cover of 'Translational Bioinformatics for Therapeutic Development'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    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 12: Synergistic Drug Combination Prediction by Integrating Multiomics Data in Deep Learning Models
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Chapter title
Synergistic Drug Combination Prediction by Integrating Multiomics Data in Deep Learning Models
Chapter number 12
Book title
Translational Bioinformatics for Therapeutic Development
Published in
Methods in molecular biology, September 2020
DOI 10.1007/978-1-0716-0849-4_12
Pubmed ID
32926369
Book ISBNs
978-1-07-160848-7, 978-1-07-160849-4
Authors

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

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X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 83 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 83 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 23%
Student > Master 10 12%
Researcher 8 10%
Student > Bachelor 6 7%
Other 3 4%
Other 12 14%
Unknown 25 30%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 14 17%
Computer Science 14 17%
Agricultural and Biological Sciences 5 6%
Chemistry 4 5%
Mathematics 3 4%
Other 13 16%
Unknown 30 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 September 2020.
All research outputs
#18,745,728
of 23,237,082 outputs
Outputs from Methods in molecular biology
#8,066
of 13,317 outputs
Outputs of similar age
#303,194
of 402,858 outputs
Outputs of similar age from Methods in molecular biology
#111
of 171 outputs
Altmetric has tracked 23,237,082 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,317 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 402,858 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 171 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.

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