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Network Biology

Overview of attention for book
Cover of 'Network Biology'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 38 Networking Omic Data to Envisage Systems Biological Regulation
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    Chapter 40 Protein–Protein Interface and Disease: Perspective from Biomolecular Networks
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    Chapter 41 Rigid-Docking Approaches to Explore Protein-Protein Interaction Space.
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    Chapter 42 Cyanobacterial Biofuels: Strategies and Developments on Network and Modeling
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    Chapter 43 ChIP-Seq Data Analysis to Define Transcriptional Regulatory Networks
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    Chapter 44 Gene Expression Analysis Through Network Biology: Bioinformatics Approaches.
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    Chapter 45 Genome-Scale Modeling of Thermophilic Microorganisms
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    Chapter 46 Network Metamodeling: Effect of Correlation Metric Choice on Phylogenomic and Transcriptomic Network Topology
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    Chapter 49 Molecular Phylogenetics: Concepts for a Newcomer
Attention for Chapter 44: Gene Expression Analysis Through Network Biology: Bioinformatics Approaches.
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Chapter title
Gene Expression Analysis Through Network Biology: Bioinformatics Approaches.
Chapter number 44
Book title
Network Biology
Published in
Advances in biochemical engineering biotechnology, January 2016
DOI 10.1007/10_2016_44
Pubmed ID
27830311
Book ISBNs
978-3-31-956459-3, 978-3-31-956460-9
Authors

Kanthida Kusonmano

Abstract

Following the availability of high-throughput technologies, vast amounts of biological data have been generated. Gene expression is one example of the popular data that has been utilized for studying cellular systems in the tran scriptional level. Several bioinformatics approaches have been developed to analyze such data. A typical expression analysis identifies a ranked list of individual significant differentially expressed genes between two conditions of interest. However, it has been accepted that biomolecules in a living organism are working together and interacting with each other. Study through network analysis could be complementary to typical expression analysis and provides more contexts to understanding the biological systems. Conversely, expression data could provide clues to functional links between biomolecules in biological networks. In this chapter, bioinformatics approaches to analyze expression data in network levels including basic concepts of network biology are described. Different concepts to integrate expression data with interactome data and example studies are explained.

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X Demographics

The data shown below were collected from the profile of 1 X user 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 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 21%
Student > Master 3 13%
Student > Bachelor 3 13%
Researcher 2 8%
Student > Doctoral Student 1 4%
Other 3 13%
Unknown 7 29%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 17%
Agricultural and Biological Sciences 2 8%
Social Sciences 2 8%
Engineering 2 8%
Computer Science 2 8%
Other 3 13%
Unknown 9 38%
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 09 December 2016.
All research outputs
#18,490,948
of 22,912,409 outputs
Outputs from Advances in biochemical engineering biotechnology
#148
of 225 outputs
Outputs of similar age
#284,638
of 393,789 outputs
Outputs of similar age from Advances in biochemical engineering biotechnology
#15
of 23 outputs
Altmetric has tracked 22,912,409 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 225 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 20th percentile – i.e., 20% 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 393,789 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.

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