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Next Generation Microarray Bioinformatics

Overview of attention for book
Cover of 'Next Generation Microarray Bioinformatics'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 A Primer on the Current State of Microarray Technologies
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    Chapter 2 The KEGG Databases and Tools Facilitating Omics Analysis: Latest Developments Involving Human Diseases and Pharmaceuticals.
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    Chapter 3 Next Generation Microarray Bioinformatics
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    Chapter 4 Analyzing Cancer Samples with SNP Arrays
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    Chapter 5 Classification Approaches for Microarray Gene Expression Data Analysis
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    Chapter 6 Biclustering of time series microarray data.
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    Chapter 7 Using the Bioconductor GeneAnswers Package to Interpret Gene Lists
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    Chapter 8 Analysis of Isoform Expression from Splicing Array Using Multiple Comparisons
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    Chapter 9 Functional Comparison of Microarray Data Across Multiple Platforms Using the Method of Percentage of Overlapping Functions
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    Chapter 10 Performance Comparison of Multiple Microarray Platforms for Gene Expression Profiling
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    Chapter 11 Integrative Approaches for Microarray Data Analysis
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    Chapter 12 Modeling Gene Regulation Networks Using Ordinary Differential Equations
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    Chapter 13 Nonhomogeneous Dynamic Bayesian Networks in Systems Biology
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    Chapter 14 Inference of Regulatory Networks from Microarray Data with R and the Bioconductor Package qpgraph
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    Chapter 15 Effective Non-linear Methods for Inferring Genetic Regulation from Time-Series Microarray Gene Expression Data
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    Chapter 16 An overview of the analysis of next generation sequencing data.
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    Chapter 17 How to Analyze Gene Expression Using RNA-Sequencing Data
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    Chapter 18 Analyzing ChIP-seq Data: Preprocessing, Normalization, Differential Identification, and Binding Pattern Characterization.
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    Chapter 19 Identifying Differential Histone Modification Sites from ChIP‐seq Data
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    Chapter 20 ChIP-Seq Data Analysis: Identification of Protein–DNA Binding Sites with SISSRs Peak-Finder
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    Chapter 21 Using ChIPMotifs for De Novo Motif Discovery of OCT4 and ZNF263 Based on ChIP-Based High-Throughput Experiments.
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    Chapter 22 Hidden Markov Models for Controlling False Discovery Rate in Genome-Wide Association Analysis
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    Chapter 23 Employing Gene Set Top Scoring Pairs to Identify Deregulated Pathway-Signatures in Dilated Cardiomyopathy from Integrated Microarray Gene Expression Data
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    Chapter 24 JAMIE: A Software Tool for Jointly Analyzing Multiple ChIP-chip Experiments
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    Chapter 25 Epigenetic Analysis: ChIP-chip and ChIP-seq
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    Chapter 26 BiNGS!SL-seq: A Bioinformatics Pipeline for the Analysis and Interpretation of Deep Sequencing Genome-Wide Synthetic Lethal Screen.
Attention for Chapter 6: Biclustering of time series microarray data.
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  • Above-average Attention Score compared to outputs of the same age and source (52nd percentile)

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Citations

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Chapter title
Biclustering of time series microarray data.
Chapter number 6
Book title
Next Generation Microarray Bioinformatics
Published in
Methods in molecular biology, December 2011
DOI 10.1007/978-1-61779-400-1_6
Pubmed ID
22130875
Book ISBNs
978-1-61779-399-8, 978-1-61779-400-1
Authors

Meng J, Huang Y, Jia Meng, Yufei Huang, Meng, Jia, Huang, Yufei

Abstract

Clustering is a popular data exploration technique widely used in microarray data analysis. In this chapter, we review ideas and algorithms of bicluster and its applications in time series microarray analysis. We introduce first the concept and importance of biclustering and its different variations. We then focus our discussion on the popular iterative signature algorithm (ISA) for searching biclusters in microarray dataset. Next, we discuss in detail the enrichment constraint time-dependent ISA (ECTDISA) for identifying biologically meaningful temporal transcription modules from time series microarray dataset. In the end, we provide an example of ECTDISA application to time series microarray data of Kaposi's Sarcoma-associated Herpesvirus (KSHV) infection.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 44%
Researcher 2 22%
Student > Doctoral Student 1 11%
Student > Master 1 11%
Professor > Associate Professor 1 11%
Other 0 0%
Readers by discipline Count As %
Agricultural and Biological Sciences 3 33%
Mathematics 2 22%
Computer Science 1 11%
Decision Sciences 1 11%
Medicine and Dentistry 1 11%
Other 1 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 19 June 2012.
All research outputs
#7,453,126
of 22,785,242 outputs
Outputs from Methods in molecular biology
#2,316
of 13,094 outputs
Outputs of similar age
#69,535
of 240,240 outputs
Outputs of similar age from Methods in molecular biology
#130
of 466 outputs
Altmetric has tracked 22,785,242 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,094 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done well, scoring higher than 76% of its peers.
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 240,240 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 466 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.

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