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Bioinformatics

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Cover of 'Bioinformatics'

Table of Contents

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    Book Overview
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    Chapter 1 3D Computational Modeling of Proteins Using Sparse Paramagnetic NMR Data.
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    Chapter 2 Inferring Function from Homology.
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    Chapter 3 Inferring Functional Relationships from Conservation of Gene Order.
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    Chapter 4 Structural and Functional Annotation of Long Noncoding RNAs.
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    Chapter 5 Construction of Functional Gene Networks Using Phylogenetic Profiles.
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    Chapter 6 Inferring Genome-Wide Interaction Networks.
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    Chapter 7 Integrating Heterogeneous Datasets for Cancer Module Identification.
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    Chapter 8 Metabolic Pathway Mining.
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    Chapter 9 Analysis of Genome-Wide Association Data.
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    Chapter 10 Adjusting for Familial Relatedness in the Analysis of GWAS Data.
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    Chapter 11 Analysis of Quantitative Trait Loci.
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    Chapter 12 High-Dimensional Profiling for Computational Diagnosis.
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    Chapter 13 Molecular Similarity Concepts for Informatics Applications.
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    Chapter 14 Compound Data Mining for Drug Discovery.
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    Chapter 15 Studying Antibody Repertoires with Next-Generation Sequencing.
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    Chapter 16 Using the QAPgrid Visualization Approach for Biomarker Identification of Cell-Specific Transcriptomic Signatures.
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    Chapter 17 Computer-Aided Breast Cancer Diagnosis with Optimal Feature Sets: Reduction Rules and Optimization Techniques.
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    Chapter 18 Inference Method for Developing Mathematical Models of Cell Signaling Pathways Using Proteomic Datasets.
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    Chapter 19 Clustering.
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    Chapter 20 Parameterized Algorithmics for Finding Exact Solutions of NP-Hard Biological Problems.
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    Chapter 21 Information Visualization for Biological Data.
Attention for Chapter 3: Inferring Functional Relationships from Conservation of Gene Order.
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Chapter title
Inferring Functional Relationships from Conservation of Gene Order.
Chapter number 3
Book title
Bioinformatics
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-6613-4_3
Pubmed ID
Book ISBNs
978-1-4939-6611-0, 978-1-4939-6613-4
Authors

Gabriel Moreno-Hagelsieb

Editors

Jonathan M. Keith

Abstract

Predicting functional associations using the Gene Neighbor Method depends on the simple idea that if genes are conserved next to each other in evolutionarily distant prokaryotes they might belong to a polycistronic transcription unit. The procedure presented in this chapter starts with the organization of the genes within genomes into pairs of adjacent genes. Then, the pairs of adjacent genes in a genome of interest are mapped to their corresponding orthologs in other, informative, genomes. The final step is to verify if the mapped orthologs are also pairs of adjacent genes in the informative genomes.

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Mendeley readers

The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 5%
Unknown 19 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 30%
Student > Ph. D. Student 4 20%
Lecturer > Senior Lecturer 2 10%
Professor > Associate Professor 2 10%
Student > Master 2 10%
Other 3 15%
Unknown 1 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 10 50%
Biochemistry, Genetics and Molecular Biology 5 25%
Computer Science 2 10%
Psychology 2 10%
Chemistry 1 5%
Other 0 0%