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Biological Networks and Pathway Analysis

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Cover of 'Biological Networks and Pathway Analysis'

Table of Contents

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    Book Overview
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    Chapter 1 A Practical Guide to Quantitative Interactor Screening with Next-Generation Sequencing (QIS-Seq)
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    Chapter 2 sbv IMPROVER: Modern Approach to Systems Biology
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    Chapter 3 Mathematical Justification of Expression-Based Pathway Activation Scoring (PAS)
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    Chapter 4 Bioinformatics Meets Biomedicine: OncoFinder, a Quantitative Approach for Interrogating Molecular Pathways Using Gene Expression Data
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    Chapter 5 Strategic Integration of Multiple Bioinformatics Resources for System Level Analysis of Biological Networks
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    Chapter 6 Functional Analysis of OMICs Data and Small Molecule Compounds in an Integrated “Knowledge-Based” Platform
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    Chapter 7 Extracting the Strongest Signals from Omics Data: Differentially Expressed Pathways and Beyond
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    Chapter 8 Search for Master Regulators in Walking Cancer Pathways
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    Chapter 9 Mathematical Modeling of Avidity Distribution and Estimating General Binding Properties of Transcription Factors from Genome-Wide Binding Profiles
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    Chapter 10 A Weighted SNP Correlation Network Method for Estimating Polygenic Risk Scores
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    Chapter 11 Analysis of cis-Regulatory Elements in Gene Co-expression Networks in Cancer
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    Chapter 12 Rule Mining Techniques to Predict Prokaryotic Metabolic Pathways
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    Chapter 13 ArrayTrack: An FDA and Public Genomic Tool
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    Chapter 14 Identification of Transcriptional Regulators of Psoriasis from RNA-Seq Experiments
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    Chapter 15 Comprehensive Analyses of Tissue-Specific Networks with Implications to Psychiatric Diseases
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    Chapter 16 Semantic Data Integration and Knowledge Management to Represent Biological Network Associations
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    Chapter 17 Knowledge-Based Compact Disease Models: A Rapid Path from High-Throughput Data to Understanding Causative Mechanisms for a Complex Disease
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    Chapter 18 Pharmacologic Manipulation of Wnt Signaling and Cancer Stem Cells
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    Chapter 19 Functional Network Disruptions in Schizophrenia
Attention for Chapter 4: Bioinformatics Meets Biomedicine: OncoFinder, a Quantitative Approach for Interrogating Molecular Pathways Using Gene Expression Data
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Citations

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Chapter title
Bioinformatics Meets Biomedicine: OncoFinder, a Quantitative Approach for Interrogating Molecular Pathways Using Gene Expression Data
Chapter number 4
Book title
Biological Networks and Pathway Analysis
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-7027-8_4
Pubmed ID
Book ISBNs
978-1-4939-7025-4, 978-1-4939-7027-8
Authors

Anton A. Buzdin, Vladimir Prassolov, Alex A. Zhavoronkov, Nikolay M. Borisov

Abstract

We propose a biomathematical approach termed OncoFinder (OF) that enables performing both quantitative and qualitative analyses of the intracellular molecular pathway activation. OF utilizes an algorithm that distinguishes the activator/repressor role of every gene product in a pathway. This method is applicable for the analysis of any physiological, stress, malignancy, and other conditions at the molecular level. OF showed a strong potential to neutralize background-caused differences between experimental gene expression data obtained using NGS, microarray and modern proteomics techniques. Importantly, in most cases, pathway activation signatures were better markers of cancer progression compared to the individual gene products. OF also enables correlating pathway activation with the success of anticancer therapy for individual patients. We further expanded this approach to analyze impact of micro RNAs (miRs) on the regulation of cellular interactome. Many alternative sources provide information about miRs and their targets. However, instruments elucidating higher level impact of the established total miR profiles are still largely missing. A variant of OncoFinder termed MiRImpact enables linking miR expression data with its estimated outcome on the regulation of molecular processes, such as signaling, metabolic, cytoskeleton, and DNA repair pathways. MiRImpact was used to establish cancer-specific and cytomegaloviral infection-linked interactomic signatures for hundreds of molecular pathways. Interestingly, the impact of miRs appeared orthogonal to pathway regulation at the mRNA level, which stresses the importance of combining all available levels of gene regulation to build a more objective molecular model of cell.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 19%
Student > Ph. D. Student 2 13%
Researcher 2 13%
Student > Master 2 13%
Other 1 6%
Other 0 0%
Unknown 6 38%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 25%
Agricultural and Biological Sciences 2 13%
Engineering 2 13%
Unknown 8 50%