Special Issue "Network Visualization and Visual Network Analysis: Cytoscape Apps & Co"

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Technologies and Resources for Genetics".

Deadline for manuscript submissions: 15 October 2018

Special Issue Editor

Guest Editor
Prof. Dr. Frank Kramer

IT Infrastructure for Translational Medicine, Department of Computer Science, University of Augsburg, 86159 Augsburg, Germany
Website | E-Mail
Interests: network visualization;network modeling;pathway knowledge;pathway analysis

Special Issue Information

Dear Colleagues,

Using networks to visualize knowledge and results helps readers to understand complex molecular interactions and relationships more easily. A single pathway sketch can contain dozens of interconnected molecules or chemicals and can still be understood by a human. Recently-established high-throughput technologies have led to a surge in newly-generated knowledge on molecular interactions in biology and medicine. The computational representation of biological networks facilitates new opportunities of data and knowledge exchange between researchers, and asserts a common vocabulary and understanding of underlying principles. Standards, methods and tools to visualize networks are continuously evolving in order to keep up with biomedical research and technological advances. In this Special Issue, we would like to invite submissions of original research and short communications on software tools, as well as review articles on topics related to “Network Visualization and Visual Network Analysis”. We look forward to receiving your contributions.

Dr. Frank Kramer
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Genes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • network visualization
  • network analysis
  • pathway knowledge
  • cytoscape
  • bioinformatics

Published Papers (1 paper)

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Review

Open AccessReview Network-Based Approaches to Explore Complex Biological Systems towards Network Medicine
Received: 3 August 2018 / Revised: 25 August 2018 / Accepted: 30 August 2018 / Published: 31 August 2018
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Abstract
Network medicine relies on different types of networks: from the molecular level of protein–protein interactions to gene regulatory network and correlation studies of gene expression. Among network approaches based on the analysis of the topological properties of protein–protein interaction (PPI) networks, we discuss
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Network medicine relies on different types of networks: from the molecular level of protein–protein interactions to gene regulatory network and correlation studies of gene expression. Among network approaches based on the analysis of the topological properties of protein–protein interaction (PPI) networks, we discuss the widespread DIAMOnD (disease module detection) algorithm. Starting from the assumption that PPI networks can be viewed as maps where diseases can be identified with localized perturbation within a specific neighborhood (i.e., disease modules), DIAMOnD performs a systematic analysis of the human PPI network to uncover new disease-associated genes by exploiting the connectivity significance instead of connection density. The past few years have witnessed the increasing interest in understanding the molecular mechanism of post-transcriptional regulation with a special emphasis on non-coding RNAs since they are emerging as key regulators of many cellular processes in both physiological and pathological states. Recent findings show that coding genes are not the only targets that microRNAs interact with. In fact, there is a pool of different RNAs—including long non-coding RNAs (lncRNAs) —competing with each other to attract microRNAs for interactions, thus acting as competing endogenous RNAs (ceRNAs). The framework of regulatory networks provides a powerful tool to gather new insights into ceRNA regulatory mechanisms. Here, we describe a data-driven model recently developed to explore the lncRNA-associated ceRNA activity in breast invasive carcinoma. On the other hand, a very promising example of the co-expression network is the one implemented by the software SWIM (switch miner), which combines topological properties of correlation networks with gene expression data in order to identify a small pool of genes—called switch genes—critically associated with drastic changes in cell phenotype. Here, we describe SWIM tool along with its applications to cancer research and compare its predictions with DIAMOnD disease genes. Full article
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