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: 1 October 2018

Special Issue Editor

Guest Editor
Dr. Frank Kramer

Department of Medical Statistics, University Medical Center Göttingen, Humboldtallee 32, 37099 Göttingen, 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.


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

Published Papers

This special issue is now open for submission, see below for planned papers.

Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Tentative Title: Network-based approach to explore complex biological systems towards network medicine

Authors: Giulia Fiscon 1,2, Federica Conte 1,2, Lorenzo Farina 3, Paola Paci 1,2

1 Institute for Systems Analysis and Computer Science Antonio Ruberti, National Research Council, 00185 Rome, Italy.

2 SysBio Centre for Systems Biology, 20126 Milano, Italy.

3 Department of Computer, Control, and Management Engineering Antonio Ruberti, Sapienza University of 00185 Rome, Italy.

Tentative Abstract: Network medicine relies on different types of networks: from molecular level of protein-protein interactions to gene regulatory network and correlation studies of gene expression. Among the regulatory networks, the past few years have witnessed the increasing interest on the regulatory mechanism of some long noncoding RNA (lncRNA) that can act as competing endogenous RNAs (ceRNAs) for messenger RNAs (mRNAs) by sharing the binding site for microRNAs (miRNAs).

     We discuss a data-driven model developed to explore the lncRNA-associated ceRNA activity in breast invasive carcinoma [1]. The authors built normal and cancer networks of miRNA-mediated sponge interactions (MMI-networks and highlighted a marked rewiring in the ceRNA program between normal and pathological breast tissue. At the heart of this phenomenon is the widely studied oncogene PVT1 that switches from being the first hub in the normal MMI-network to fall outside the list of nodes of the cancer network. Interestingly, PVT1 revealed a net binding preference towards the mir-200 family as the bone of contention with its rival mRNAs known to be related to the cancer development and progression (e.g. GATA3, CDH1, TP53, TP63, TP73, RUNX1, and RUNX3). The authors sought the rationale behind the withdrawal in breast cancer tissues of the PVT1 ceRNA activity [2], betting on the hypothesis of a mechanism of titration, i.e. large variations in the ceRNAs expression levels can overcome, or relive, the repression of miRNA on its competitors, or similar over-expression of miRNA can abolish the competition between the two transcripts.

     On the other hand, a very promising example of co-expression network is the one implement by the software SWIM [3], 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. SWIM has been successfully applied in viticulture [4], leading to the identification of key genes in the process of grapevine ripening, as well as in network medicine [3]. In particular, from a multi-cancer analysis SWIM identifies 100 common switch genes, which are implicated in cell cycle regulation, that could be negative regulators of cancer metabolism, and could in turn be controlled by growth factors such as E2F and NFY.


[1] Paci, P., Colombo, T., Farina, L. Computational analysis identifies a sponge interaction network between long non-coding RNAs and messenger RNAs in human breast cancer. BMC Syst. Biol 2014, 83.

[2] Conte, F., Fiscon, G., Chiara, M., Colombo, T., Farina, L., and Paci, P. Role of the long non-coding RNA PVT1 in the dysregulation of the ceRNA-ceRNA network in human breast cancer. PloS One 2017, 12.

[3] Paci, P., Colombo, T. Fiscon, G., Gurtner, A. Pavesi, G., Farina, L. SWIM: A computational tool to unveiling crucial nodes in complex biological networks. Sci.Rep. 2017, 7.

[4] Palumbo, M.C., Zenoni, S., Fasoli, M., Massonnet, M., Farina, L., Castiglione, F., Pezzotti, M., Paci, P. Integrated network analysis identifies fight-club nodes as a class of hubs encompassing key putative switch genes that induce major transcriptome reprogramming during grapevine development. Plant Cell. 2014, 26, 4617–4635.

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