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Special Issue "Complex Networks and Machine Learning: From Molecular to Social Sciences"
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: closed (30 November 2018) | Viewed by 43751
Special Issue Editors
E-Mail Website1 Website2
2. IKERBASQUE, Basque Foundation for Science, 48011 Bilbao, Biscay, Spain
Interests: cheminformatics; bioinformatics; machine learning; complex networks; computational nanoscience
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2. Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade do Porto, Praça de Gomes Teixeira, 4099-002, Portugal
3. Center for Computer Science (CCS), University of Miami, Rosenstiel Medical Science Building (RMSB), 1600 NW 10th Avenue, Miami, FL 33136, USA
Special Issue Information
Complex networks and machine learning methods are useful for the study of complex systems in applied sciences. On one hand, we can use complex networks to represent and study the structure of complex systems in applied sciences. The systems susceptible to study with this approach range from small chemical compounds, proteins, metabolic pathways, and other molecular systems, to brain cortex, ecosystems, internet, market, social networks, etc.
On the other hand, computational techniques coming from machine learning (ML) are gaining importance in the analysis of numerical data related to complex systems. Some ML methods include artificial neural networks, support vector machines, etc. In addition, we can use the numerical parameters of complex networks and other input variables to train ML algorithms in order to predict the properties of these systems.
As a result of this reflection, we decided to launch one Special Issue focused on the benefits of using ML and complex network analysis (in combination or separately) to study complex systems in applied sciences. The topic of the issue is: Complex Networks and Machine Learning in Applied Sciences. Accepted papers will be published in the journal Applied Science, which is an open access publication journal of MDPI (https://www.mdpi.com/journal/applsci). The Issue also includes full versions of proceedings published in MOL2NET International Conference Series on Multidisciplinary Sciences, 2017 (closed) and 2018 (open), with official website at SciForum platform. The Sciforum platform is supported by MDPI editorial. Last year (2017), the conference received more than 250 communications from more than 450 authors worldwide. These communications have been presented online and/or in person in more than 10 associated specialized workshops held at universities in the USA, Spain, Portugal, Brazil, etc. MOL2NET 2018 link: http://sciforum.net/conference/mol2net-04.
Prof. Dr. Humbert González-Díaz
Prof. Dr. Maykel Cruz-Monteagudo
Prof. Dr. Terace Fletcher
Prof. Dr. David Quesada
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 submissions that pass pre-check are 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. Applied Sciences is an international peer-reviewed open access semimonthly 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 2300 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.
- complex networks in applied sciences
- proteome analysis and protein interaction networks (PINs)
- complex networks and systems biology
- metabolic pathway networks
- brain networks
- social, financial, and legal networks
- machine learning in applied sciences
- machine learning in cheminformatics
- machine learning in bioinformatics
- machine learning in biomedical engineering
- artificial neural networks
- support vector machines
- systems biology
- deep learning