Special Issue "Metabolic Modeling of the Human Nasal Microbiome"
Deadline for manuscript submissions: 15 February 2022.
2. Department of Computer Science, University of Tübingen, 72076 Tübingen, Germany
3. Cluster of Excellence ‘Controlling Microbes to Fight Infections,’ University of Tübingen, Tübingen, Germany
4. German Center for Infection Research (DZIF), Partner Site Tübingen, Tübingen, Germany
Interests: systems biology; genome-scale metabolic modeling; microbial interaction; infectious diseases; standardization
We are pleased to announce a Special Issue of the journal Metabolites dedicated to metabolic modeling of the human nasal microbiome. As the bridge between the environment and the internal body, the nose plays a vital role in the defense against various infectious diseases: Various commensal and pathogenic bacterial species plus viruses recurringly colonize highly diverse habitats within the nostrils. While antiviral treatments may not even always be available, the spread of antibiotic resistance leads to a situation in which many harmful pathogens no longer reliably respond to antibacterial medication. At the same time, a complex interplay of commensal bacterial, human body cells, and further nasal inhabitants may reduce the risk for severe infections and possibly enable alternative treatment strategies. This Special Issue collects studies that investigate systems biology modeling approaches of the human nasal microbiome. Contributions may focus on the biology of the nasal environment and colonization, computational reconstructions of individual nasal inhabitants, their interplay, or interactions with the human host from a physiological or computational viewpoint. Additionally, larger microbial communities, such as multispecies exchange and their interaction with the host, and possible intervention measures against pathogens, or general methods for modeling such communities, are welcome. Modeling techniques may include but are not limited to stochastic systems, partial or ordinary differential equation systems, constraint-based modeling approaches, logical models, population dynamics, or agent-based systems. We also encourage the submission of graphical forms of knowledge representations and big data visualization or novel software solutions in this context. Papers will be published as accepted and assembled in the Special Issue appearing in 2022.
Prof. Dr. Andreas Dräger
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. Metabolites 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 1800 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.
- systems biology
- nasal infections
- microbial and host interaction
- antibiotics resistance
- quorum sensing
- population dynamics
- metabolic modeling
- big data visualization
- biological network visualization
- innovative therapeutics/novel approaches for intervention
- human nasal microbiome
- microbial interactions
- community modeling