Modelling Biological Systems for Digitalisation of Bioindustries
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Biosciences and Bioengineering".
Deadline for manuscript submissions: closed (28 February 2021) | Viewed by 289
Special Issue Editors
Interests: modelling of biological systems; biotechnology; digital bioprocessing; biochemical engineering
Interests: bioinformatics; gene and genome evolution; microbiology; post-translational regulation, molecular networks
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Resource-effective and sustainable manufacturing initiatives in bioindustries have necessitated the adoption of systematic approaches towards understanding the biological systems utilised, as well as the processes employed. This endeavour, reinforced by digitalisation, will lead to achieving fully understood and automated processes in bioindustries where sophisticated control strategies can be implemented to improve all aspects of biomanufacturing. Model-based investigation of biological systems is a crucial aspect of this initiative. Scientific efforts and advances in the field vary extensively across practices, from the utilisation of hypothesis-driven reconstruction of structured formal models to exploratory data-driven modelling that relies on learning algorithms.
In this Special Issue, we invite submissions exploring the utilisation of formal or data-driven approaches to model biological systems in a variety of applications related to or implicated in bioindustries. Contributions can focus on but are not limited to network-based analysis, formal modelling, or ML-based predictive modelling of biological phenomena, modelling of mono-cultures or mixed-species cultures and their associated bioprocesses, or novel approaches in control of these systems that are directly relevant for bioindustries. Computational or bioinformatics tools that enhance our understanding of cellular and biological phenomena and facilitate their utilisation in bioindutries including those relevant for strain design and selection, as well as survey papers and reviews related to these areas are also welcomed.
Dr. Duygu DikiciogluProf. Dr. Grigoris Amoutzias
Guest Editors
Manuscript Submission Information
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Keywords
- digital bioprocessing
- mathematical modelling of biological systems and bioprocesses
- formal models in biotechnology
- machine learning in bioprocess design and control
- data-driven bioprocess modelling and control
- network models of biosystems and bioprocesses
