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Practical Aspects of Molecular Communications
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Practical Aspects of Molecular Communications

A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Bioorganic Chemistry".

Deadline for manuscript submissions: closed (31 July 2022) | Viewed by 7899

Special Issue Editors

Dr. Murat Kuscu

E-Mail Website
Guest Editor
Department of Electrical and Electronics Engineering, Koc University, 34450 Istanbul, Turkey
Interests: internet of bio-nano things; molecular information and communication technologies; graphene and related two-dimensional nanomaterials; biosensors; bio-cyber interfaces; microfluidic sensors
Dr. Ergin Dinc

E-Mail Website
Guest Editor
Battcock Centre for Experimental Astrophysics, Cavendish Laboratory, University of Cambridge, 19 JJ Thomson Avenue, Cambridge CB3 0HE, UK
Interests: channel modelling; massive MIMO; signal processing; Internet of Things; wireless power transfer; energy harvesting
Special Issues, Collections and Topics in MDPI journals
Dr. Bige Deniz Unluturk

E-Mail Website
Guest Editor
Institute of Quantitative Health Science and Engineering, Michigan State University, 775 Woodlot Dr, East Lansing, MI 48824, USA
Interests: molecular communication; internet of bio-nano things; biological communication; networking
Dr. Michael Barros

E-Mail Website
Guest Editor
School of Computer Science and Electronic Engineering (CSEE), University of Essex, Colchester CO4 3SQ, UK
Interests: molecular communications; biocomputing; biocyber interfaces
Special Issues, Collections and Topics in MDPI journals
Dr. Sasitharan Balasubramaniam

E-Mail Website
Guest Editor
TSSG/Walton Institute, Waterford Institute of Technology, Cork Rd, Waterford, Ireland
Interests: molecular communications and nano networks; bacterial nano networks; internet of bio-nanonetworks
Dr. Kerstin Lenk

E-Mail Website
Guest Editor
Institute of Neural Engineering, Graz University of Technology, 8010 Graz, Austria
Interests: computational neuroscience; biophysical modeling; molecular communication

Special Issue Information

Dear Colleagues,

The Internet of Bio-Nano Things (IoBNT) is an emerging technology that aims to extend our connectivity to nanoscale and biological environments with collaborative nanonetworks of artificial nanomachines and biological entities integrated into the Internet infrastructure. To enable the IoBNT and its groundbreaking applications, such as continuous intrabody health monitoring, it is imperative to devise low-complexity nanoscale communication techniques suitable for the envisioned nanomachines of simple architectures. The most promising communication technology for realizing the IoBNT is Molecular Communications (MC), as it ubiquitously manifests itself in many complex biological systems in the Universe, and thus, stands as one of the most common communication modalities, optimized from many aspects as a result of billions of years of evolutionary advancement.

Making use of this naturally existing technology requires understanding its foundations through our existing modeling and analysis tools. This quest, which started almost 15 years ago, has received increasing attention from ICT researchers, which have been overly inspired by conventional electromagnetic communication technologies in their approach to this radically different paradigm. These theoretical approaches, however, have not always come with sufficient physical relevance. Currently, this emerging field has come to a critical turning point, as many researchers have started to report on initial MC experiments following different approaches and using different materials, while consistently pointing out a discrepancy between the obtained experimental results and the past theoretical work. This reveals the need to rethink the previous efforts and come up with new interdisciplinary strategies, thus building practical MC techniques and developing feasible MC system components, experimental testbeds, and prototypes in order to close the gap between theory and practice, and expedite the transfer of this emerging technology to the market.

Among the challenges stated above, this Special Issue is particularly focused on the practical aspects of MC. Therefore, we are calling for technical papers that report on new research with the potential to move this field forward towards its practical application, as well as surveys/tutorials focusing on the practical challenges of MC research. Hence, its scope encompasses a wide range of interdisciplinary research topics, with some examples listed as follows: 

  • The physical design, modeling, and implementation of MC system components (e.g., transmitter, receiver, channel);
  • The design and implementation of MC testbeds;
  • Practical and low-complexity MC methods (e.g., modulation, detection, channel estimation, synchronization, coding methods);
  • The testing and validation of MC transceiver/channel models and MC methods;
  • Applications of microfluidics, biosensors, and nanomaterials for MC system design;
  • Bio-cyber interfaces between MC networks and conventional macroscale networks;
  • Synthetic biology-based MC transceiver architectures;
  • Optimization of ligand-receptor interactions for MC;
  • Biocompatibility and co-existence challenges;
  • Energy harvesting and power transfer techniques for MC networks;

The design and demonstration of MC applications (e.g., those in healthcare, agriculture, biocomputing).

Dr. Murat Kuscu
Dr. Ergin Dinc
Dr. Bige Deniz Unluturk
Dr. Michael Barros
Dr. Sasitharan Balasubramaniam
Dr. Kerstin Lenk
Guest Editors

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. Molecules 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 2700 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

  • molecular communications
  • internet of bio-nano Things
  • nanonetworks
  • biosensors
  • nanomaterials
  • microfluidics
  • ligand-receptor interactions
  • bio-cyber interfaces

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (3 papers)

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Research

13 pages, 2383 KiB  
Article
Effects of Environmental and Electric Perturbations on the pKa of Thioredoxin Cysteine 35: A Computational Study
by Valeria D’Annibale, Donatella Fracassi, Paolo Marracino, Guglielmo D’Inzeo and Marco D’Abramo
Molecules 2022, 27(19), 6454; https://doi.org/10.3390/molecules27196454 - 30 Sep 2022
Cited by 1 | Viewed by 1562
Abstract
Here we present a theoretical-computational study dealing with the evaluation of the pKa of the Cysteine residues in Thioredoxin (TRX) and in its complex with the Thioredoxin-interacting protein (TXNIP). The free energy differences between the anionic and neutral form of the Cysteine 32 [...] Read more.
Here we present a theoretical-computational study dealing with the evaluation of the pKa of the Cysteine residues in Thioredoxin (TRX) and in its complex with the Thioredoxin-interacting protein (TXNIP). The free energy differences between the anionic and neutral form of the Cysteine 32 and 35 have been evaluated by means of the Perturbed Matrix Method with classical perturbations due to both the environment and an exogenous electric field as provided by Molecular Dynamics (MD) simulations. The evaluation of the free energies allowed us to show that the effect of the perturbing terms is to lower the pKa of Cysteine 32 and Cysteine 35 with respect to the free amino-acid. On the other hand, in the complex TRX-TXNIP, our data show an enhanced stabilization of the neutral reduced form of Cys 35. These results suggest that external electric stimuli higher than 0.02 V/nm can modulate the Cysteine pKa, which can be connected to the tight regulation of the TRX acting as an antioxidant agent. Full article
(This article belongs to the Special Issue Practical Aspects of Molecular Communications)
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23 pages, 2884 KiB  
Article
Objective Supervised Machine Learning-Based Classification and Inference of Biological Neuronal Networks
by Michael Taynnan Barros, Harun Siljak, Peter Mullen, Constantinos Papadias, Jari Hyttinen and Nicola Marchetti
Molecules 2022, 27(19), 6256; https://doi.org/10.3390/molecules27196256 - 23 Sep 2022
Cited by 4 | Viewed by 2417
Abstract
The classification of biological neuron types and networks poses challenges to the full understanding of the human brain’s organisation and functioning. In this paper, we develop a novel objective classification model of biological neuronal morphology and electrical types and their networks, based on [...] Read more.
The classification of biological neuron types and networks poses challenges to the full understanding of the human brain’s organisation and functioning. In this paper, we develop a novel objective classification model of biological neuronal morphology and electrical types and their networks, based on the attributes of neuronal communication using supervised machine learning solutions. This presents advantages compared to the existing approaches in neuroinformatics since the data related to mutual information or delay between neurons obtained from spike trains are more abundant than conventional morphological data. We constructed two open-access computational platforms of various neuronal circuits from the Blue Brain Project realistic models, named Neurpy and Neurgen. Then, we investigated how we could perform network tomography with cortical neuronal circuits for the morphological, topological and electrical classification of neurons. We extracted the simulated data of 10,000 network topology combinations with five layers, 25 morphological type (m-type) cells, and 14 electrical type (e-type) cells. We applied the data to several different classifiers (including Support Vector Machine (SVM), Decision Trees, Random Forest, and Artificial Neural Networks). We achieved accuracies of up to 70%, and the inference of biological network structures using network tomography reached up to 65% of accuracy. Objective classification of biological networks can be achieved with cascaded machine learning methods using neuron communication data. SVM methods seem to perform better amongst used techniques. Our research not only contributes to existing classification efforts but sets the road-map for future usage of brain–machine interfaces towards an in vivo objective classification of neurons as a sensing mechanism of the brain’s structure. Full article
(This article belongs to the Special Issue Practical Aspects of Molecular Communications)
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19 pages, 1413 KiB  
Article
What Is the Trait d’Union between Retroactivity and Molecular Communication Performance Limits?
by Francesca Ratti, Maurizio Magarini and Domitilla Del Vecchio
Molecules 2022, 27(10), 3130; https://doi.org/10.3390/molecules27103130 - 13 May 2022
Cited by 1 | Viewed by 1971
Abstract
Information exchange is a critical process in all communication systems, including biological ones. Retroactivity describes the load that downstream modules apply to their upstream systems in biological circuits. The motivation behind this work is that of integrating retroactivity, a concept proper of biochemical [...] Read more.
Information exchange is a critical process in all communication systems, including biological ones. Retroactivity describes the load that downstream modules apply to their upstream systems in biological circuits. The motivation behind this work is that of integrating retroactivity, a concept proper of biochemical circuits, with the metrics defined in Information Theory and Digital Communications. This paper focuses on studying the impact of retroactivity on different biological signaling system models, which present analogies with well-known telecommunication systems. The mathematical analysis is performed both in the high and low molecular counts regime, by mean of the Chemical Master Equation and the Linear Noise Approximation, respectively. The main goal of this work is to provide analytical tools to maximize the reliable information exchange across different biomolecular circuit models. Results highlight how, in general, retroactivity harms communication performance. This negative effect can be mitigated by adding to the signaling circuit an independent upstream system that connects with the same pool of downstream circuits. Full article
(This article belongs to the Special Issue Practical Aspects of Molecular Communications)
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