Molecular communication networks: drug target scalability based on artificial intelligence prediction techniques

2021 ◽  
Vol 23 (3) ◽  
Author(s):  
A. R. Junejo ◽  
Xiang Li ◽  
Hina Madiha ◽  
Soha Mohamed
Keyword(s):  
Artificial Intelligence ◽  
Communication Networks ◽  
Drug Target ◽  
Molecular Communication ◽  
Prediction Techniques

Nanonetworks in Biomedical Applications

2019 ◽  
Vol 20 (8) ◽  
pp. 800-807 ◽  
Author(s):  
Jose Luis Marzo ◽  
Josep Miquel Jornet ◽  
Massimiliano Pierobon
Keyword(s):  
Communication Networks ◽  
Information Exchange ◽  
Biomedical Applications ◽  
Chemical Compounds ◽  
The Internet ◽  
Molecular Communication ◽  
Common Goal ◽  
Communication Paradigm ◽  
Communication Needs ◽  
Electromagnetic Signals

By interconnecting nanomachines and forming nanonetworks, the capacities of single nanomachines are expected to be enhanced, as the ensuing information exchange will allow them to cooperate towards a common goal. Nowadays, systems normally use electromagnetic signals to encode, send and receive information, however, in a novel communication paradigm, molecular transceivers, channel models or protocols use molecules. This article presents the current developments in nanomachines along with their future architecture to better understand nanonetwork scenarios in biomedical applications. Furthermore, to highlight the communication needs between nanomachines, two applications for nanonetworks are also presented: i) a new networking paradigm, called the Internet of NanoThings, that allows nanoscale devices to interconnect with existing communication networks, and ii) Molecular Communication, where the propagation of chemical compounds like drug particles, carry out the information exchange.

scholarly journals Network Amelioration, AI Automation and Future Integration in Wireless Networks

2021 ◽  
Vol 9 (8) ◽  
pp. 2607-2613
Author(s):  
Marzook Khatri
Keyword(s):  
Artificial Intelligence ◽  
Communication Networks ◽  
Mobile Networks ◽  
Network Virtualization ◽  
Mobile Network ◽  
Data Access ◽  
Detailed Comparison ◽  
Mobile Industry ◽  
Generation Network ◽  
Network Operations

Abstract: The deployment of 5G mobile communication networks is just getting started right now. There are numerous technologies available today, each capable of fulfilling activities such as enabling voice traffic via voice over IP (VoIP), providing broadband data access in mobile environments, and so on. However, there is a pressing need to implement technology that can bring all of these systems together into a single unified system. Because it is all about smoothly integrating terminals, networks, and applications, 8G presents a solution to this dilemma. In this work, an attempt is made to provide a study of various cellular technologies, such as 4G, 5G, 6G, 7G, and FG, as well as a detailed comparison between them. With the introduction of network virtualization and the implementation of 5G/IoT, mobile networks will become more complicated and offer more diverse services. This raises concerns about a considerable increase in the workload of network operations. Meanwhile, artificial intelligence (AI) is advancing rapidly and is projected to alleviate human resource shortages in a variety of industries. Similarly, the mobile industry is gaining traction in the application of artificial intelligence (AI) to network operations in order to improve the efficiency of mobile network operations. This paper will address the idea of using AI technology to network operations and will give various use examples to demonstrate that AI-driven network operations have a bright future. Keywords: 5G & 6G networks, Artificial Intelligence, Next generation network, Future Advancement.

scholarly journals Special Issue in Artificial Intelligence

2019 ◽  
Vol 30 (1) ◽  
pp. 7-8
Author(s):  
Dora Maria Ballesteros
Keyword(s):  
Artificial Intelligence ◽  
Communication Networks ◽  
Language Processing ◽  
Autonomous Systems ◽  
Big Data Analytics ◽  
Human Robot Interaction ◽  
Support Vector ◽  
Special Issue ◽  
Science And Engineering ◽  
Robot Interaction

Artificial intelligence (AI) is an interdisciplinary subject in science and engineering that makes it possible for machines to learn from data. Artificial Intelligence applications include prediction, recommendation, classification and recognition, object detection, natural language processing, autonomous systems, among others. The topics of the articles in this special issue include deep learning applied to medicine [1, 3], support vector machine applied to ecosystems [2], human-robot interaction [4], clustering in the identification of anomalous patterns in communication networks [5], expert systems for the simulation of natural disaster scenarios [6], real-time algorithms of artificial intelligence [7] and big data analytics for natural disasters [8].

scholarly journals A review on drug repurposing applicable to COVID-19

2020 ◽  
Author(s):  
Serena Dotolo ◽  
Anna Marabotti ◽  
Angelo Facchiano ◽  
Roberto Tagliaferri
Keyword(s):  
Artificial Intelligence ◽  
Drug Target ◽  
Lower Cost ◽  
Drug Repositioning ◽  
Drug Repurposing ◽  
Chemical Compounds ◽  
The Moment ◽  
New Applications ◽  
Novel Drug ◽  
Small Chemical

Abstract Drug repurposing involves the identification of new applications for existing drugs at a lower cost and in a shorter time. There are different computational drug-repurposing strategies and some of these approaches have been applied to the coronavirus disease 2019 (COVID-19) pandemic. Computational drug-repositioning approaches applied to COVID-19 can be broadly categorized into (i) network-based models, (ii) structure-based approaches and (iii) artificial intelligence (AI) approaches. Network-based approaches are divided into two categories: network-based clustering approaches and network-based propagation approaches. Both of them allowed to annotate some important patterns, to identify proteins that are functionally associated with COVID-19 and to discover novel drug–disease or drug–target relationships useful for new therapies. Structure-based approaches allowed to identify small chemical compounds able to bind macromolecular targets to evaluate how a chemical compound can interact with the biological counterpart, trying to find new applications for existing drugs. AI-based networks appear, at the moment, less relevant since they need more data for their application.

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