Biological Network Analysis and Synthesis for Symmetry

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Life Sciences".

Deadline for manuscript submissions: closed (30 September 2021) | Viewed by 5052

Special Issue Editors


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Guest Editor
Department of Life Science and Informatics, Maebashi Institute of Technology, Maebashi 371-0816, Japan
Interests: network science; systems biology; genetic regulatory network; ecosystem model

E-Mail Website
Guest Editor
Department of Life Science and Informatics, Maebashi Institute of Technology, Gunma, Japan
Interests: web intelligence, brain informatics, data mining and intelligent information systems

Special Issue Information

Dear Colleagues,

The biological phenomena related to the term symmetry—or asymmetry—should stimulate researcher interest. These phenomena are observed in various fields. Schrödinger suggested that a life system takes orderliness from its environment and sustains itself at a fairly high level of orderliness. First, the environment which is the world of nature itself changes irreversibly, paraphrased as asymmetrically in time. Topics of interest can be exemplified as the following. Plants exhibit a reversible or irreversible response according to environmental stresses. Signal transmission from an animal eye to a visual cortex eventually became symmetric during the process of evolution and is easily modified (i.e., becomes asymmetric) due to an environmental perturbation. Rooney et al. suggested structural asymmetry enhances the stability of diverse food webs. Gardner et al. developed a genetic toggle switch with a symmetric network structure in Escherichia coli. The last example demonstrates that symmetry should be a design target in synthetic biology.

The Guest Editor of this Special Issue invites research articles and reviews on these topics in the broad area of science and engineering, in which symmetry and asymmetry play a significant role, such as (though not restricted to) omics analysis for reversible or irreversible process in plant environmental stress response; symmetric properties in network development in neural systems; reversible or irreversible process models for biological regulatory systems (e.g., orderliness in a biological network); symmetric structure in genome sequences; synthetic biology for symmetric biological networks; symmetry or asymmetry in ecosystems; symmetric configuration and conformation in drug design; biomechanics and robotics for symmetrical movement. Theoretical or computational studies as well as method papers are also welcomed.

Prof. Dr. Katsumi Sakata
Prof. Dr. Ning Zhong
Guest Editors

Manuscript Submission Information

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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. Symmetry 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 2400 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

  • omics analysis
  • neural system
  • reversible or irreversible biological process
  • biological network
  • ecosystem model
  • symmetry in drug design
  • engineering for biological symmetry
  • brain informatics

Published Papers (1 paper)

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16 pages, 2535 KiB  
Article
EEG-Based EMG Estimation of Shoulder Joint for the Power Augmentation System of Upper Limbs
by Hongbo Liang, Yingxin Yu, Mika Mochida, Chang Liu, Naoya Ueda, Peirang Li and Chi Zhu
Symmetry 2020, 12(11), 1851; https://doi.org/10.3390/sym12111851 - 10 Nov 2020
Cited by 4 | Viewed by 4628
Abstract
Brain–Machine Interfaces (BMIs) have attracted much attention in recent decades, mainly for their applications involving severely disabled people. Recently, research has been directed at enhancing the ability of healthy people by connecting their brains to external devices. However, there are currently no successful [...] Read more.
Brain–Machine Interfaces (BMIs) have attracted much attention in recent decades, mainly for their applications involving severely disabled people. Recently, research has been directed at enhancing the ability of healthy people by connecting their brains to external devices. However, there are currently no successful research reports focused on robotic power augmentation using electroencephalography (EEG) signals for the shoulder joint. In this study, a method is proposed to estimate the shoulder’s electromyography (EMG) signals from EEG signals based on the concept of a virtual flexor–extensor muscle. In addition, the EMG signal of the deltoid muscle is used as the virtual EMG signal to establish the EMG estimation model and evaluate the experimental results. Thus, the shoulder’s power can be augmented by estimated virtual EMG signals for the people wearing an EMG-based power augmentation exoskeleton robot. The estimated EMG signal is expressed via a linear combination of the features of EEG signals extracted by Independent Component Analysis, Short-time Fourier Transform, and Principal Component Analysis. The proposed method was verified experimentally, and the average of the estimation correlation coefficient across different subjects was 0.78 (±0.037). These results demonstrate the feasibility and potential of using EEG signals to provide power augmentation through BMI technology. Full article
(This article belongs to the Special Issue Biological Network Analysis and Synthesis for Symmetry)
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