A molecular systems architecture of neuromuscular junction in amyotrophic lateral sclerosis.

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
V A Shiva Ayyadurai, Prabhakar Deonikar, Roger D Kamm
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引用次数: 0

Abstract

A molecular systems architecture is presented for the neuromuscular junction (NMJ) in order to provide a framework for organizing complexity of biomolecular interactions in amyotrophic lateral sclerosis (ALS) using a systematic literature review process. ALS is a fatal motor neuron disease characterized by progressive degeneration of the upper and lower motor neurons that supply voluntary muscles. The neuromuscular junction contains cells such as upper and lower motor neurons, skeletal muscle cells, astrocytes, microglia, Schwann cells, and endothelial cells, which are implicated in pathogenesis of ALS. This molecular systems architecture provides a multi-layered understanding of the intra- and inter-cellular interactions in the ALS neuromuscular junction microenvironment, and may be utilized for target identification, discovery of single and combination therapeutics, and clinical strategies to treat ALS.

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来源期刊
NPJ Systems Biology and Applications
NPJ Systems Biology and Applications Mathematics-Applied Mathematics
CiteScore
5.80
自引率
0.00%
发文量
46
审稿时长
8 weeks
期刊介绍: npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.
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