Optimisation of sparse deep autoencoders for dynamic network embedding by Huimei Tang, Yutao Zhang, Lijia Ma, Qiuzhen Lin, Liping Huang, Jianqiang Li, Maoguo Gong

“…Abstract Network embedding (NE) tries to learn the potential properties of complex networks represented in a low‐dimensional feature space. …”
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Identifying optimal substrate classes of membrane transporters. by Andreas Denger, Volkhard Helms

“…Protein datasets are frequently annotated with thousands of molecular functions that form complex networks, often with partial or full redundancy and hierarchical relationships. …”
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An Effective Approach for Modular Community Detection in Bipartite Network Based on Integrating Rider with Harris Hawks Optimization Algorithms by Bader Fahad Alkhamees, Mogeeb A. A. Mosleh, Hussain AlSalman, Muhammad Azeem Akbar

“…The strenuous mining and arduous discovery of the concealed community structure in complex networks has received tremendous attention by the research community and is a trending domain in the multifaceted network as it not only reveals details about the hierarchical structure of multifaceted network but also assists in better understanding of the core functions of the network and subsequently information recommendation. …”
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Multi-query based key node mining algorithm for social networks by Guodong XIN, Tengwei ZHU, Junheng HUANG, Jiayang Wei, Runxuan Liu, Wei WANG

“…Mining key nodes in complex networks has been a hotly debated topic as it played an important role in solving real-world problems.However, the existing key node mining algorithms focused on finding key nodes from a global perspective.This approach became problematic for large-scale social networks due to the unacceptable storage and computing resource overhead and the inability to utilize known query node information.A key node mining algorithm based on multiple query nodes was proposed to address the issue of key suspect mining.In this method, the known suspects were treated as query nodes, and the local topology was extracted.By calculating the critical degree of non-query nodes in the local topology, nodes with higher critical degrees were selected for recommendation.Aiming to overcome the high computational complexity of key node mining and the difficulty of effectively utilizing known query node information in existing methods, a two-stage key node mining algorithm based on multi-query was proposed to integrate the local topology information and the global node aggregation feature information of multiple query nodes.It reduced the calculation range from global to local and quantified the criticality of related nodes.Specifically, the local topology of multiple query nodes was obtained using the random walk algorithm with restart strategy.An unsupervised graph neural network model was constructed based on the graphsage model to obtain the embedding vector of nodes.The model combined the unique characteristics of nodes with the aggregation characteristics of neighbors to generate the embedding vector, providing input for similarity calculations in the algorithm framework.Finally, the criticality of nodes in the local topology was measured based on their similarity to the features of the query nodes.Experimental results demonstrated that the proposed algorithm outperformed traditional key node mining algorithms in terms of time efficiency and result effectiveness.…”
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Extracting Skeleton of the Global Terrorism Network Based on m-Modified Topology Potential by Shuliang Wang, Kanokwan Malang, Hanning Yuan, Aniwat Phaphuangwittayakul, Yuanyuan Lv, Matthew David Lowdermilk, Jing Geng

“…Skeleton network extraction is a crucial context in studying the core structure and essential information on complex networks. The objective of this paper is to introduce the novel network extraction method, namely, TPKS-skeleton, for investigating the global terrorism network. …”
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Cohort and Rhyme Priming Emerge from the Multiplex Network Structure of the Mental Lexicon by Massimo Stella

“…Complex networks recently opened new ways for investigating how language use is influenced by the mental representation of word similarities. …”
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A distinct double-ring LH1–LH2 photocomplex from an extremophilic phototroph by Kazutoshi Tani, Kenji V. P. Nagashima, Risa Kojima, Masaharu Kondo, Ryo Kanno, Issei Satoh, Mai Kawakami, Naho Hiwatashi, Kazuna Nakata, Sakiko Nagashima, Kazuhito Inoue, Yugo Isawa, Ryoga Morishita, Shinichi Takaichi, Endang R. Purba, Malgorzata Hall, Long-Jiang Yu, Michael T. Madigan, Akira Mizoguchi, Bruno M. Humbel, Yukihiro Kimura, Yutaka Nagasawa, Takehisa Dewa, Zheng-Yu Wang-Otomo

“…The LH2 ring is composed of 9 αβ-subunits, and the BChl a molecules in the co-complex form extensive intra- and inter-complex networks to allow near 100% efficiency of energy transfer to its surrounding LH1. …”
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Efficiency enhancement in main path extraction in mRNA vaccine field: A novel approach leveraging intermediate patents, with shielding origin and terminus patent edges by Ting Zhang, Zhongquan Jian, Juan Chen, Dongzi Xu, Xiaoyi Yang, Yan Lu, Shu Yan, Lizi Pan, Qingqiang Wu, Zhaolian Ouyang

“…This study significantly advances the methodology of MPA, with the innovative shielding technique offering a fresh perspective for navigating complex networks and providing a deeper understanding of technological development in the mRNA vaccine domain.…”
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Multiplex Community Detection in Social Networks Using a Chaos-Based Hybrid Evolutionary Approach by Bagher Zarei, Bahman Arasteh, Mehdi Asadi, Vahid Majidnezhad, Saeid Taghavi Afshord, Asgarali Bouyer

“…An essential task within network analysis is deciphering the structure of complex networks including technological, informational, biological, and social networks. …”
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The interplay of sex and genotype in disease associations: a comprehensive network analysis in the UK Biobank by Vivek Sriram, Jakob Woerner, Yong-Yeol Ahn, Dokyoon Kim

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Transcriptional Systems Vaccinology Approaches for Vaccine Adjuvant Profiling by Diogo Pellegrina, Heather L. Wilson, George K. Mutwiri, Mohamed Helmy

“…While other molecular biology methods can verify if one or few genes are differentially regulated in response to vaccination, systems vaccinology provides a more comprehensive picture by simultaneously identifying the hundreds or thousands of genes that interact with complex networks in response to a vaccine. Transcriptomics tools such as RNA sequencing (RNA-Seq) allow us to simultaneously quantify the expression of practically all expressed genes, making it possible to make inferences that are only possible when considering the system as a whole. …”
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