Article
Computer Science, Artificial Intelligence
Junzhong Ji, Hanghang Xiao, Cuicui Yang
Summary: This paper presents a novel hybrid approach of fireworks algorithm and differential evolution strategies for detecting functional modules in PPI networks, which performs well in terms of Recall, Sn, PPV, and ACC metrics. It is able to accurately detect functional modules and assist biologists in discovering novel biological insights.
APPLIED INTELLIGENCE
(2021)
Article
Biotechnology & Applied Microbiology
Xinguo Lu, Fang Liu, Qiumai Miao, Ping Liu, Yan Gao, Keren He
Summary: Our study aimed to reveal functional overlapping patterns in gene modules to elucidate regulatory relationships between overlapping genes and communities, as well as explore cancer formation and progression. We analyzed six cancer datasets and identified three types of gene functional modules for each cancer, with our method outperforming others in terms of identifying distinguishing communities and survival prognostics for patients. In conclusion, overlapping genes play a crucial role in constructing comprehensive carcinogenesis by establishing communication bridges between different specific functional groups.
Article
Genetics & Heredity
Yan Wang, Chen Qiong, Lili Yang, Sen Yang, Kai He, Xuping Xie
Summary: This paper proposes a novel overlapping community detection algorithm based on the neighboring local clustering coefficient (NLC), which improves seed selection accuracy, enhances community division accuracy, and optimizes overlapping structures. Experimental results show that the NLC algorithm improves the EQ and NMI values, demonstrating its effectiveness in detecting reasonable communities and identifying overlapping structures in networks.
FRONTIERS IN GENETICS
(2021)
Article
Biology
Youlin Zhan, Jiahan Liu, Min Wu, Chris Soon Heng Tan, Xiaoli Li, Le Ou-Yang
Summary: Detecting protein complexes is crucial for studying cellular organizations and functions. Existing computational methods for identifying protein complexes from protein-protein interaction (PPI) networks often ignore the signs of PPIs and do not consider joint clustering of multiple PPI networks. In this study, we propose a novel partially shared signed network clustering (PS-SNC) model that takes into account the signs of PPIs and can identify protein complexes from multiple state-specific signed PPI networks jointly.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Multidisciplinary Sciences
Simon Gosset, Annie Glatigny, Melina Gallopin, Zhou Yi, Marion Sale, Marie-Helene Mucchielli-Giorgi
Summary: Protein-protein interactions are crucial for cell processes and analyzing PPI networks can provide insights into protein functions. APPINetwork is a user-friendly open-source package for building and analyzing PPI networks from any species.
Review
Biochemistry & Molecular Biology
Sara Omranian, Zoran Nikoloski, Dominik G. Grimm
Summary: This article provides a systematic review of state-of-the-art algorithms for protein complex prediction from protein-protein interaction networks. The existing approaches are categorized and compared, and the performance of eighteen methods is analyzed on benchmark networks. The limitations, drawbacks, and potential solutions in the field are discussed, emphasizing future research efforts.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2022)
Article
Biochemistry & Molecular Biology
Sara Omranian, Angela Angeleska, Zoran Nikoloski
Summary: GCC-v is an efficient, parameter-free algorithm that accurately predicts protein complexes, outperforming twelve state-of-the-art methods in multiple experimental scenarios. Its robustness to network perturbations is demonstrated in pan-plant PPI networks and Arabidopsis thaliana, highlighting its potential for impact assessment on predicted protein complexes.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2021)
Article
Genetics & Heredity
Jia Liu, Huole Zhu, Jianfeng Qiu
Summary: In this paper, an effective disease module identification method IDMCSS is proposed, which adjusts human PPI networks to identify disease modules and predict drug intervention targets for asthma research.
FRONTIERS IN GENETICS
(2021)
Article
Computer Science, Artificial Intelligence
Chunying Li, Yong Tang, Zhikang Tang, Jinli Cao, Yanchun Zhang
Summary: The study introduces a novel community detection method - MELPA, which effectively reveals the community structure in complex networks through motif-based embedding label propagation algorithm. By integrating higher-order topology with lower-order connectivity features, reconstructing the network topology, and designing a new label update rule to overcome the randomness of label selection.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Article
Optics
Daeho Kim, Hoon Kim
Summary: We investigate the capacity-achieving symbol distributions for directly modulated laser (DML) and direct-detection (DD) systems utilizing probabilistic constellation shaped pulse amplitude modulation formats. We show that the probabilistic constellation shaping (PCS) technique marginally increases the capacity of DML-DD system when the optical modulation index (OMI) is less than 1. However, the PCS technique allows us to increase the OMI larger than 1 without clipping distortions. As a result, we can increase the capacity of DML-DD system by using the PCS technique in comparison with the uniformly distributed signals.
Article
Engineering, Multidisciplinary
Lun Hu, Jun Zhang, Xiangyu Pan, Xin Luo, Huaqiang Yuan
Summary: Protein complexes play a crucial role in cell processes, and detecting them accurately is essential for understanding cell organization and function. The proposed link-based clustering algorithm effectively identifies overlapping protein complexes by leveraging interactions, leading to improved detection accuracy compared to existing algorithms.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2021)
Article
Green & Sustainable Science & Technology
Xiaowen Wang, Xiaoying Shi, Yinliang Xu, Xinwei Shen
Summary: The increased power demand from electric vehicles presents new challenges for the distribution network. This paper proposes a mixed-integer non-linear programming (MINLP) model considering various network constraints to address the expansion planning of the distribution network with a high penetration level of EVs. The stochastic demands are handled through a set of scenarios and a distributed biased min-consensus algorithm is used to solve the MINLP model. Comparative tests on different scales of distribution networks demonstrate the effectiveness of the proposed approach, with a reduction in computation time of 42.46% compared to the traditional shortest path algorithm based approach.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2023)
Article
Green & Sustainable Science & Technology
Xiaowen Wang, Xiaoying Shi, Yinliang Xu, Xinwei Shen
Summary: The increased power demand caused by electric vehicles has posed new challenges for the distribution network. This paper presents a mixed-integer non-linear programming model considering various network constraints for the distribution network expansion planning under a high penetration level of EVs. A distributed biased min-consensus algorithm based approach is proposed to solve the model. Comparison tests on different scales of distribution networks validate the effectiveness of the proposed approach, with simulation results showing a 42.46% reduction in computation time compared to the traditional shortest path algorithm based approach.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2023)
Article
Genetics & Heredity
Yan Sun, Yijun Gu, Qianqian Ren, Yiting Li, Junliang Shang, Jin-Xing Liu, Boxin Guan
Summary: This paper proposes a module detection method called MDSN for identifying high-order epistatic interactions. By constructing an SNP network and using a node evaluation measure, it can effectively detect high-order interactions associated with diseases.
Article
Biochemical Research Methods
Sudipta Acharya, Laizhong Cui, Yi Pan
Summary: This study proposes an improved fused protein similarity measure called FuSim-II, which shows improved performance in finding protein similarity and detecting potential hub-proteins in protein-protein interaction networks.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2022)
