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495 results on '"Lei, Xiujuan"'

2. Automated Planning and Scheduling with Swarm Intelligence

Author

Cheng, Shi, Lu, Hui, Lei, Xiujuan, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Tan, Ying, editor, and Shi, Yuhui, editor

Published
2024
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3. Multi-filter Based Signed Graph Convolutional Networks for Predicting Interactions on Drug Networks

Author

Chen, Ming, Hu, Zitao, Lei, Xiujuan, Ji, Chunyan, Tong, Zhao, Pan, Yi, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Peng, Wei, editor, Cai, Zhipeng, editor, and Skums, Pavel, editor

Published
2024
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13. Graph Convolution Networks Using Message Passing and Multi-Source Similarity Features for Predicting circRNA-Disease Association

Author

Mudiyanselage, Thosini Bamunu, Lei, Xiujuan, Senanayake, Nipuna, Zhang, Yanqing, and Pan, Yi

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

Graphs can be used to effectively represent complex data structures. Learning these irregular data in graphs is challenging and still suffers from shallow learning. Applying deep learning on graphs has recently showed good performance in many applications in social analysis, bioinformatics etc. A message passing graph convolution network is such a powerful method which has expressive power to learn graph structures. Meanwhile, circRNA is a type of non-coding RNA which plays a critical role in human diseases. Identifying the associations between circRNAs and diseases is important to diagnosis and treatment of complex diseases. However, there are limited number of known associations between them and conducting biological experiments to identify new associations is time consuming and expensive. As a result, there is a need of building efficient and feasible computation methods to predict potential circRNA-disease associations. In this paper, we propose a novel graph convolution network framework to learn features from a graph built with multi-source similarity information to predict circRNA-disease associations. First we use multi-source information of circRNA similarity, disease and circRNA Gaussian Interaction Profile (GIP) kernel similarity to extract the features using first graph convolution. Then we predict disease associations for each circRNA with second graph convolution. Proposed framework with five-fold cross validation on various experiments shows promising results in predicting circRNA-disease association and outperforms other existing methods.

Published
2020

16. COVID-19 Detection Method Based on Attentional Mechanism and LSTM

Author

Zhu, Wanpeng, Lei, Xiujuan, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Tan, Ying, editor, Shi, Yuhui, editor, and Niu, Ben, editor

Published
2022
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21. Predicting Microbe-Disease Association via Tripartite Network and Relation Graph Convolutional Network

Author

Wang, Yueyue, Lei, Xiujuan, Pan, Yi, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Wei, Yanjie, editor, Li, Min, editor, Skums, Pavel, editor, and Cai, Zhipeng, editor

Published
2021
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25. Inferring Candidate CircRNA-Disease Associations by Bi-random Walk Based on CircRNA Regulatory Similarity

Author

Fan, Chunyan, Lei, Xiujuan, Tan, Ying, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Tan, Ying, editor, Shi, Yuhui, editor, and Tuba, Milan, editor

Published
2020
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30. Low-Temperature Regulates the Cell Structure and Chlorophyll in Addition to Cellulose Metabolism of Postharvest Red Toona sinensis Buds across Different Seasons.

Author

Zhao, Qian, Wang, Fu, Wang, Yifei, Zhong, Xiulai, Zhu, Shunhua, Zhang, Xinqi, Li, Shuyao, Lei, Xiujuan, Zang, Zhenyuan, Tan, Guofei, and Zhang, Jian

Subjects
TOONA, CELLULOSE, CHLOROPHYLL, SPRING, CELL anatomy, POSTHARVEST diseases, CITRUS greening disease
Abstract

Postharvest fibrosis and greening of Toona sinensis buds significantly affect their quality during storage. This study aimed to clarify the effects of low-temperature storage on postharvest red TSB quality harvested in different seasons. Red TSB samples were collected from Guizhou province, China, 21 days after the beginning of spring (Lichun), summer (Lixia), and autumn (Liqiu), and stored at 4 °C in dark conditions. We compared and analyzed the appearance, microstructure, chlorophyll and cellulose content, and expression levels of related genes across different seasons. The results indicated that TSB harvested in spring had a bright, purple-red color, whereas those harvested in summer and autumn were green. All samples lost water and darkened after 1 day of storage. Severe greening occurred in spring-harvested TSB within 3 days, a phenomenon not observed in summer and autumn samples. Microstructural analysis revealed that the cells in the palisade and spongy tissues of spring and autumn TSB settled closely during storage, while summer TSB cells remained loosely aligned. Xylem cells were smallest in spring-harvested TSB and largest in autumn. Prolonged storage led to thickening of the secondary cell walls and pith cell autolysis in the petioles, enlarging the cavity area. Chlorophyll content was higher in leaves than in petioles, while cellulose content was lower in petioles across all seasons. Both chlorophyll and cellulose content increased with storage time. Gene expression analysis showed season-dependent variations and significant increases in the expression of over half of the chlorophyll-related and cellulose-related genes during refrigeration, correlating with the observed changes in chlorophyll and cellulose content. This research provides valuable insights for improving postharvest storage and freshness preservation strategies for red TSB across different seasons. [ABSTRACT FROM AUTHOR]

Published
2024
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32. A New Method for Identification of Essential Proteins by Information Entropy of Protein Complex and Subcellular Localization

Author

Zhao, Jie, Lei, Xiujuan, Yang, Xiaoqin, Guo, Ling, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Tan, Ying, editor, Shi, Yuhui, editor, and Niu, Ben, editor

Published
2019
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33. Essential Protein Detection from Protein-Protein Interaction Networks Using Immune Algorithm

Author

Yang, Xiaoqin, Lei, Xiujuan, Wang, Jiayin, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Rojas, Ignacio, editor, Valenzuela, Olga, editor, Rojas, Fernando, editor, and Ortuño, Francisco, editor

Published
2019
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42. Mining Overlapping Protein Complexes in PPI Network Based on Granular Computation in Quotient Space

Author

Zhao, Jie, Lei, Xiujuan, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Huang, De-Shuang, editor, Bevilacqua, Vitoantonio, editor, Premaratne, Prashan, editor, and Gupta, Phalguni, editor

Published
2018
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43. ACO Based Core-Attachment Method to Detect Protein Complexes in Dynamic PPI Networks

Author

Liang, Jing, Lei, Xiujuan, Guo, Ling, Tan, Ying, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Tan, Ying, editor, Shi, Yuhui, editor, and Tang, Qirong, editor

Published
2018
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50. Predicting Essential Proteins Based on Gene Expression Data, Subcellular Localization and PPI Data

Author

Lei, Xiujuan, Wang, Siguo, Pan, Linqiang, Barbosa, Simone Diniz Junqueira, Series editor, Chen, Phoebe, Series editor, Filipe, Joaquim, Series editor, Kotenko, Igor, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Yuan, Junsong, Series editor, Zhou, Lizhu, Series editor, He, Cheng, editor, Mo, Hongwei, editor, Pan, Linqiang, editor, and Zhao, Yuxin, editor

Published
2017
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