Intelligent Computing Theories and Application: 16th International Conference, ICIC 2020, Bari, Italy, October 2–5, 2020, Proceedings, Part II | SpringerLink
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Intelligent Computing Theories and Application

16th International Conference, ICIC 2020, Bari, Italy, October 2–5, 2020, Proceedings, Part II

  • Conference proceedings
  • © 2020

Overview

Editors:
  1. De-Shuang Huang

    1. Institute of Machine Learning and Systems Biology, Tongji University, Shanghai, China

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  2. Kang-Hyun Jo

    1. School of Electrical Engineering, University of Ulsan, Ulsan, Korea (Republic of)

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12464)

Part of the book sub series: Information Systems and Applications, incl. Internet/Web, and HCI (LNISA)

Included in the following conference series:

Conference proceedings info: ICIC 2020.

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About this book

This two-volume set of LNCS 12463 and LNCS 12464 constitutes - in conjunction with the volume LNAI 12465 - the refereed proceedings of the 16th International Conference on Intelligent Computing, ICIC 2020, held in Bari, Italy, in October 2020. The 162 full papers of the three proceedings volumes were carefully reviewed and selected from 457 submissions.

The ICIC theme unifies the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. The theme for this conference is “Advanced Intelligent Computing Methodologies and Applications.” Papers related to this theme are especially solicited, addressing theories, methodologies, and applications in science and technology.

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Table of contents (54 papers)

  1. Front Matter

    Pages i-xxii
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  2. Gene Expression Array Analysis

    1. Front Matter

      Pages 1-1
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    2. A Novel Clustering-Framework of Gene Expression Data Based on the Combination Between Deep Learning and Self-organizing Map

      • Yan Cui, Huacheng Gao, Rui Zhang, Yuanyuan Lu, Yuan Xue, Chun-Hou Zheng
      Pages 3-13

    3. Tumor Gene Selection and Prediction via Supervised Correlation Analysis Based F-Score Method

      • Jia-Jun Cheng, Bo Li
      Pages 14-20

    4. A Machine Learning Based Method to Identify Differentially Expressed Genes

      • Bolin Chen, Li Gao, Xuequn Shang
      Pages 21-31

    5. Multi-omics Classification on Kidney Samples Exploiting Uncertainty-Aware Models

      • Marta Lovino, Gianpaolo Bontempo, Giansalvo Cirrincione, Elisa Ficarra
      Pages 32-42

  3. Gene Regulation Modeling and Analysis

    1. Front Matter

      Pages 43-43
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    2. Inference Method for Reconstructing Regulatory Networks Using Statistical Path-Consistency Algorithm and Mutual Information

      • Yan Yan, Xinan Zhang, Tianhai Tian
      Pages 45-56

    3. Exploring lncRNA-MRNA Regulatory Modules Based on lncRNA Similarity in Breast Cancer

      • Lei Tian, Shu-Lin Wang, Xing Zhong
      Pages 57-66

    4. Three-Layer Dynamic Transfer Learning Language Model for E. Coli Promoter Classification

      • Ying He, Zhen Shen, Qinhu Zhang, Siguo Wang, Changan Yuan, Xiao Qin et al.
      Pages 67-78

    5. A New Method Combining DNA Shape Features to Improve the Prediction Accuracy of Transcription Factor Binding Sites

      • Siguo Wang, Zhen Shen, Ying He, Qinhu Zhang, Changan Yuan, Xiao Qin et al.
      Pages 79-89

    6. Predicting in-Vitro Transcription Factor Binding Sites with Deep Embedding Convolution Network

      • Yindong Zhang, Qinhu Zhang, Changan Yuan, Xiao Qin, Hongjie Wu, Xingming Zhao
      Pages 90-100

  4. Protein-Protein Interaction Prediction

    1. Front Matter

      Pages 101-101
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    2. Prediction of Membrane Protein Interaction Based on Deep Residual Learning

      • Tengsheng Jiang, Hongjie Wu, Yuhui Chen, Haiou Li, Jin Qiu, Weizhong Lu et al.
      Pages 103-108

    3. GCNSP: A Novel Prediction Method of Self-Interacting Proteins Based on Graph Convolutional Networks

      • Lei Wang, Zhu-Hong You, Xin Yan, Kai Zheng, Zheng-Wei Li
      Pages 109-120

    4. Predicting Protein-Protein Interactions from Protein Sequence Using Locality Preserving Projections and Rotation Forest

      • Xinke Zhan, Zhuhong You, Changqing Yu, Jie Pan, Ruiyang Li
      Pages 121-131

    5. Predicting Protein-Protein Interactions from Protein Sequence Information Using Dual-Tree Complex Wavelet Transform

      • Jie Pan, Zhu-Hong You, Chang-Qing Yu, Li-Ping Li, Xin-ke Zhan
      Pages 132-142

  5. Biomarker Discovery and Detection

    1. Front Matter

      Pages 143-143
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    2. Biomarkers Selection of Abnormal Functional Connections in Schizophrenia with \( {\mathbf{\ell }}_{{{\mathbf{2,1 - 2}}}} \)-Norm Based Sparse Regularization Feature Selection Method

      • Na Gao, Chen Qiao, Shun Qi, Kai Ren, Jian Chen, Hanfeng Fang
      Pages 145-158

  6. Systems Biology

    1. Front Matter

      Pages 159-159
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Other volumes

  1. Intelligent Computing Theories and Application

  2. Intelligent Computing Theories and Application

  3. Intelligent Computing Methodologies

Editors and Affiliations

  • Institute of Machine Learning and Systems Biology, Tongji University, Shanghai, China

    De-Shuang Huang

  • School of Electrical Engineering, University of Ulsan, Ulsan, Korea (Republic of)

    Kang-Hyun Jo

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