ICIC 2020 Special Session

The ICIC 2020 Program Committee is inviting proposals for special sessions to be held during the conference (http://ic-ic.tongji.edu.cn/2020/index.htm), taking place on October 2-5, 2020, in Bari,Italy.

Each special session proposal should be well motivated and should consist of 8 to 12 papers. Each paper must have the title, authors with e-mails/web sites, and as detailed an abstract as possible. The special session organizer(s) contact information should also be included. All special session organizers must obtain firm commitments from their special session presenters and authors to submit papers in a timely fashion (if the special session is accepted) and, particularly, present them at the ICIC 2020. Each special session organizer will be session chair for their own special sessions at ICIC 2020 accordingly. All planned papers for special sessions will undergo the same review process as the ones in regular sessions. All accepted papers for special sessions will also be published by Springer's Lecture Notes in Computer Sciences (LNCS)/ Lecture Notes in Artificial Intelligence (LNAI)/ Lecture Notes in Bioinformatics (LNBI).

All the authors for each special session must follow the guidelines in CALL FOR PAPERS to prepare your submitted papers.

Proposals for special sessions should be submitted in ELECTRONIC FORMAT to Special Session Chair:

Abir Hussain
Liverpool John Moores University, UK
A.Hussain@ljmu.ac.uk


orders
Title
Organizers
Nationality
Special Session on Artificial Intelligence in Biological and Medical Information Procession
Wenzheng Bao and Bin Yang
China
Computational Intelligence for Applied Time Series Forecasting in Biomedical Sciences (CIATSFCSBS)
Cristian Rodriguez Rivero,Julian Pucheta,Leonardo Franco,Alvaro Orjuela Canon and Gustavo Juarez
Netherlands,Spain,Argentina
Special Session for ICIC 2020 Recent Advances in Swarm Intelligence: computing and applications
Ben Niu,Yanmin Liu,Qinge Xiao and Aijia Ouyang
China
Information Security
Yunxia Liu
China
Special Session on Exploring Complex Diseases with Next Generation Sequencing Data for Personalized Medicine
Shulin Wang, Jiawei Luo, Jianwen Fang,Xinguo Lu
China
Special Session on Machine Learning Techniques in Bioinformatics
Zheng-Wei Li,Lun Hu, Pengwei Hu
China
Special Session on High-performance Modelling Methods on High-throughput Biomedical Data
Chun-Hou Zheng,Junfeng Xia, Jin-Xing?Liu
China
Special Session on Intelligent Computing and Swarm Optimization
Qiuzhen Lin,Wenjian Luo, Lijia Ma
China
Special Session on Construction of Large-Scale Heterogeneous Molecular Association Network and its Application in Molecular Link Prediction
Zhu-Hong You, Yang-Ming Li,Yu-An Huang
China,USA

1. Special Session on Artificial Intelligence in Biological and Medical Information Procession

Organizers:
Wenzheng Bao
Xuzhou University of Technology, China
Email:baowz55555@126.com

Bin Yang
Zaozhuang University, China
Email: batsi@126.com

Scope and Topics:
Biological and medical information mining and procession can be regarded as one of the most significant issues in the field of artificial intelligence and machine learning. In this special session, we want to discuss the latest and novel artificial intelligence and machine learning approaches to deal with the information of medical information and biological data. It is indeed of great interest for the scientific community to discover and mine the potential information of such huge data. The aim of this session is therefore to draw a picture of the recent advances and challenges in evolving artificial intelligence in biological and medical information mining and procession.Topics for this session include, but are not limited to:

  • Gene Expression Data Mining
  • Gene Regulatory Network Inference
  • Biological Data Mining and Processing
  • Post Translational Modification Identification
  • Protein-Protein Interaction
  • Protein Structure Recognition
  • Medical Image Procession
  • Medical Data Mining
  • Artificial intelligence in Medical Information

2.Computational Intelligence for Applied Time Series Forecasting in Biomedical Sciences (CIATSFCSBS

Organizers:
Cristian Rodriguez Rivero
University of Amsterdam, Netherlands
Email:c.m.rodriguezrivero@uva.nl

Julian Pucheta
National University of Cordoba, Argentina
Email: jpucheta@unc.edu.ar

Leonardo Franco
University of Malaga, Spain
Email: lfranco@lcc.uma.es

Alvaro Orjuela Canon
University of Rosario, Argentina
Email: dorjuela@ieee.org

Gustavo Juarez
National University of Tucuman, Argentina
Email: juarez.gustavo@ieee.org

Scope and Topics:
Motivation :Over the past few decades, application of simple statistical procedures with considerable heuristic or judgmental input was the beginning of forecasting, then in the 80s, sophisticated time series models started to be used by some of the dynamic system operators, and these approaches, were to become pioneering works in this field.Soft computing methods including support vectors regression (SVR), fuzzy inference system (FIS) and artificial neural networks (ANN) to time-series forecasting (TSF) has been growing rapidly in order to unify the field of forecasting and to bridge the gap between theory and practice, making forecasting useful and relevant for decision-making in many fields of the sciences.The purpose of this session is to hold smaller, informal meetings where experts in a particular field of time series forecasting can discuss forecasting problems in Biomedical Sciences, research, and solutions in the field of applied machine learning. There is generally a nominal registration fee associated with attendance.This session aims to debate in finding solutions for problems facing the field of forecasting. We wish to hear from people working in different research areas, practitioners, professionals and academicians involved in this problematic. The session seeks to foster the presentation and discussion of innovative techniques, implementations and applications of different problems that are Forecasting involved, specially in real-world problems applied to control and automation.

  • Time Series Analysis
  • Time Series Forecasting
  • Evaluation of Forecasting Methods and Approaches
  • Impact of Uncertainty on Decision Making
  • Seasonal Adjustment
  • Multivariate Time Series Modelling and Forecasting
  • Clinical Time Series Machine learning approaches
  • Medical Data Mining
  • Healthcare Diagnosis and Prognostics

3. Special Session for ICIC 2020 Recent Advances in Swarm Intelligence: computing and applications

Organizers:
Ben Niu
Shenzhen University, China
Email:drniuben@gmail.com

Yanmin Liu
Zunyi Normal University, China
Email: yanmin7813@163.com

Qinge Xiao
Shenzhen University, China
Email:xqg2974@163.com

Aijia Ouyang
Zunyi Normal University, China
Email:oyaj@hnu.edu.cn

Scope and Topics:
Swarm intelligence is an important branch of nature-inspired computing that allows the group as a whole to accomplish tasks with decentralized self-organized behavior and collective intelligence. Particularly, the potential features of the parallel and distribution make SI a significant direction in computer domain. SI has a multidisciplinary character that broadly focuses on global-searching operators, life-cycle principles, unique exploration-exploitation strategies, etc. Recently years, SI becomes a power-engine transforming various research and applications. Emphasis is given to such aspects as the modeling and analysis of collective swarm systems; application of swarm intelligence models to real-world problems, and theoretical and empirical research in ant colony optimization, bacterial foraging optimization,particle swarm optimization, and other swarm intelligence algorithms. This special session aims to harvest the latest efforts in theoretical computing as well as numerical simulated calculation of swarm intelligence and their applications. Research areas relevant to the special issue include, but are not limited to, the following topics:

  • Particle swarm optimization
  • Bacterial foraging optimization
  • Ant colony optimization
  • Bee colony optimization
  • Artificial fish search algorithm
  • Harmony search algorithm
  • Water cycle algorithm
  • Other swarm and bio based algorithms
Applications of the above algorithms include but not limited to:
  • Operations research
  • Decision making
  • Management optimization
  • Information systems
  • Power and energy systems
  • Data mining
  • Multi-objective optimization
  • Pattern recognition
  • Robotics
  • Manufacturing system scheduling
  • Intelligent Transportation and Traffic
  • Maritime optimization and scheduling
  • Other relating applications

4.Information Security

Organizers:
Yunxia Liu
College of information science and technology, China
Email:liuyunxia0110@hust.edu.cn

Scope and Topics:
Information security has become a crucial need for almost all information transaction applications due to the large diversity of the hackers and attacks, Traditional techniques such as cryptography, watermarking, and data hiding are basic notions and play an important role in developing information security algorithms and solutions. In spite of the large development in the information security techniques, there are still several challenges that need to be addressed in terms of time, accuracy and reliability. The special session targets the information security research area with respect to trends, advanced techniques and applications, which attracts researchers and practitioners from academia and industry, and provides a discussion environment in order to share their experiences in information security. Authors are encouraged to submit both theoretical and applied papers on their research in information security. Topics of interest include, but are not limited to:

  • applied cryptography
  • data protection
  • formal methods in security
  • information dissemination control
  • information hiding and watermarking
  • network security
  • privacy
  • secure group communications
  • security in social networks
  • embedded security
  • blockchain Secure

5.Special Session on Exploring Complex Diseases with Next Generation Sequencing Data for Personalized Medicine

Organizers:
Shulin Wang, Professor, Ph.D
College of Computer Science and Electronics Engineering, Hunan University, China
Email:smartforesting@163.com

Jiawei Luo, Professor, Ph.D
College of Computer Science and Electronics Engineering, Hunan University, China
Email:luojiawei@hnu.edu.cn

Jianwen Fang, Ph.D
Division of Cancer Treatment and Diagnosis, National Cancer Institute, USA
Email:jianwen.fang@nih.gov

Xinguo Lu, Associate Professor, Ph.D
College of Computer Science and Electronics Engineering, Hunan University, China
Email:hnluxinguo@126.com

Scope and Topics:
The accumulation of next generation sequencing (NGS) data such as TCGA brings great challenges for analyzing and mining these data to explore complex diseases (such as cancer, diabetes and schizophrenia, etc.). Especially, the emergence of single cell sequencing technique increases the difficulty of this challenge. Novel data mining methods, therefore, are emergently explored to solve the integration of various NGS data to discover the potential laws hidden in these NGS data, which are of great benefit to personalized medicine as well as drug discovery and development. We sincerely invite the submission of high-quality, original and unpublished papers in this area and the extended and revised versions of the selected papers will be considered for relevant Journals. Topics for this session include, but are not limited to:

  • Identifying cancer-related driver genes and cancer progression
  • Integrative analysis of various next generation sequencing data
  • Cancer-related driver mutation/gene/pathway recognition and analysis
  • Identifying miRNA-mRNA regulatory modules based on next generation sequencing data
  • Exploring ncRNA-Disease association by various regulatory networks
  • Gene expression and regulation pattern discovery and classification
  • Network Biology/Medicine and Pathway/Regulation Analysis for cancer
  • Drug repositioning and computer-aided drug design by integrating sequencing information
  • Disease biomarker discovery and pharmacogenomics
  • Personalized medicine and treatment optimization
  • High-performance bio-computing and big data analytics in biology and medicine

6.Special Session on Machine Learning Techniques in Bioinformatics

Organizers:
Zheng-Wei Li, Associate Professor, Ph.D
School of Computer Science and Technology, China University of Mining and Technology, China
Email:zwli@cumt.edu.cn

Lun Hu, Professor, Ph.D
Xinjiang Institute of Physics and Chemistry, Chinese Academy of Sciences, China
Email:hulun499@gmail.com

Pengwei Hu, Ph.D
IBM Research
Email:hupwei@cn.ibm.com

Scope and Topics:
With the advances of the big data era in biology, it is foreseeable that machine learning will become increasingly important in the field and will be incorporated in vast majorities of analysis pipelines. Several machine learning algorithms are available in the present literature. However, researchers are facing difficulties in choosing the best technique that can be applied to their datasets. The goal of this session is to bring together professionals, researchers, and practitioners in the area of bioinformatics to present, discuss, and share the latest findings in the field, and exchange ideas that address real-world problems with real-world solutions. We invite the submission of high-quality, original and unpublished papers in this area. Topics for this session include, but are not limited to:

  • Analysis of high through-put biotechnology data
  • Biomedical data analysis/processing
  • Screening and analysis of differentially expressed genes
  • Computer aided diagnosis/treatment of diseases
  • Protein-protein interaction identification
  • MiRNA-disease association prediction
  • Drug discovery, design, and repurposing
  • Application and use of machine learning in healthcare
  • Future directions and challenges in bioinformatics

7.Special Session on High-performance Modelling Methods on High-throughput Biomedical Data

Organizers:
Chun-Hou Zheng, Professor, Ph.D
School of Computer Science and Technology, Anhui University, China
Email:zhengch99@126.com

Junfeng Xia, Professor, Ph.D
School of Computer Science and Technology, Anhui University, China
Email:jfxia@ahu.edu.cn

Jin-Xing?Liu?ProfessorPh.D
School?of?Information?Science?and?Engineering, Qufu?Normal?University, China
Email:sdcavell@126.com

Scope and Topics:
With the advent of high throughput technologies, especially next generation sequencing, an increasing number of data are generated in biomedical research. These big biomedical data encourage researchers to develop novel data integration and mining methodologies. Tools and techniques for analyzing big biomedical data enable a transformation of basic biomedical research to clinical applications. This session provides a forum for researchers to present and discuss the latest research results, to summarize recent advances, to evaluate existing algorithms and methods, and to timely identify and address emerging problems and challenges with regard to biomedical data integration and mining in the era of big data. We invite the submission of high-quality, original and unpublished papers in this area. Topics for this session include, but are not limited to:

  • AI?and?machine?learning?methods?in?bioinformatics
  • Big data science including storage, analysis, modeling and visualization
  • Next generation sequencing data analysis, applications, and tools
  • Brain Imaging Genomics
  • MiRNA-Disease association prediction
  • Medical informatics and translational bioinformatics
  • LncRNA-Disease association prediction
  • Microbe-Disease association prediction
  • Drug discovery, design, and repurposing
  • Disease gene network/pathway analysis
  • Computational?modeling?and?data?integration
  • Applications of systems biology approaches to biomedical studies
  • Integrative analysis of multi-omics data

8.Special Session on Intelligent Computing and Swarm Optimization

Organizers:
Qiuzhen Lin, Associate Professor, Ph.D,
College of Computer Science and Software Engineering, Shenzhen University, China
Email:qiuzhlin@szu.edu.cn

Wenjian Luo, Professor, Ph.D,
Harbin Institute of Technology, Shenzhen, China
Email:luowenjian@hit.edu.cn

Lijia Ma, Assistant Professor, Ph.D,
College of Computer Science and Software Engineering, Shenzhen University, China
Email:ljma1990@szu.edu.cn

Scope and Topics:
Recent years, with the rapid developments of Internet, hardware, big data and artificial intelligence, intelligence computing and swarm optimization have received great focuses in the fields of physics, bioinformatics, engineering, computer science, social computing, etc. Intelligence computing and swarm optimization focus on problems that are difficult to be solved by artificial systems, but they can be easily solved by humans and some animals with collective intelligence. Generally, these problems show the nondeterministic polynomial-time hard (NP-hard) property. Intelligence computing and swarm optimization have been successfully applied to many NP-hard problems, like traveling salesman problem, hamiltonian cycle problem, decision making problem, network clustering, maximum clique problem, etc. Moreover, many intelligence computing and swarm optimization methods have been proposed to solve these problems, and they have showed very promising performance for the practical applications. The aim of this special issue is to introduce some recent advances in intelligence computing and swarm optimization and their applications, which are useful for both researchers and engineers. We invite the submission of high-quality, original and unpublished papers in this area. Topics for this session include, but are not limited to:

  • Evolutionary Algorithm
  • Genetic Algorithm
  • Artificial Immune System
  • Particle Swarm Optimization?
  • Artificial Bee Colony Algorithm
  • Brain Storm Optimization Algorithm
  • Harmony Search
  • Differential Evolution
  • Teaching Learning Based Optimization
  • Grey Wolf Optimizer
  • Neural Networks?
  • Fuzzy System?
  • Applications of intelligence computing and swarm optimization?
  • Parallel Computing?
  • Computational?modeling?and?data?mining?
  • Analysis of the benchmarks of real-world applications?

9.Special Session on Construction of Large-Scale Heterogeneous Molecular Association Network and its Application in Molecular Link Prediction

Organizers:
Zhu-Hong You, Professor, Ph.D
Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Science, China
Email:zhuhongyou@ms.xjb.ac.cn

Yang-Ming Li, Assistant Professor, Ph.D
Department of Electrical Computer and Telecommunications Engineering Technology, Rochester Institute of Technology, USA
Email:Yangming.Li@rit.edu

Yu-An HuangPh.D
School?of?Information?Science?and?Engineering, Qufu?Normal?University, China Department of Computing, Hong Kong Polytechnic University, Hong Kong SAR, China
Email:yu-an.huang@connect.polyu.hk

Scope and Topics:
The key issue in the post-genomic era is how to systematically describe the association between small molecule transcripts or translations inside cells. With the rapid development of high-throughput omics technologies, the achieved ability to detect and characterize molecules with other molecule targets opens up the possibility of investigating the relationships between different molecules from a global perspective. More specifically, a Molecular Associations Network (MAN) is constructed and comprehensively analyzed by integrating the associations among miRNA, lncRNA, protein, drug, and disease, in which any kind of potential associations can be predicted. This session provides a forum for researchers to present and discuss the latest research results, and to timely identify and address emerging problems and challenges with regard to construction and analysis of a Molecular Associations Network. We invite the submission of high-quality, original and unpublished papers in this area. Topics for this session include, but are not limited to:

  • Construction of large-scale heterogeneous molecular association network
  • Analysis and visualization of large-scale proteomic data
  • Big data approaches for proteomics data analyses
  • Big data and health information technologies
  • Deep learning approaches in bioinformatics
  • Biomedical data modeling and mining
  • Intelligent computing in drug design
  • Modeling, simulation, and optimization of biological systems
  • Phosphoproteomics data analysis, signaling pathway modeling.
  • Drug resistance study using drug combination treatment strategies.

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