2018 IEEE World Congress on Computational Intelligence (WCCI 2018)
Rio de Janeiro, BRAZIL, 08-13 July 2018 - http://www.ecomp.poli.br/~wcci2018/
Abstract & Topics
Bioinformatics and Computational Biology deal with a wide range of problems and applications which, in recent years, have been successfully solved by means of Computational Intelligence and Machine Learning techniques. Moreover, due to technological progress, huge amounts of data concerning biological organisms are gathered and collected (e.g. genes transcript, protein structures and the like), thereby demanding the use of parallel and distributed computing for facing Big Datasets and/or high-throughput application requirements. Further, in such fields, data usually encodes complex information, which is natively represented by structured records, such as sequences, graphs and images, most of which lie in so-called “non-metric spaces”, i.e. input spaces for which a meaningful (dis)similarity measure might not be metric, making the problem more challenging since ad-hoc (dis)similarity measures or embedding functions need to be defined.
This Special Session aims at collecting the latest research in Computational Intelligence applications for Bioinformatics and Computational Biology, with emphasis on parallel/distributed computing and non-metric spaces analysis, by means of different (or hybridization of) Computational Intelligence techniques, from evolutionary meta-heuristics to neural computation, from pattern recognition to fuzzy systems.
Topics of interest include (but are not limited to):
- Protein function prediction
- Protein folding prediction
- Generative models for protein contact networks
- String kernel methods for sequence classification
- Mining metabolic pathways
- Gene finding and prediction
- Exact/inexact motifs and pattern matching
- Network and Systems Biology
- Granular computing approaches for non-metric spaces analysis
- Large-scale data mining and pattern recognition
- Distributed and parallel computing systems for machine learning and data mining
- Clinical Diagnostic Systems
- Medical image analysis
● Prof. Antonello Rizzi, University of Rome “La Sapienza”, Rome, email@example.com
● Dr. Alessandro Giuliani, Istituto Superiore di Sanità, Rome, firstname.lastname@example.org
Antonello Rizzi received the Ph.D. in Information and Communication Engineering in 2000, from the University of Rome “La Sapienza”. In September 2000, he joined the INFO-COM Dpt., as an Assistant Professor. Since July 2010 he joined the “Information Engineering, Electronics and Telecommunications” Dpt. (DIET), in the same University. His major research interests are in the area of Soft Computing, Pattern Recognition and Computational Intelligence, including supervised and unsupervised data driven modeling techniques, neural networks, fuzzy systems and evolutionary algorithms. His research activity concerns the design of automatic modeling systems, focusing on classification, clustering, function approximation and prediction problems. Currently, he is working on different research topics and projects, such as Granular Computing, Data Mining and Knowledge Discovery, Content Based Retrieval Systems, classification and clustering systems for structured patterns, graph and sequence matching, agent-based clustering, smart grids and micro-grids modeling and control, intelligent systems for sustainable mobility, battery management systems. Since 2008, he serves as the scientific coordinator and technical director of the R&D activities in the "Intelligent Systems Laboratory" within the Research and Technology Transfer Center for Sustainable Mobility of Lazio Region. He is the scientific coordinator of the "Computational Intelligence and Pervasive Systems" Lab at DIET. Dr. Rizzi (co-)authored more than 140 international journal/conference papers and book chapters. He is a member of IEEE.
Alessandro Giuliani was born in Roma, on February 14, 1959. He took his Laurea in Biological Sciences at University of Rome "La Sapienza" score 110/110 cum laude (Academic Year ‘81/’82) with a specialization in Statistics. He serves as Senior Scientist at Environment and Health Dept., Istituto Superiore di Sanità, Rome, Italy (1997 - ). He is Professor (on contract basis) at Pontifical Urbaniana University, Rome.
Dr. Alessandro Giuliani is involved since more than thirty years in the generation and testing of soft physical and statistical models for life sciences. He puts a special emphasis on the elucidation of mesoscopic complex systems like protein sequence/structure prediction, complex network approaches, QSAR, Systems Biology. He contributed (together with Prof. Zbilut and Prof. Webber) to the development of Recurrence Quantification Analysis (RQA) data analysis technique. He is the author of about 300 publications on peer-review journals with an H-index = 38.
More information can be found at
- Official WCCI 2018 Call for Papers: http://www.ecomp.poli.br/~wcci2018/call-for-papers/
- Official WCCI 2018 Guidelines: http://www.ecomp.poli.br/~wcci2018/submissions/#guidelines
- The Special Session website: https://sites.google.com/a/uniroma1.it/wcci2018-ci4bcb/