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PROGRAM SCHEDULE
The modelling and investigation of complex system through graphs that integrate biological, biomedical and clinical data, represent a hot topic for the research community. Since the study of associations in a system-level scale has shown great potential, the use of networks has become a de-facto standard and the application fields span from molecular biology to connectome analysis.
Networks and network analysis methods are a keystone in computational biology and bioinformatics and are more and more used to study biological and clinical data in an integrated way.
Network analysis consists of a collection of techniques with a shared methodological perspective, which allow to depict relations among entities and to analyze the structures that emerge from the recurrence of these relations.
The basic assumption is that better explanations of different phenomena are yielded by analysis of the relations among entities.
Network analysis can be performed to a single network or for the comparison of two or more networks. The methods belonging to the first class analyze the properties of a single network and extract both the global and local properties of the graph. These properties are then used to infer knowledge. For example, in interatomic, the identification of small subgraphs that are statistically overrepresented can be used to identify functionally relevant modules. Similarly, network analysis is used to highlight highly connected regions, assuming they can encode protein complexes. In addition, the systematic study of complex interactions among molecular components (i.e. DNA, RNA, microRNA, proteins and small molecules) is a new paradigm for discovering functional pathways in a global scale.
Furthermore, the methods belonging to the second class study the conservation and divergence of interactions between different species.
In parallel, Representation Learning (RL) is applied to biological networks from modeling to learning with networks.
In particular, Network representation learning (NRL) and cascade representation learning (CRL) are fundamental backbones of different kinds of network analysis problems.
Interest to the BIBM community
Biological Network Analysis can be utilized in several applications such as the identification of drug targets, determining the role of proteins or genes of unknown function, the design of effective strategies for infectious diseases and the early diagnosis of neurological disorders through detecting abnormal patterns of neural synchronization in specific brain regions.
The main motivation for the workshop is focuses on the collection of advanced works on development of new pipelines, algorithms and tools for the network analysis of complex systems in different domains.
TOPICS OF INTEREST
The workshop is seeking original research papers presenting applications of parallel and high performance computing to biology and medicine. Topics of interest include, but are not limited to:
Network-based bioinformatics methods;
Networks-based applications in computational biology, genomics, medicine, and healthcare;
Graph representation learning for visualizing and interpreting biological and biomedical data;
Bioinformatics methods for network-based analysis and visualization;
Network-based modelling and analysis of complex diseases;
Complex network models for structure and function analysis;
Network models in epidemiology;
Next-generation network science;
Artificial intelligence for network models of complex diseases;
Applications of deep learning approaches in computational biology, genomics, medicine, and healthcare;
Networks Alignment;
Complex Prediction;
Network Embedding;
Pathways Analysis;
Interactomics databases;
Pathways databases.
PROGRAM
The workshop will take place on December 6-9, 2022 (To Be Announced). The program is not available yet.
PAPER SUBMISSION, REGISTRATION AND PUBLICATION
Please submit a full-length paper (up to 8 page IEEE 2-column format) through the BIBM-2022 Workshops submission system:
https://wi-lab.com/cyberchair/2022/bibm22/scripts/ws_submit.php
You can download the format instruction here:
http://www.ieee.org/conferences_events/conferences/publishing/templates.html
Electronic submissions (in PDF or Postscript format) are required. Selected participants will be asked to submit their revised papers in a format to be specified at the time of acceptance.
IMPORTANT DATES
Oct 10, 2022: Due date for full workshop papers submission
Nov 5, 2022: Notification of paper acceptance to authors
Nov. 21, 2022: Camera-ready of accepted papers
Dec 6-9, 2022: Workshops
WORKSHOP ORGANIZER
Marianna Milano, University Magna Graecia of Catanzaro, Italy
m.milano@unicz.it
Giuseppe Agapito, University Magna Graecia of Catanzaro, Italy
agapito@unicz.it
PROGRAM COMMITTEE (TO BE CONFIRMED)
Loris Belcastro, University of Calabria, Italy
Marzia Settino, University Magna Graecia of Catanzaro, Italy
Anna Bernasconi, Politecnico di Milano
Barbara Calabrese, University Magna Graecia of Catanzaro, Italy
Chiara Pastrello Krembil Research Institute (KRI), Toronto, Canada
Antonio Guerrieri, ICAR-CNR, Italy
Fabrizio Marozzo, University of Calabria, Italy
Chiara Zucco, University Magna Graecia of Catanzaro, Italy
Anna Procopio, University Magna Graecia of Catanzaro, Italy
Pietro Cinaglia, University Magna Graecia of Catanzaro, Italy
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