Digital transformation is in full progression in worldwide healthcare and life sciences, leading to creation, storage and processing of massive amounts of health related data. Artificial intelligence and Big Data Analytics have been established in bioinformatics and biomedical research and are increasingly reaching healthcare with certified clinical decision support systems and smart health apps. Besides stablished fields like molecular dynamics, genomics or neuroimaging now many other medical domains rely heavily on large scale computational resources.
The emerging new methods need to manage Tbytes or Pbytes of data with large-scale structural and functional relationships, TFlops or PFlops of computing power for simulating highly complex models, or many-task processes and workflows for processing and analyzing data. On the other hand, they need to provide interaction with highly distributed user landscapes, such as actors of primary care, hospitals and increasingly the patient itself Today, many areas in Life Sciences are facing these challenges, such as biomodelling, predictive models of disease and treatment, evolutionary biology, medical biology, cell biology, biomedical image processing, biosignal sensoring or computer-supported diagnosis.
This new situation demands appropriate IT-infrastructures, where biological and medical data can be processed within an acceptable timespan – reaching from minutes in health-care applications to days in large-scale research projects. Distributed IT-systems such as Grids, Clouds, Fogs and Big Data Environments are promising to address research, clinical and medical research community requirements. They allow for significant reduction of computational time for running large experiments and for speeding-up development time for new algorithms. Furthermore, they can increase the availability of new methods for the research community and reduce barriers for large-scale multi-centric collaborations. However, specific challenges in the employment of such systems for biomedical applications – such as security, reliability and user-friendliness – often impede straightforward adoption of existing solutions from other application domains.
This workshop aims at bringing together developers of bioinformatics and medical applications and researchers in the field of distributed IT systems. It addresses researchers who are already employing distributed infrastructure techniques in biomedical applications as well as computer scientists working in the field of distributed systems interested in bringing new developments into the biomedical area. The goals of the workshop are to exchange and discuss existing solutions and latest developments in both fields, and to identify the remaining challenges. The workshop further intends to identify common requirements to lead future developments in collaboration between Life Sciences and Computing Sciences. It aims to explore new ideas and approaches to successfully apply distributed IT-systems in translational research, clinical intervention, and decision-making.
Contributions accepted for CCGrid-Life 2022 are invited to submit an extended version to the Special Issue in Future Generation Computer Systems (Impact Facctor 7.1) FCGS – LIFE2022
Submission Guidelines
All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:
Full papers or Posters describing contributions to the following topics:
Detailed application use-cases highlighting achievements and roadblocks
Exploitation of distributed IT resources for Life Sciences, HealthCare and research applications, for example medical imaging, disease modeling, bioinformatics, Public health informatics, drug discovery, clinical trials
Service and/or algorithm design and implementation applicable to medical and bioinformatic applications
Improved energy consumption of bioinformatic applications using clouds
Modeling and simulation of complex biological processes
Genomics and Molecular Structure evolution
Molecular Dynamics
Clouds for big data manipulation in bioinformatics and medicine
Ontologies and biomedical text mining
Biological data mining and visualization
Machine Learning in biomedical data analytics
Deep learning experiences in Life Sciences
Error handling and fault tolerance
Distributed and heterogeneous bioinformatic and medical data management
Big Medical and Bioinformatic Data applications and solutions
Data privacy, security and access control
Development environments for distributed bioinformatic applications
Programming paradigms and tools for bioinformatic applications
Scientific gateways and user environments targeting distributed medical and bioinformatic applications
Interoperability for exchanging data, algorithms and analysis pipelines
Committees
Program Committee
Jesus Carretero, University Carlos III of Madrid, Spain
Vladimir Korkhov, St. Petersburg State University, Russia
Scott Emrich, University of Tennessee, USA
Julian Kunkel, Gesellschaft für wissenschaftliche Datenverarbeitung mbH Göttingen, Germany
Tram Truong-Huu, National University of Singapore, Singapore
Kary Ocaña, National Laboratory of Scientific Computing, Brazil
Alban Gaignard, CNRS, France
Sandra Gesing, University of Illinois Chicago, IL, USA
Dagmar Krefting, University Medical Center Göttingen, Germany
Daniel de Oliveira, Fluminense Federal University, Niterói, Brazil
Tristan Glatard, Concordia University, Montreal, Canada
Afonso Duarte, Agency for Clinical Research and Biomedical Innovation, Portugal
Arrate Munoz-Barrutia Universidad Carlos III de Madrid, Spain
Bruno Schulze LNCC/MCT, Brazil
Ivan Merelli Institute for Biomedical Technologies – National Research Council, Italy
Silvia D. Olabarriaga, Amsterdam University Medical Centers, University of Amsterdam, Netherlands
Organizing committee
Jesus Carretero, University Carlos III of Madrid, Spain
Dagmar Krefting, University Medical Center Göttingen, Germany
Sandra Gesing, University of Illinois Chicago, IL, USA
Silvia D. Olabarriaga, AMC/ University of Amsterdam, Netherlands
Contact
All questions about submissions should be emailed to Jesus Carretero (jesus.carretero@uc3m.es) or Dagmar Krefting (dagmar.krefting@med.uni-goettingen.de)