Welcome

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.

Topics of Interest

Contributions are expected but not restricted 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

Other Community Efforts and Special Issue

The community gathering around the topics of Clusters, Clouds and Grids computing for Life Sciences is active across the year and, as part of other efforts, is hosting a special issue of FGCS (IF 7.1) on topics of interest. The special issue is open to all the scientists around the world working in this domain. Authors of papers at the workshop can consider the special issue as a possible venue for their future work. Contributions accepted for CCGrid-Life 2022 are invited to submit an extended version to the Special Issue. All papers will be peer-reviewed. Please, look for details at FCGS - LIFE2022 .