Special Issue on Clusters, Clouds and Grids for Life Sciences (LIFE2019)
• 大类 : 工程技术 - 2区
• 小类 : 计算机：理论方法 - 2区
"Future Generation Computer Systems", a forum for the publication of peer-reviewed, high-quality original papers showing advances in distributed systems, collaborative environments, high performance and high-performance computing, Big Data on such infrastructures as grids, clouds and the Internet of Things (IoT), is seeking original manuscripts for aSpecial Issue on Clusters, Clouds and Grids for Life Sciences (LIFE2019)scheduled to appear in the second half of 2019.
Computational methods are nowadays ubiquitous in the field of bioinformatics and biomedicine. Besides established fields like molecular dynamics, genomics or neuroimaging, new emerging methods like deep learning models rely heavily on large-scale computational resources. These 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. 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. Clouds, Edge/Fogs and Big Data Environments are promising to address research, clinical and medical research community requirements as they allow for significant reduction of computational time to run large experiments, for speeding-up development time for new algorithms, and to reduce barriers for large-scale multi-centric collaborations.
The special issue will provide a forum for presenting research works showing advances of bioinformatics and medical applications using distributed IT systems, new ideas and approaches to successfully apply distributed IT-systems in translational research, clinical intervention, and decision-making, and novel proposal to tackle specific challenges in Life Sciences computing such as security, traceability, data interoperability, simulation of complex models, creation of cloud services, or application of artificial intelligence techniques to enhance decisions and to speed up processes.
The special issue will be open to any author, but it will also invite extended versions of selected papers of CCGrid-Life 2019 workshop, held with CCGRID 2019, whose topics fit in the scope of this special issue. Each submission will be reviewed by at least three reviewers to ensure a very high quality of papers selected for the Special Issue.
AREAS OF INTEREST
This special issue of Future Generation Computing Systems will feature articles that discuss the following areas of interest:
Novel exploitation techniques of distributed IT resources for Life Sciences, HealthCare and research applications, for example medical imaging, disease modeling, bioinformatics, Public health informatics, drug discovery, and clinical trials.
New distributed algorithms applicable to medical and bioinformatics applications,
Modeling and simulation of complex biological processes (Genomics and Molecular Structure evolution, Molecular Dynamics, etc.)
New scientific gateways and user environments targeting distributed medical and bioinformatics applications Clouds for big data manipulation in bioinformatics and medicine.
Cloud services for life sciences (genomics as a service, medical image as a service, protein folding, etc.)
Biological data mining and visualization, ontologies and text mining.
New deep learning and machine learning experiences in Life Sciences.
Distributed and heterogeneous bioinformatics and medical data management for data-enabled life sciences, including standardization, interoperability for data exchanges, privacy, security and access control.
Novel development environments, programming paradigms and tools distributed bioinformatics applications
Big Medical and Bioinformatics Data applications and solutions for Clouds, Edge/Fogs and Big Data Environments.
New solutions for process optimizations using smart contracts and block chain technology.
Reproducibility and traceability of experiments in Life sciences.
Detailed application use-cases highlighting achievements and roadblocks using hybrid or public clouds.