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Due to the availability of high-throughput platforms (e.g. next generation sequencing, microarray and mass spectrometry) and clinical diagnostic tools (e.g. medical imaging), a recent trend in Bioinformatics and Biomedicine is the ever-increasing production of experimental and clinical data.
Considering the complex analysis pipelines often used in biomedical research, there is a main bottleneck that involves the storage, integration, and analysis of experimental data, as well as their correlation and integration with publicly available data banks. While parallel computing and Grid computing may offer the computational power and the storage to face this overwhelming availability of data, Cloud Computing is a key technology to hide the complexity of computing infrastructures, to reduce the cost of the data analysis task, and especially to change the overall model of biomedical research and health care delivery.
High-performance infrastructures may offer the huge data storage needed to store experimental and biomedical data, while parallel computing can be used for basic pre-processing (e.g. parallel BLAST, mpiBLAST) and for more advanced analysis (e.g. parallel data mining). In such a scenario, novel parallel architectures (e.g. CELL processors, GPUs, FPGA, hybrid CPU/FPGA) coupled with emerging programming models may overcome the limits posed by conventional computers to the mining and exploration of large amounts of data. On the other hand, these technologies require great investments by biomedical and clinical institutions and are based on a traditional model where users often need to be aware and face different management problems, such as hardware and software management, data storage, software ownership, and prohibitive costs (professional-level software applications in the biomedical domain have very high licensing costs preventing many small laboratories from using them).
Cloud Computing technology, that is able to offer scalable costs with increased accessibility, availability and ease of application use, while enhancing the potential for collaboration among scientists, is already changing the business model in different sectors and has been adopted in the bioinformatics and biomedical domains. However, many problems remain to be solved, such as availability and safety of the data, privacy-related issues, availability of software platforms for rapid deployment, and the execution and billing of biomedical applications.
The goal of ParBio 2019 is to bring together scientists in the fields of high performance and cloud computing, computational biology and medicine to discuss the parallel implementation of bioinformatics and biomedical applications and problems and opportunities of moving biomedical and health applications to the cloud. Moreover, big data analytics issues in healthcare and bioinformatics will be addressed. The workshop will focus on research issues, problems and opportunities of moving biomedical and health applications to the cloud, as well as on the opportunity to define guidelines and minimum requirements for a Biomedical Cloud. Moreover, the workshop will discuss parallel and distributed management and analysis of molecular and clinical data that more and more needs to be integrated and analyzed in a joint way.
TOPICS OF INTEREST
The main themes and research topics include applications of parallel and high performance computing to biology and medicine, as well as Cloud Computing opportunities and problems encountered for bioinformatics and biomedical applications deployment.
- Data Science in Bioinformatics and Health Informatics
- Big data analytics in healthcare and bioinformatics
- Data Mining in Bioinformatics and Health Informatics
- Deep Learning in Bioinformatics and Health Informatics
- Sentiment Analysis in bioinformatics and healthcare
- Effective Computing in bioinformatics and healthcare
- Text mining of biomedical literature and clinical notes
- Healthcare data quality, privacy, and security
- High performance computing for computational biology
- Data integration and ontologies in biology and medicine
- Large scale biological and biomedical databases
- Parallel bioinformatics algorithms
- Parallel visualization and exploration of omics and clinical data
- Parallel visualization and analysis of biomedical images
- Computing environments for large scale collaboration
- Scientific workflows in bioinformatics and biomedicine
- Emerging architectures and programming models for bioinformatics and biomedicine
- Parallel processing of bio-signals
- Modeling and simulation in healthcare and medicine
- Cloud Computing for bioinformatics and biomedicine
- Cloud Computing for health systems
- Services for bioinformatics and biomedicine
- Internet of Things in bioinformatics and healthcare
- Peer-To-Peer Computing for bioinformatics and biomedicine
PROGRAM
The workshop will take place on September 7th (tentative).
The workshop is scheduled as a half-day event
in conjunction with the ACM BCB conference.
PAPER SUBMISSION, REGISTRATION AND PUBLICATION
ParBio 2019 welcomes original submissions of any length that have not been published and that are not under review by another conference or journal. Papers should not exceed 10 pages in ACM template on 8.5 x 11 inch paper (see ACM templates - http://www.acm.org/sigs/publications/proceedings-templates). All submissions will be evaluated on their originality, technical soundness, significance, presentation, and interest to the conference attendees.
Submission implies the willingness of at least one of the authors to register and present the work associated with the paper submitted. ParBio's technical program committee will review all submitted papers. All accepted papers of registered authors will be included in the workshop proceedings published by ACM digital libraries. Authors of selected papers may be invited to adapt their papers for publication in several journals. Authors of accepted papers will be required to submit an online ACM Copyright Form. Authors will be contacted by ACM requesting this information.
(Note that ACM copyright permissions are directly compatible with NIH and similar open access policies, see http://authors.acm.org/main.html for more information.).
Authors should submit papers using the ParBio2019 EasyChair Installation:
https://easychair.org/conferences/?conf=parbio2019
IMPORTANT DATES
Paper submissions due: *extended* June 24, 2019
Notifications sent to authors: July 1, 2019
Camera-ready papers due: July 8, 2019
Workshop date: September 7, 2019 (tentative)
WORKSHOP ORGANIZERS
Prof. Mario Cannataro
Dep. of Medical and Surgical Sciences,
University Magna Graecia, Catanzaro
ITALY
Prof. Wes J. Lloyd
School of Engineering and Technology,
University of Washington, Tacoma
USA
Dr. Giuseppe Agapito
Dep. of Medical and Surgical Sciences,
University Magna Graecia, Catanzaro
ITALY
PROGRAM COMMITTEE
- Pratul K. Agarwal, Oak Ridge National Laboratory, USA
- Marian Bubak, AGH Krakow, PL, and University of Amsterdam, NL,
- Barbara Calabrese, University Magna Graecia of Catanzaro, Italy
- Umit Catalyurek, The Ohio State University, USA
- Jake Y. Chen, Indiana University - Purdue University Indianapolis (IUPUI), USA
- Tim Clark, Harvard Medical School, USA
- Giuseppe Di Fatta, University of Reading, UK
- Werner Dubitzky, University of Ulster, UK
- Ling Hong Hung, University of Washington Ð Tacoma, USA
- Ananth Y. Grama, Purdue University, USA
- Concettina Guerra, Georgia Institute of Technology, USA
- Pietro Hiram Guzzi, University Magna Graecia of Catanzaro, Italy
- Kamer Kaya, The Ohio State University, USA
- Marianna Milano, University Magna Graecia of Catanzaro, Italy
- Salvatore Orlando, University of Venezia, Italy
- Maria S. Perez, Universidad Politecnica de Madrid, Madrid, Spain
- Shruti Ramesh, Micrsosoft, Redmond, WA USA
- Richard Sinnott, University of Melbourne, Melbourne, Australia
- Roberto Tagliaferri, University of Salerno, Italy
- Giuseppe Tradigo, University Magna Graecia of Catanzaro, Italy
- Paolo Trunfio, University of Calabria, Italy
- Pierangelo Veltri, University Magna Graecia of Catanzaro, Italy
- Albert Zomaya, University of Sydney, Australia
- Chiara Zucco, University Magna Graecia of Catanzaro, Italy
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