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High-throughput technologies (e.g. microarray, mass spectrometry, NGS) and clinical diagnostic tools (e.g. medical imaging) are producing an increasing amount of experimental and clinical data. In such a scenario, large-scale databases and bioinformatics tools are key tools for organizing and exploring biological and biomedical data with the aim to discover new knowledge in biology and medicine.
High-performance computing may play an important role in many phases of life sciences research, from raw data management and processing, to data analysis and integration, till data exploration and visualization. In particular, at the raw data layer, Grid 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) and for more advanced analysis (e.g. parallel data mining). In such a scenario, novel parallel architectures (e.g. 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.
At an higher layer, emerging biomedical applications need to use in a coordinated way both bioinformatics tools, biological data banks and patient’s clinical data, that require seamless integration, privacy preservation and controlled sharing. Service Oriented Architectures and semantic technologies, such as ontologies, may allow the building and deployment of the so-called collaboratories where remote scientists may conduct experimental research in a collaborative way.
The goal of HiBB is to bring together scientists in the fields of bioinformatics, biomedicine, medical informatics, high performance computing, as well as scientists working in biology and medicine, to discuss, among the others, the challenges and the requirements posed by novel data analysis pipelines for the management and analysis of omics data, that are more and more produced by high-throughput experimental platforms as well as diagnostic tools. Furthermore, the use of novel parallel architectures and dedicated hardware to implement bioinformatics and biomedical algorithms will be discussed.
Interest to the BIBM community
Bioinformatics and Biomedicine are two main application domains where the large availability of data, the complexity of analysis pipeline and the presence of continuous data, represent main challenges for the parallel and distributed computing community. On the other hand, to be effective in the biology, medicine and clinical environment, data analysis pipelines need to exploit the power offered by high performance computers and Cloud systems, that will more and more be used in health scenarios.
The main motivation for the HiBB workshop is the increasing production of experimental and clinical data in biology and medicine, and the needs to provide efficient storage, preprocessing and analysis of this data for supporting the biomedical research.
In fact, the availability and large diffusion of high-throughput experimental platforms, such as Next Generation Sequencing, Microarray and Mass Spectrometry, as well as the improved resolution and coverage of clinical diagnostic tools, such as Magnetic Resonance Imaging, are becoming the major sources of data in biomedical research, and the storage, preprocessing, and analysis of this data is becoming the main bottleneck of the biomedical analysis pipeline.
Parallel computing and high-performance infrastructures are more and more used in all phases of life sciences research, e.g. for storing and preprocessing large experimental data, for the simulation of biological systems, for data exploration and visualization, for data integration, and for knowledge discovery.
The current bioinformatics scenario is characterized by the application of well established techniques, such as parallel computing on multicore architectures and grid computing, as well as by the application of emerging computational models such as graphics processing and cloud computing.
Large scale infrastructures such as grids or clouds are mainly used to store in an efficient manner and to share in an easy way, the huge experimental data produced in life sciences, while parallel computing allows the efficient analysis of huge data.
In particular, novel parallel architectures such as GPUs and emerging programming models such as MapReduce, may overcome the limits posed by conventional computers to the analysis of large amounts of data.
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:
- 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
- Affective 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 Novembre 18-21, 2019 (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-2019 Workshops submission system:
https://wi-lab.com/cyberchair/2019/bibm19/scripts/ws_submit.php?subarea=S
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
Sept. 20, 2019: Due date for full workshop papers submission
Oct. 15, 2019: Notification of paper acceptance to authors
Nov. 1, 2019: Camera-ready of accepted papers
Nov. 18-21, 2019: Workshop
JOURNAL SPECIAL ISSUE
After of the workshop, we plan to invite the best papers of the workshop for a special issue of an international journal.
WORKSHOP ORGANIZER
Mario Cannataro, University Magna Graecia of Catanzaro, Italy
PROGRAM COMMITTEE (TO BE CONFIRMED)
- Giuseppe Agapito, University Magna Graecia of Catanzaro, Italy
- Pratul K. Agarwal, Oak Ridge National Laboratory, USA
- Ignacio Blanquer; Universidad Politecnica de Valencia, Valencia, Spain
- Barbara Calabrese, University Magna Graecia of Catanzaro, Italy
- Giuseppe Di Fatta, University of Reading, UK
- Werner Dubitzky, University of Ulster, UK
- Ananth Y. Grama, Purdue University, USA
- Concettina Guerra, Georgia Institute of Technology, USA
- Vicente Hernandez, Univ. Politecnica de Valencia, Spain
- Marianna Milano, University Magna Graecia of Catanzaro, Italy
- Salvatore Orlando, University of Venezia, Italy
- Horacio Perez-Sanchez, University of Murcia, Spain
- Laura Ricci, University of Pisa, Italy
- Richard Sinnott, University of Melbourne, Melbourne, Australia
- Giuseppe Tradigo, University Magna Graecia of Catanzaro, Italy
- Paolo Trunfio, University of Calabria, Italy
- Albert Zomaya, University of Sydney, Australia
- Chiara Zucco, University Magna Graecia of Catanzaro, Italy
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