Call for Papers

The Second International Workshop on Big Data in Bioinformatics and Healthcare Informatics (BBH2014) is the leading forum for research, work-in-progress, and applications addressing big data challenges. BBH2014 is calling for papers presenting concepts, infrastructure, and analytical tools that integrate data from heterogeneous data sources to provide new insights for researchers and industries. You can access the latest Call for Paper for BBH14 in PDF format.

Important Dates

  • Paper submission: Aug 4, 2014 Aug 25, 2014 (Final Extension)
  • Notification of acceptance: Sep 22, 2014
  • Submission of camera-ready papers: Sep 28, 2014

Topics of Interest

¬†We welcome submissions covering various aspects of big data processing and analysis in “Bioinformatics” and “Healthcare Informatics”. Areas of interest include but are not limited to computer science, in-memory technology, computational science, biological, biomedical, pharmaceutical, nursing, clinical care, dentistry, and public health.

Bioinformatics and Biomedical Informatics

  • Next-generation sequencing (NGS) data storage and analysis
  • Large scale biological network construction and learning
  • Population-based bioinformatics
  • Genome structural change detection
  • Large-scale bio-image and medical-image analysis
  • Big data in molecular simulation and protein structure prediction
  • Big data in systems biology
  • Big data in precision medicine and stratified medicine
  • Big data in drug discovery, development, and post-market surveillance
  • Big data in semantics and bio-text mining

Healthcare Systems

  • Real-time aspects of healthcare data infrastructure
  • Security and privacy for clinical data in big data infrastructures
  • Health IT implementations and demonstrations
  • Case studies for healthcare analysis in distributed environments
  • Benchmarking of big data infrastructure in healthcare
  • Novel data analysis algorithms that enable integrated discovery of knowledge from structured and unstructured Electronic Medical Records (EMR)
  • Analysis and visualizing for summarizing large patient data in EMRs
  • Novel algorithms and applications dealing with noisy, incomplete, but large EMR data
  • Integrating genomic data in today’s medicine to improve human health
  • Data science and modeling for health analysis
  • Advances in new storage models for data variety (records, images, Magnetic Resonance Imaging (MRI), scans) for hospitals
  • Big data challenges in accountable care settings
  • Extracting meaning from multi-structured big data in real time to improve outcome
  • Combining information from imaging (RIS, PACS), Electronic Health Records (EHR), laboratories, genomics to give coherent diagnosis and treatment
  • Leveraging social networks for data aggregation
  • Smart visualizations for big data streams
  • Analysis of big data from home monitoring devices
  • Design patterns and anti-patterns for development of solutions for big data

Analysis of Big Medical Data

  • Real-time analysis of big medical data in the course of precision medicine
  • Analysis of longitudinal and time-series data to discover new correlations
  • Co-registration of patient data acquired over several time-points in their life
  • Identification of important metadata that has to be tracked over a longitudinal duration
  • Software platforms for enabling easy access to the patient’s medical and clinical history
  • Gap-handling in history-taking
  • Quality improvement and noise-handling on longitudinal data
  • Missing functionality in current clinical decision support systems using longitudinal data