Introduction

The emerging field of translational biomedical informatics aims to develop innovative analytic methods and tools to transform large amount of biomedical and genomic data into meaningful clinical and biological knowledge. It will largely accelerate biomedical knowledge discovery and improve health services and patient care outcomes. To achieve the holly grail of translational biomedical informatics research, clinical observations and biological experiments should be analyzed holistically. Unfortunately, the huge volume of data of heterogeneous nature, and different cultures in biomedical research and clinical practice impose a severe obstacle – even bioinformatics and medical informatics (also called clinical informatics sometimes) remain as separate fields for long time. Methods, technologies and applications that build on biomedical and clinical data integration are in great need.

The broader context of the workshop includes artificial intelligence, information retrieval, machine learning, natural language processing, and integrative analysis of biological and clinical data. The purpose of this workshop is to provide a forum for researchers to share their research methodologies and tools on managing, analyzing, and discovering knowledge from diverse and complex biomedical and clinical data. Submissions are invited to address the needs for developing innovative methods and meaningful applications that can potentially lead to significant advances in translational biomedical informatics research.

Topics

The topics of interest include but not limited to:

• Application of data mining approaches in precision medicine
• Machine learning and statistical approaches for biomedical and clinical data mining
• Natural language processing in clinical data
• Information retrieval in clinical data
• Topic detection and information extraction in biomedical and clinical data
• Integration of heterogeneous biomedical data sources
• Semantic annotation on biomedical data
• Semantic reasoning and inference on biomedical data
• Biomedical data representation utilizing Ontology matching and data model schema
• Large-scale biomedical data management system
• Phenotypic-Genotypic association detection
• Network and Systems Biology
• Biomedical Network motif analysis
• Computational genetics, genomics and proteomics
• Computational drug discovery
• Computer-aided detection and diagnosis
• Pharmacogenomics
• Multi-omics data integration

Organizers

• Feichen Shen, Ph.D., Research Associate, Department of Health Sciences Research, Mayo Clinic(Program Committee Member for BIBM 2017)
• Yuji Zhang, Ph.D., Assistant Professor, Division of biostatistics and Bioinformatics, Department of Epidemiology and Public Health, University of Maryland School of Medicine
• Lixia Yao, PhD., Assistant Professor, Department of Health Sciences Research, Mayo Clinic
• Hongfang Liu, Ph.D., Professor, Department of Health Sciences Research, Mayo Clinic

Program committees:

• Sunghwan Sohn, Ph.D. (Mayo Clinic, USA)
• Yanshan Wang, Ph.D. (Mayo Clinic, USA)
• Sijia Liu (Mayo Clinic, USA)
• Liwei Wang, MD, Ph.D. (Mayo Clinic, USA)
• Dingcheng Li, Ph.D. (Baidu USA, USA)

Important Dates

Sept 20, 2017, 11:59 pm CST: Due date for full workshop papers submission

Oct 10, 2017: Notification of acceptance to authors

Oct 25 2017: Camera-ready of accepted papers

Nov 13-16, 2017: Workshops

Contact

Please email Workshop co-chair, Feichen Shen(shen.feichen@mayo.edu)