Bio-Ontologies (#bioontologieshttp://www.bio-ontologies.org.uk/) is an ISMB Community of Special Interest (COSI) that covers the latest and most innovative research in the application of ontologies and more generally the organisation, presentation and dissemination of knowledge in biomedicine and the life sciences. Join our mailing list and our slack team!  Have something to say? Tweet to @bioontologies or send an email to the organizers - bioontologies@gmail.com .

Bio-Ontologies will be in its 22nd year at ISMB/ECCB 2019, which will be held in Basel, Switzerland between July 21-25. Bio-ontologies strives to provide a vibrant environment for reporting novel methods and sharing experiences on the construction and application of ontologies in health care and the life sciences. The COSI offers a constructive environment to nurture discussion of innovative and scientifically sound work that range from preliminary to completed, from both young and experienced investigators alike. Bio-Ontologies participants also benefit from a strongly interdisciplinary setting, where ISMB attendees intermingle with members from American Medical Informatics Association (AMIA) and the W3C’s Healthcare and Life Sciences Community Group (HCLSCG), thereby increasing impact through broader dissemination and enabling new and exceptional collaborations. This year's event will be integrated into the main conference and will feature papers accepted for the ISMB proceedings.

Selected papers will be invited to submit an extended version of their manuscript to the bio-ontologies theme in the Journal of Biomedical Semantics.

Key Dates (as per ISMB deadlines)

 Submission Deadline April 11, 2019
 Late Poster Deadline  April 30, 2019
 Acceptance Notification May 2, 2019
 Late Poster Notification     May 21, 2019
 Program Information June 15, 2019
 Early Bird Registration June 20, 2019
 Bio-Ontologies track @ ISMB July 22-23, 2019
 Special Issue deadline October 1, 2019


Keynotes: 

Speaker: Ioannis Xenarios

Title: Knowledge graph and computable models

Knowledge graph and computable models are becoming entities that tries to capture the complexity of biological systems and encode this information into a structure that is reusable and linkable. Cellular models used in systems biology have emerged over the last decade as useful media to map, compute and sometimes predict in-silico cellular behavior. The presentation will tackle with a set of examples how computable models requires accurate and community maintained ontologies. The emergence as well of linked data being an essential component of this eco-system.

Bio: Ioannis Xenarios holds a PhD in immunology from the Ludwig Institute for Cancer Research (LICR) and the Biochemistry department from the University of Lausanne. He has been trained on profile/prosite method for domain detection in proteins by Dr Philipp Bucher and Roland Luethy as an undergrad student and after his PhD went in the computational structural biology laboratory of Prof David Eisenberg where he created with his colleague at UCLA the first database of interacting proteins (DIP). He then moved to an industrial position at Serono /Merck-Serono where he hold several positions in domain ranging from genomics to systems-immunology oriented activities. For 11 years he was part of the SIB Swiss Institute of Bioinformatics where he led the Swiss-Prot part of the UniProt consortium and the Vital-IT competence center. Since 2019 he is leading a systems immunology modeling actiivities within the LICR and the Data Analysis Platform of the Health2030 Genome Center. He is a professor at the Center for Integrative Genomics of the University of Lausanne and a Professor of Chemistry/Biochemistry at the University of Geneva.


Speaker: Helena Deus

Title: A Knowledge Graph for Health: can graphs really save lives? 

Weaving a web of reliable health knowledge has never been more important - as machine learning automation replaces computational health care tasks that used to be performed by hospital staff, the datasets used to train them need to be complete, reliably updated, clean and unbiased. The primary source of that data are hospital electronic health records and related physician’s notes. Yet the rise of cell therapies, precision medicine and wearable medical devices has created another, highly relevant source of data for that automation - detailed measurements of genetic, metabolic and environmental data. Whereas these have been repeatedly shown to significantly impact diagnosis and treatment, providers of such services will face an uphill battle until their data is available to the patient in an interoperable format. One of the formats supported by FHIR, the health interoperability standard recommended by HL7, is RDF. Knowledge graphs are therefore set to play an increasingly important role not only as the interfaces connecting data from wearables and diagnostic tests to the patient ecosystem, but also as sources of data for training machine learning models that can identify the best treatment given the patient’s information. This talk will describe a few of the challenges - and the solutions - that staff at Elsevier has come across while using an expert curated knowledge graph and machine learning for enabling precision medicine. 

Bio: Helena Deus received her PhD in Bioinformatics from Lisbon University (UNL) where she focused on Linked Data and Semantic Web applications for Health Care and Life Sciences, with an emphasis on Cancer Research. Helena is passionate about applying data science to improving healthcare – in particular for oncology. She works for Elsevier as technology research director and is leading the effort to build a knowledge graph for health. Prior to joining Elsevier, Helena's roles included directing a data science team at Foundation Medicine and leading the Health Care and Life Sciences strategy at the Digital Enterprise Research Institute.





Call for Submissions

We invite the submission of short papers, flash updates and posters for presentation at the Bio-Ontologies. Papers are invited in the following three areas:

1. The development of biological and biomedical ontologies to represent and structure knowledge.

2. Ontology-focused tools and methods (e.g. ontology engineering, ontology alignment, biocuration, information extraction, text mining, data integration) featuring biological use cases.

3. Biological applications of ontologies (e.g. ontologies use in data mining, machine learning, visualization, knowledge graphs, semantic query answering)


Deadlines and Presentation Length

We welcome short research papers (4 pages), flash updates (1 page) and poster abstracts (1 page) as a PDF using the Bio-ontologies template for papers (https://goo.gl/KD7Bmi) or updates/posters (https://goo.gl/1OkQSH). Submissions can be made on the easychair site. Please note that accepted submissions require that one author register for the conference and present the work. The presenter should identify themselves as the corresponding author during the submission process. The research presentations are normally allocated between 20 minutes while flash updates are presented in 5-10 minutes. 

Review Criteria

  1. Relevance, interest, and value of the topic to conference attendees.
  2. Significance of the problem, such that reviewers understand that it is a problem that is important and worth solving.
  3. Novelty of the approach, including critical discussion of related work.
  4. Soundness and potential for reproducibility of the study and/or methods.
  5. Quality of writing, including readability and clearly stated contribution(s)


Organizing Committee

Previous Meetings

Chicago (2018), Prague (2017), Orlando (2016), Dublin (2015), Boston (2014), Berlin (2013), Long Beach (2012), Vienna (2011), Boston (2010), Stockholm (2009), Toronto (2008), Vienna (2007), Fortaleza (2006), Detroit (2005), Glasgow (2004), Brisbane (2003), Edmonton (2002), Copenhagen (2001), San Diego (2000), Heidelberg (1999), Montreal (1998).


Feedback

Have suggestions for this year? We'd love to hear from you at bioontologies@gmail.com