This document summarizes a webinar titled "Human vs. Machine-Enhanced Scientific Discovery" hosted by Collaborative Drug Discovery, Inc. on September 21, 2016. It introduces the moderators and panelists which include experts from CDD, University of Miami, Stanford University, and biotech consultants. The webinar then discusses topics like semantic web, ontologies, controlled vocabularies, challenges of semantic annotation, and visions of future laboratory research. Resources like Protégé, BioPortal, CEDAR, BAO, LINCS, and DTO are also presented. Questions from attendees are addressed at the end.

1. Archive, Mine, Collaborate© 2016 Collaborative Drug Discovery, Inc.
“Human vs. Machine-Enhanced
Scientific Discovery”
Town Hall Webinar
September 21, 2016

2. Archive, Mine, Collaborate© 2016 Collaborative Drug Discovery, Inc.
Our Moderators
Kellan Gregory, CDD
Director of Product Excellence
Frank Cole, CDD
Head of Sales, Eastern USA

3. Archive, Mine, Collaborate© 2016 Collaborative Drug Discovery, Inc.
Our Panelists
Jan Kranz,
CDD Advocate and
biotech consultant.
Formerly of the Broad
Institute, ALS-TDI,
Proteome, Cubist
Stephan Schurer,
Associate Professor in the
Department of Pharmacology
and Director of Drug
Discovery at the Center for
Computational Science –
University of Miami
Mark Musen, Professor of
Biomedical Informatics and of
Biomedical Data
Science, Director of Biomedical
Informatics Research –
Stanford University

4. Archive, Mine, Collaborate© 2016 Collaborative Drug Discovery, Inc.
Semantic Web: provides a common framework that allows data to be shared and
reused across application, enterprise, and community boundaries". The term was
coined by Tim Berners-Lee for a web of data that can be processed by machines.
Ontology: the philosophical study of the nature of being, becoming, existence or
reality as well as the basic categories of being and their relations. Traditionally listed
as a part of the major branch of philosophy known as metaphysics, ontology often
deals with questions concerning what entities exist or may be said to exist and how
such entities may be grouped, related within a hierarchy, and subdivided according
to similarities and differences.
Controlled Vocabulary: provide a way to organize knowledge for subsequent
retrieval. They are used in subject indexing schemes, subject headings, thesauri,
taxonomies and other forms of knowledge organization systems. Controlled
vocabulary schemes mandate the use of predefined, authorized terms that have
been preselected by the designers of the schemes, in contrast to natural language
vocabularies, which have no such restriction.
Taken from Wikipedia

5. Archive, Mine, Collaborate© 2016 Collaborative Drug Discovery, Inc.
Mark Musen: Protégé
http://protege.stanford.edu/

6. Archive, Mine, Collaborate© 2016 Collaborative Drug Discovery, Inc.
http://bioportal.bioontology.org/
Mark Musen: BioPortal

7. Archive, Mine, Collaborate© 2016 Collaborative Drug Discovery, Inc.
https://metadatacenter.org/
Mark Musen: CEDAR

8. Archive, Mine, Collaborate© 2016 Collaborative Drug Discovery, Inc.
Stephan Schürer: BAO
http://bioassayontology.org/

9. Archive, Mine, Collaborate© 2016 Collaborative Drug Discovery, Inc.
Stephan Schürer: LINCS
http://www.lincsproject.org/

10. Archive, Mine, Collaborate© 2016 Collaborative Drug Discovery, Inc.
Stephan Schürer: DTO
http://drugtargetontology.org/about.html

11. Archive, Mine, Collaborate© 2016 Collaborative Drug Discovery, Inc.
Bioassay Express – 5HT1A Assay Annotated by
“Top 19 Common Assay Template Terms”

12. Archive, Mine, Collaborate© 2016 Collaborative Drug Discovery, Inc.
Ontology Branches
• Each annotation term is part of a
tree structure
• Inheritance provides extra layers
of meaning and relatedness
• From Common Assay Template +
ontologies (shown=BAO)
• Updated as ontologies are
extended or modified
(http://bioportal.bioontology.org)

13. Archive, Mine, Collaborate© 2016 Collaborative Drug Discovery, Inc.
Machine Learning Helps Curation
Existing data (3500 PubChem assays as of 9/1/16) used for learning:
proposed annotations from text
Natural
Language
Processing
Bayesian
Models

14. Archive, Mine, Collaborate© 2016 Collaborative Drug Discovery, Inc.
Browse
• Select primary category
• Toggle desired terms (or whole
classes)
• Select secondary category (etc)
• Retrieve assays, compounds…

15. Archive, Mine, Collaborate© 2016 Collaborative Drug Discovery, Inc.
Search
• Search using semantic terms
• Similar interface as annotation
Results ranked by using annotations
like fingerprints
http://www.bioassayexpress.com

16. Archive, Mine, Collaborate© 2016 Collaborative Drug Discovery, Inc.
What are the technical challenges to realizing the full
potential of semantically annotated scientific data?
- Making it painless for adoption?
- Social challenges too?

17. Archive, Mine, Collaborate© 2016 Collaborative Drug Discovery, Inc.
As the amount of public scientific data grows …
… the work becomes easier, harder or different?

18. Archive, Mine, Collaborate© 2016 Collaborative Drug Discovery, Inc.
What are the misunderstandings about semantic,
annotated scientific space…

19. Archive, Mine, Collaborate© 2016 Collaborative Drug Discovery, Inc.
MAIME
http://www.fged.org/projects/miame/

20. Archive, Mine, Collaborate© 2016 Collaborative Drug Discovery, Inc.
GEO
http://www.ncbi.nlm.nih.gov/geo/info/overview.html

21. Archive, Mine, Collaborate© 2016 Collaborative Drug Discovery, Inc.
Crystallography and PDB
http://www.crystallography.net/cod/index.php
http://www.wwpdb.org/

22. Archive, Mine, Collaborate© 2016 Collaborative Drug Discovery, Inc.
What do you imagine the future of lab research to be
in 10…15… years and beyond?

23. Archive, Mine, Collaborate© 2016 Collaborative Drug Discovery, Inc.
Questions?

24. Archive, Mine, Collaborate© 2016 Collaborative Drug Discovery, Inc.
Once again, Our Panelists
Jan Kranz,
CDD Advocate and
biotech consultant.
Formerly of the Broad
Institute, ALS-TDI,
Proteome, Cubist.
Stephan Schurer,
Associate Professor in the
Department of Pharmacology
and Director of Drug
Discovery at the Center for
Computational Science –
University of Miami
Mark Musen, Professor of
Biomedical Informatics and of
Biomedical Data
Science, Director of Biomedical
Informatics Research –
Stanford University

25. Archive, Mine, Collaborate© 2016 Collaborative Drug Discovery, Inc.
Visit our website or contact your
CDD representative for future
events!
https://www.collaborativedrug.com/blog/events

26. Archive, Mine, Collaborate© 2016 Collaborative Drug Discovery, Inc.
THANK YOU!