communicating systems biology - why and how we should do better in a digital world

ICBP Houston April 27, 2012

Communicating Systems Biology – Why and How We Should Do Better in a Digital World ?

Philip E. BourneUniversity of California San Diego

[email protected]://www.slideshare.net/pebourne/

mailto:[email protected]


Why We Should Do Better

• Discovery processes are increasingly complex and broad in scope

• Data must be connected more closely to the methods under study

• Science is an increasingly social endeavor

http://www.discoveryinformaticsinitiative.org/Yolanda Gil and Haym Hirsch

http://www.discoveryinformaticsinitiative.org/




Why We Should Do BetterThe Scientific Process is Too Slow to Respond to a Crisis – Either Global

or Personal

Motivation

http://knol.google.com/k/plos-currents-influenza#

By the time the paper is published we could all be dead

ICBP Houston April 27, 2012* http://www.cdc.gov/h1n1flu/estimates/April_March_13.htm

Jan. 2008 Jan. 2009 Jan. 2010Jul. 2009Jul. 2008 Jul. 2010

1RUZ: 1918 H1 Hemagglutinin

Structure Summary page activity forH1N1 Influenza related structures

3B7E: Neuraminidase of A/Brevig Mission/1/1918 H1N1 strain in complex with zanamivir

In a time of crisis the need for fast access to accurate data and any knowledge associatedwith that data are paramount

Motivation


If that is not enough…

For some people the scientific process may be too slow to save their life

Motivation


Josh Sommer – A Remarkable Young ManCo-founder & Executive Director the Chordoma Foundation

http://sagecongress.org/Presentations/Sommer.pdf

Motivation


Chordoma

• A rare form of brain cancer

• No known drugs• Treatment – surgical

resection followed by intense radiation therapy

Motivation

http://upload.wikimedia.org/wikipedia/commons/2/2b/Chordoma.JPG



Motivation

ICBP Houston April 27, 2012Motivation



http://fora.tv/2010/04/23/Sage_Commons_Josh_Sommer_Chordoma_Foundation

Motivation


Science is an Increasingly Social Endeavor

Witness the Story of Meredith


A Requirement is More Open ScienceBut ….


Openness is Misunderstood by Scientists

• Witness the confusion regarding open access

• Witness PubMed Central


What Are the Impediments to Open Science?

Change Reward

You don’t get tenure for starting a blog!


How Can We Do Better? …


How Can We Do Better?

• Better communication, data and knowledge access, and new modes of discovery, which means:– We need data and knowledge about that data to interoperate

i.e. we need new kinds of fast, versatile publications and data archives

– We need to be more open with both– We need to think more about the tools that analyze, visualize

and annotate data to maximize knowledge discovery– Reward systems need to change– We need scientist management and discovery tools– We need to be less fixated on the big data problems– We need to unleash the full power of the Internet

Easy Hard

Both Are Under Stress

• PubMed contains ~21M entries (May 2011)

• ~100,000 papers indexed per month

• In Feb 2009:– 67,406,898 interactive

searches were done– 92,216,786 entries were

viewed

• 1330 databases reported in NAR 2011

• MetaBase http://biodatabase.org reports 2,651 entries edited 12,587 times

PLoS Comp. Biol. 2005 1(3) e34

http://biodatabase.org/

Some More Comparisons

• Journals have a pretty standardized interface

• Journals have a business model

• The quality is declining as numbers increase (?)

• Audience believes they are sustainable

• Efforts to make the interfaces different!

• Little attempt at a business model compared to the Web 2.0 world

• Quality is increasing (?)• Not well sustained

PLoS Comp. Biol. 2008. 4(7): e1000136Databases versus journals

1. A link brings up figures from the paper

0. Full text of PLoS papers stored in a database

2. Clicking the paper figure retrievesdata from the PDB which is

analyzed

3. A composite view ofjournal and database

content results

We Need Data and Knowledge About That

Data to Interoperate

1. User clicks on content2. Metadata and

webservices to data provide an interactive view that can be annotated

3. Selecting features provides a data/knowledge mashup

4. Analysis leads to new content I can share

4. The composite view haslinks to pertinent blocks

of literature text and back to the PDB

1.

2.

3.

4.

The Knowledge and Data Cycle

PLoS Comp. Biol. 2005 1(3) e34


We Need Data and Knowledge About That Data to Interoperate – What is Stopping Us?

• Governance – publishers vs. database providers

• Reward• Metadata standards for provenance, privacy

etc.• Exemplars• ….

Caveat: Each discipline is different – I speak very much from a biomedicalsciences perspective

A Small Example - The World Wide Protein Data Bank

• The single worldwide repository for data on the structure of biological macromolecules

• Vital for drug discovery and the life sciences

• 41 years old• Free to all

http://www.wwpdb.org

We need data and knowledge about that data to interoperatePLoS Comp. Biol. 2005 1(3) e34 ICBP Houston April 27, 2012

The World Wide Protein Data Bank – The Best Case Scenario

• Paper not published unless data are deposited – strong data to literature correspondence

• Highly structured data conforming to extensive ontologies

• DOI’s assigned to every structure

http://www.wwpdb.org

We need data and knowledge about that data to interoperatePLoS Comp. Biol. 2005 1(3) e34 ICBP Houston April 27, 2012


www.rcsb.org/pdb/explore/literature.do?structureId=1TIM

Example Interoperability: The Database View

We need data and knowledge about that data to interoperateBMC Bioinformatics 2010 11:220


Example Interoperability: The Literature Viewhttp://biolit.ucsd.edu

Nucleic Acids Research 2008 36(S2) W385-389 We need data and knowledge about that data to interoperate

http://biolit.ucsd.edu/


Semantic Tagging & Widgets are a Powerful Tool to Integrate Data and Knowledge of that

Data, But as Yet Not Used Much

Will Widgets and Semantic Tagging Change Computational Biology? PLoS Comp. Biol. 6(2) e1000673

We need data and knowledge about that data to interoperate


Semantic Tagging of Database Content in The Literature or Elsewhere

http://www.rcsb.org/pdb/static.do?p=widgets/widgetShowcase.jspPLoS Comp. Biol. 6(2) e1000673Semantic Tagging


Where Will It All End?http://richard.cyganiak.de/2007/10/lod/lod-datasets_2010-09-22_colored.html


This is Literature Post-processingBetter to Get the Authors Involved

• Authors are the absolute experts on the content

• More effective distribution of labor

• Add metadata before the article enters the publishing process



Word Add-in for Authors

• Allows authors to add metadata as they write, before they submit the manuscript

• Authors are assisted by automated term recognition– OBO ontologies– Database IDs

• Metadata are embedded directly into the manuscript document via XML tags, OOXML format– Open– Machine-readable

• Open source, Microsoft Public License

http://www.codeplex.com/ucsdbiolit




Challenges

• Authors – Carrot IF one or more publishers fast tracked a

paper that had semantic markup it might catch on

• Publishers– Carrot Competitive advantage



The Promise – A Hypothetical Example

Immunology Literature

Cardiac DiseaseLiterature

Shared Function








Easy Hard


One Small Example of the Problem• jMol, VMD … are de facto

standard important tools for rendering biological molecules .. but

• They are not versatile ie do not for example:– Respond to the data they are

reading– Offer views that match the users

interests– Allow the user to annotate the

data– Allow those annotations to be

shared (published?)

Think More About the Tools

Github is Great But We Need Apps for Science

Computational Biology Resources Lack Persistence and Usability. PLoS Comp. Biol. 2008 4(7): e1000136


A Few Things to Accelerate the Rate of Scientific Discovery




and annotate data to maximize knowledge discovery– Reward systems need to change– We need scientist management tools– We need to be less fixated on the big data problems– We need to unleash the full power of the Internet

Easy Hard


Reward Systems Need to ChangeWhat is Needed?

• Author disambiguation• Auditing (identification and metrics) of all

scholarship - means new tools• Seniors need to promote alternative forms of

scholarship• Juniors need to respond

Reward Systems Need to Change

Ten Simple Rules for Getting Promoted as a Computational Biologist in Academia PLoS Comp Biol 2011 7(10 e1002001


What Are these Alternative Forms of Scholarship?

Research[Grants]

JournalArticle

ConferencePaper

PosterSession

Reviews

BlogsCommunity Service/Data

Curation


ICBP Houston April 27, 2012Reward Systems Need to Change


A Unique Identifier is Going to Happen

• It is DOIs for people• Some scientists will

resist• The winner is ORCID?


http://www.youtube.com/watch?v=29JewlGsYxs&feature=related


Ideally the ID will be Tagged to Every Piece of Scholarly Communication

I an Not a Scientist I am a NumberPLoS Comp. Biol. 2008 4(12) e1000247



One Solution: Use the Traditional Reward System in New Ways

The Wikipedia Experiment – Topic Pages

• Identify areas of Wikipedia that relate to the journal that are missing of stubs

• Develop a Wikipedia page in the sandbox

• Have a Topic Page Editor review the page

• Publish the copy of record with associated rewards

• Release the living version into Wikipedia







Easy Hard


The Truth About My Laboratory

• I have ?? mail folders!

• The intellectual memory of my laboratory is in those folders

• This is an unhealthy hub and spoke mentality

We Need Scientist Management Tools


The Truth About My Laboratory

• I generate way more negative that positive data, but where is it?

• Content management is a mess– Slides, posters…..– Data, lab notebooks ….– Collaborations, Journal clubs …

• Software is open but where is it?• Farewell is for the data too

Computational Biology Resources Lack Persistence and Usability. PLoS Comp. Biol. 2008 4(7): e1000136


http://artbyvida.com/portfolio.php


Many Great Tools Out There


Taverna


The Dream of Discovery Informatics

• At the end of the day a software agent reviews all of our labs electronic notebooks. Common themes and individual interests are extracted and searched against recent literature, public data, blogs, other social media and results returned and ranked for perusal next morning over coffee.






and annotate data to maximize knowledge discovery– Reward systems need to change– We need scientist management tools– We need to be less fixated on the big data problems– We need to unleash the full power of the Internet

Easy Hard

Yes YouTube Can Increase the Rate of Discovery

Unleash the full power of the Internet


The Lab ExperimentPaper+Rich Media

• My students enjoyed the experience• The shyest student was actually the most bold

in front of the camera• “We will become a generation of “science

castors”• They liked the exposure for the most part –

rather than the PI it puts them out in front



Organic Growth

• Some of their work viewed 20,000+ times• Global audience of researchers, educators and

academic/research institutions– 60,000 unique visitors & 2M pageviews/month– 16,000 registered users & 600 communities– 5,000 uploads of video content (about journal articles,

conferences, research news and classes)– Growing 4-5% monthly

• Sustainability - evolving a business model supporting journals and conferences

3 Years Laterwww.scivee.tv



Products

ApplicationProduct Primary Customers

Journals PubCast Journals, publishers, societies

Meetings PosterCast Societies, conference orgs.SlideCast

Comm. PaperCast Societies, journalsPodcastSlideCast

Education PosterCast Societies, universitiesSlideCast

Books BookCast Publishers, book sellers

What Emerged: SciveeCasts



AndroidiPhone

Windows Phone 7

Step 1presenter starts

PowerPoint

Step 2presenter starts

recording onsmart phone

Step 3presenter stops recording and

initiates upload

Slides

Website

Step 5slides and podcastare automatically

synchronizedSync FilePodcast

Step 6listener

plays back synchronized presentation

Proposal - The TeachU WorkflowMacPC

Step 4slides areuploaded


Acknowledgements• BioLit Team

– Lynn Fink– Parker Williams– Marco Martinez– Rahul Chandran– Greg Quinn

• MBT– John Moreland– John Beaver

• Microsoft Scholarly Communications– Pablo Fernicola– Lee Dirks– Savas Parastitidas– Alex Wade– Tony Hey

• wwPDB team– Andreas Prilc– Dimitris Dimitropoulos

• SciVee Team– Apryl Bailey– Leo Chalupa– Lynn Fink– Marc Friedman (CEO)– Ken Liu– Alex Ramos– Willy Suwanto– Ben Yukich

http://www.scivee.tv

http://biolit.ucsd.eduhttp//www.pdb.orghttp://www.codeplex.com/ucsdbiolit





Questions?

[email protected]

mailto:[email protected]


What Is Open Science

• Unrestricted access and reuse of scientific knowledge as found in the literature and elsewhere provided attribution is given

• Ditto the data, protocols, software etc. from which that knowledge is derived

• Something catalyzed by the Fourth Paradigm


What Motivates Me to Talk About Open Science?

• I am a domain (life) scientist not a computer or information scientist

• I have been co-directing a major open and freely accessible biological data source – the Protein Data Bank (PDB) for the past 11 years.

• Almost 6 years ago I co-founded and remain the founding Editor in Chief of the open access journal PLoS Computational Biology

• I co-founded SciVee.tv to disseminate science in new ways

• There must be a business model to enable persistence and growth


What Are the Promises of Open Science?

• To accelerate the rate of scientific discovery worldwide

• To enable contributions from a broader geographic and economic base

• To approach learning and comprehension in new ways

• To reach a broader audience including the general public


MBT Featureshttp://mbt.sdsc.edu

• Offer a framework not an end user application

• Responds to the data type• Support read write access• Encourages others to

write end user applications

• Discourages feature creep

Think More About the Tools

Immunome Research, 2007 3(1):3

Immunologists

MedicinalChemists

BMC Bioinformatics 2005, 6:21.