• Share
  • Email
  • Embed
  • Like
  • Save
  • Private Content
Ismb2009
 

Ismb2009

on

  • 724 views

 

Statistics

Views

Total Views
724
Views on SlideShare
713
Embed Views
11

Actions

Likes
0
Downloads
1
Comments
0

3 Embeds 11

http://www.linkedin.com 8
https://www.linkedin.com 2
http://www.slideshare.net 1

Accessibility

Categories

Upload Details

Uploaded via as Adobe PDF

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

    Ismb2009 Ismb2009 Presentation Transcript

    • From Proteins to Hypotheses: Some Experiments in Semantic Enrichment Anita de Waard Principal Researcher, Disruptive Technologies Elsevier Labs, Amsterdam Utrecht Institute of Linguistics, University Utrecht The Netherlands a.dewaard@elsevier.com
    • Some Experiments in Semantic Enrichment
    • Some Experiments in Semantic Enrichment Entities and Relationships: FEBS Structured Digital Abstracts OKKAM Entity Repository
    • Some Experiments in Semantic Enrichment Entities and Relationships: FEBS Structured Digital Abstracts OKKAM Entity Repository Hypotheses and Evidence: Discourse Analysis of Biology Articles Hypotheses, Evidence and Relationships
    • Some Experiments in Semantic Enrichment Entities and Relationships: FEBS Structured Digital Abstracts OKKAM Entity Repository Hypotheses and Evidence: Discourse Analysis of Biology Articles Hypotheses, Evidence and Relationships Collaborations: Elsevier Grand Challenge Future of Research Communications
    • Entities and Relationships
    • FEBS Letters Structured Digital Abstracts - With FEBS Letters Editorial Office in Heidelberg; and MINT database Rome - SDA [Gerstein et. al]: ‘machine-readable XML summary of pertinent facts’ - For each ppi paper: proteins, protein-protein interactions, methods: provided by author in XLS - Started April 9, 2008: in ScienceDirect links to MINT and Uniprot - Now 117 articles with SDA: http://www.febsletters.org/content/sda - Being used as Gold Standard for Biocreative Challenge II.5 http://www.biocreative.org/tasks/biocreative-ii5/biocreative-ii5-evaluation/
    • expression of GSG1 stimulates TPAP targeting to the ER, suggesting that interactions between the two proteins lead to the redistribution of TPAP from the cytosol to the ER. MINT-6168263: Gsg1 (uniprotkb:Q8R1W2), TPAP (uniprotkb:Q9WVP6) and Calmegin (uniprotkb:P52194) colocalize (MI:0403) by cosedimentation (MI:0027) MINT-6168204, MINT-6168178: Gsg1 (uniprotkb:Q8R1W2) and TPAP (uniprotkb:Q9WVP6) colocalize (MI:0403) by fluorescence microscopy (MI:0416) MINT-6167930: Gsg1 (uniprotkb:Q8R1W2) physically interacts (MI:
    • expression of GSG1 stimulates TPAP targeting to the ER, suggesting that interactions between the two proteins lead to the redistribution of TPAP from the cytosol to the ER. MINT-6168263: Gsg1 (uniprotkb:Q8R1W2), TPAP (uniprotkb:Q9WVP6) and Calmegin (uniprotkb:P52194) colocalize (MI:0403) by cosedimentation (MI:0027) MINT-6168204, MINT-6168178: Gsg1 (uniprotkb:Q8R1W2) and TPAP (uniprotkb:Q9WVP6) colocalize (MI:0403) by fluorescence microscopy (MI:0416) MINT-6167930: Gsg1 (uniprotkb:Q8R1W2) physically interacts (MI:
    • expression of GSG1 stimulates TPAP targeting to the ER, suggesting that interactions between the two proteins lead to the redistribution of TPAP from the cytosol to the ER. MINT-6168263: Gsg1 (uniprotkb:Q8R1W2), TPAP (uniprotkb:Q9WVP6) and Calmegin (uniprotkb:P52194) colocalize (MI:0403) by cosedimentation (MI:0027) MINT-6168204, MINT-6168178: Gsg1 (uniprotkb:Q8R1W2) and TPAP (uniprotkb:Q9WVP6) colocalize (MI:0403) by fluorescence microscopy (MI:0416) MINT-6167930: Gsg1 (uniprotkb:Q8R1W2) physically interacts (MI:
    • expression of GSG1 stimulates TPAP targeting to the ER, suggesting that interactions between the two proteins lead to the redistribution of TPAP from the cytosol to the ER. MINT-6168263: Gsg1 (uniprotkb:Q8R1W2), TPAP (uniprotkb:Q9WVP6) and Calmegin (uniprotkb:P52194) colocalize (MI:0403) by cosedimentation (MI:0027) MINT-6168204, MINT-6168178: Gsg1 (uniprotkb:Q8R1W2) and TPAP (uniprotkb:Q9WVP6) colocalize (MI:0403) by fluorescence microscopy (MI:0416) MINT-6167930: Gsg1 (uniprotkb:Q8R1W2) physically interacts (MI:
    • expression of GSG1 stimulates TPAP targeting to the ER, suggesting that interactions between the two proteins lead to the redistribution of TPAP from the cytosol to the ER. MINT-6168263: Gsg1 (uniprotkb:Q8R1W2), TPAP (uniprotkb:Q9WVP6) and Calmegin (uniprotkb:P52194) colocalize (MI:0403) by cosedimentation (MI:0027) MINT-6168204, MINT-6168178: Gsg1 (uniprotkb:Q8R1W2) and TPAP (uniprotkb:Q9WVP6) colocalize (MI:0403) by fluorescence microscopy (MI:0416) MINT-6167930: Gsg1 (uniprotkb:Q8R1W2) physically interacts (MI:
    • OKKAM Project FP7 - EU funded project, 13 partners, 2008 - 2010 - Main goal: create entity identifier repository - Create entity-centric architecture: - create new entities + synonyms where needed - offer interface/link where not needed - contain resolver, matcher, repository - E.g. http://sig.ma - semantic mashup of entity properties
    • http://sig.ma/search?q=p53
    • OKKAM Entity-centric authoring tool Current: - Build MS Word plugin to find proteins in FEBS articles (i.e., semi-automating FEBS SDA!) - Now: testing web server interface to Whatizit Next: link to Biocreative metaserver - Add: links to other entities via OKKAM server - Prototype now being tested with FEBS Office Future: - Create unique Author ID, straddling proprietary (Scopus) and other (ResearcherID, OpenID) systems - Allow query and resolution of authors/papers within Word
    • OKKAM Entity Editor in MS Word
    • OKKAM Entity Editor in MS Word
    • OKKAM Entity Editor in MS Word
    • OKKAM Entity Editor in MS Word
    • OKKAM plugin vs. UCSD group Plugin UCSD plugin Okkam plugin Works! Can be Prototype, starting to test with downloaded, open source FEBS authors etc. Offline: load ontologies Online: call out to web services locally (soon...) Identify classes of entities Identify specific entities (e.g., a (e.g., ‘inhibitor’) specific protein) Works with other version of Word Works with Word 2007 (on a PC!) Stores annotations as XML Store annotations as Word metadata - maintain comments - can generate report metadata in Word info pane of entitieslinked to identifiers Work well together!
    • OKKAM plugin vs. UCSD group Plugin UCSD plugin Okkam plugin Works! Can be Prototype, starting to test with downloaded, open source FEBS authors etc. Offline: load ontologies Online: call out to web services locally (soon...) Identify classes of entities Identify specific entities (e.g., a (e.g., ‘inhibitor’) specific protein) Works with other version of Word Works with Word 2007 (on a PC!) Stores annotations as XML Store annotations as Word metadata - maintain comments - can generate report metadata in Word info pane of entitieslinked to identifiers Work well together!
    • Hypotheses and Evidence
    • Issue with Biocreative challenge: From one of the documents in the training set: - In Xenopus oocyte maturation, cytoplasmic polyadenylation mediated by cytoplasmic polyadenylation element binding protein (CPEB) induces the translation of maternal mRNA [5]. - In mouse testis, another novel member of the CPEB protein family (CPEB2) and a homolog of xGLD-2 (mGLD-2) have been identified [7] and [8] versus: - TPAP was present in GSG1 immunoprecipitates (Fig. 2B). The in vivo data suggest that TPAP–GSG1 interactions occur in mammalian cells. Issue 1: what is experimentally verified content? Issue 2: what is new?
    • Discourse analysis of biological text
    • Discourse analysis of biological text - How can we identify line of argumentation in biology text?
    • Discourse analysis of biological text - How can we identify line of argumentation in biology text?
    • Discourse analysis of biological text - How can we identify line of argumentation in biology text? - Liguistics says: parse into clauses (anything with a verb)
    • Discourse analysis of biological text - How can we identify line of argumentation in biology text? - Liguistics says: parse into clauses (anything with a verb) - Identify Discourse Segment Purpose
    • Discourse analysis of biological text - How can we identify line of argumentation in biology text? - Liguistics says: parse into clauses (anything with a verb) - Identify Discourse Segment Purpose - Identify verb tense, type, markers for each segment type
    • Discourse analysis of biological text - How can we identify line of argumentation in biology text? - Liguistics says: parse into clauses (anything with a verb) - Identify Discourse Segment Purpose - Identify verb tense, type, markers for each segment type
    • Discourse analysis of biological text - How can we identify line of argumentation in biology text? - Liguistics says: parse into clauses (anything with a verb) - Identify Discourse Segment Purpose - Identify verb tense, type, markers for each segment type
    • 3 Realms of Science: Conceptual realm Experimental realm Data realm
    • 3 Realms of Science: (1) Oncogene-induced senescence is (4b) transduction with either Conceptual characterized by the appearance of miR-Vec-371&2 or miR-Vec- V12 cells with a flat morphology that 373 prevents RAS - realm express senescence associated (SA)- induced growth arrest in -Galactosid a s e . primary human cells. (2a) Indeed, (4a) Altogether, these data show that Experimental realm V12 (2b) control RAS -arrested (3b) very few cells showed cells showed relatively high senescent morphology when (3a) Consistent abundance of flat cells transduced with either miR- with the cell expressing SA- - Vec-371&2, miR-Vec-373, or growth assay, kd Galactosidase control p53 . (2c) (Figures 2G and 2H). Data realm (Figures)
    • 3 Realms of Science: (1) Oncogene-induced senescence is (4b) transduction with either Conceptual characterized by the appearance of miR-Vec-371&2 or miR-Vec- V12 cells with a flat morphology that 373 prevents RAS - realm express senescence associated (SA)- induced growth arrest in -Galactosid a s e . primary human cells. (2a) Indeed, (4a) Altogether, these data show that Experimental realm V12 (2b) control RAS -arrested (3b) very few cells showed cells showed relatively high senescent morphology when (3a) Consistent abundance of flat cells transduced with either miR- with the cell expressing SA- - Vec-371&2, miR-Vec-373, or growth assay, kd Galactosidase control p53 . (2c) (Figures 2G and 2H). Data realm (Figures)
    • Hypotheses ‘erode’ into facts:
    • Hypotheses ‘erode’ into facts: KnownFact KnownFact Concepts
    • Hypotheses ‘erode’ into facts: To investigate the possibility that miR-372 and miR-373 suppress the expression of LATS2, we... KnownFact KnownFact Concepts Hypothesis
    • Hypotheses ‘erode’ into facts: To investigate the possibility that miR-372 and miR-373 suppress the expression of LATS2, we... KnownFact KnownFact Concepts Hypothesis Goal Method Result Data Experiment 1
    • Hypotheses ‘erode’ into facts: To investigate the possibility that miR-372 and miR-373 suppress the expression of LATS2, we... Therefore, these results point to LATS2 as a mediator of the miR-372 and miR-373 effects on cell proliferation and tumorigenicity, KnownFact KnownFact Concepts Hypothesis Implication Goal Method Result Data Experiment 1
    • Hypotheses ‘erode’ into facts: To investigate the possibility that miR-372 and miR-373 suppress the expression of LATS2, we... Therefore, these results point to LATS2 as a mediator of the miR-372 and miR-373 effects on cell proliferation and tumorigenicity, KnownFact KnownFact Concepts Hypothesis Implication Goal Goal Method Result Method Result Data Data Experiment 1 Experiment 2
    • Hypotheses ‘erode’ into facts: To investigate the possibility that miR-372 and miR-373 suppress the expression of LATS2, we... Raver-Shapira et.al, JMolCell 2007 Therefore, these results point to two miRNAs, miRNA-372 and-373, function as LATS2 as a mediator of the miR-372 and potential novel oncogenes in testicular germ cell miR-373 effects on cell proliferation and tumors by inhibition of LATS2 expression, tumorigenicity, which suggests that Lats2 is an important tumor suppressor (Voorhoeve et al., 2006). KnownFact KnownFact Concepts Hypothesis Implication Fact Goal Goal Method Result Method Result Data Data Experiment 1 Experiment 2
    • Hypotheses ‘erode’ into facts: Yabuta, JBioChem 2007 miR-372 and miR-373 target the Lats2 tumor suppressor To investigate the possibility that (Voorhoeve et al., 2006) miR-372 and miR-373 suppress the expression of LATS2, we... Raver-Shapira et.al, JMolCell 2007 Therefore, these results point to two miRNAs, miRNA-372 and-373, function as LATS2 as a mediator of the miR-372 and potential novel oncogenes in testicular germ cell miR-373 effects on cell proliferation and tumors by inhibition of LATS2 expression, tumorigenicity, which suggests that Lats2 is an important tumor suppressor (Voorhoeve et al., 2006). KnownFact KnownFact Concepts Hypothesis Implication Fact Goal Goal Method Result Method Result Data Data Experiment 1 Experiment 2
    • Hypotheses ‘erode’ Hypothesis + into facts: Yabuta, JBioChem 2007 miR-372 and miR-373 target the Lats2 tumor suppressor To investigate the possibility that Evidence (Voorhoeve et al., 2006) miR-372 and miR-373 suppress the expression of LATS2, we... Raver-Shapira et.al, JMolCell 2007 Therefore, these results point to two miRNAs, miRNA-372 and-373, function as LATS2 as a mediator of the miR-372 and potential novel oncogenes in testicular germ cell miR-373 effects on cell proliferation and tumors by inhibition of LATS2 expression, tumorigenicity, which suggests that Lats2 is an important tumor suppressor (Voorhoeve et al., 2006). KnownFact KnownFact Concepts Hypothesis Implication Fact Goal Goal Method Result Method Result Data Data Experiment 1 Experiment 2
    • Identification of hypotheses in papers: SWAN Alzheimer KB
    • Identification of hypotheses in papers: SWAN Alzheimer KB
    • Identification of hypotheses in papers: SWAN Alzheimer KB
    • HypER Working Group: - Goal: Align and expand existing efforts on detection and analysis of Hypotheses, Evidence & Relationships - Partners: - Harvard/MGH: SWAN, ARF - Open University: Cohere - Oxford University: CiTO, eLearning/Rhetoric - DERI: SALT, aTags - University of Trento: LiquidPub - Xerox Research: XIP hypothesis identifier - U Tilburg: ML for Science - Elsevier, UUtrecht: Discourse analysis of biology
    • HypER Working Group: - Goal: Align and expand existing efforts on detection and analysis of Hypotheses, Evidence & Relationships - Partners: - Harvard/MGH: SWAN, ARF - Open University: Cohere - Oxford University: CiTO, eLearning/Rhetoric - DERI: SALT, aTags - University of Trento: LiquidPub - Xerox Research: XIP hypothesis identifier - U Tilburg: ML for Science - Elsevier, UUtrecht: Discourse analysis of biology
    • HypER Working Group: - Goal: Align and expand existing efforts on detection and analysis of Hypotheses, Evidence & Relationships - Partners: - Harvard/MGH: SWAN, ARF - Open University: Cohere - Oxford University: CiTO, eLearning/Rhetoric - DERI: SALT, aTags - University of Trento: LiquidPub - Xerox Research: XIP hypothesis identifier - U Tilburg: ML for Science - Elsevier, UUtrecht: Discourse analysis of biology
    • HypER Working Group: - Goal: Align and expand existing efforts on detection and analysis of Hypotheses, Evidence & Relationships - Partners: - Harvard/MGH: SWAN, ARF - Open University: Cohere - Oxford University: CiTO, eLearning/Rhetoric - DERI: SALT, aTags - University of Trento: LiquidPub - Xerox Research: XIP hypothesis identifier - U Tilburg: ML for Science - Elsevier, UUtrecht: Discourse analysis of biology
    • HypER Working Group: - Goal: Align and expand existing efforts on detection and analysis of Hypotheses, Evidence & Relationships - Partners: - Harvard/MGH: SWAN, ARF - Open University: Cohere - Oxford University: CiTO, eLearning/Rhetoric - DERI: SALT, aTags - University of Trento: LiquidPub - Xerox Research: XIP hypothesis identifier - U Tilburg: ML for Science - Elsevier, UUtrecht: Discourse analysis of biology
    • HypER Working Group: - Goal: Align and expand existing efforts on detection and analysis of Hypotheses, Evidence & Relationships - Partners: - Harvard/MGH: SWAN, ARF - Open University: Cohere - Oxford University: CiTO, eLearning/Rhetoric - DERI: SALT, aTags - University of Trento: LiquidPub - Xerox Research: XIP hypothesis identifier - U Tilburg: ML for Science - Elsevier, UUtrecht: Discourse analysis of biology
    • HypER Working Group: - Goal: Align and expand existing efforts on detection and analysis of Hypotheses, Evidence & Relationships - Partners: - Harvard/MGH: SWAN, ARF - Open University: Cohere - Oxford University: CiTO, eLearning/Rhetoric - DERI: SALT, aTags - University of Trento: LiquidPub - Xerox Research: XIP hypothesisHypothesis 22: Intramembrenous Aβ dimer may be toxic identifier - U Tilburg: ML for Science Derived from: POSTAT_CONTRIBUTION(This essay explo possibility that a fraction of these Abeta peptides never leav - Elsevier, UUtrecht: Discourse analysis of biology
    • HypER Activities: http://hyper.wik.is Current activities: - Aligning discourse ontologies: joint task with W3C HCLSSig - Aligning architectures to exchange hypotheses + evidence - Format for a rhetorical conference paper (SALT + abcde) - Parser comparison of hypothesis identification tools - With NIF+SWAN/SCF: Structured Rhetorical Abstracts for Neuroscience publications Further interests: - Better structure of evidence: MyExperiment, KeFeD, ... - Granularity of annotation/access: entity, hypothesis, discussion? - Where/how annotate: http://saakm2009.semanticauthoring.org/
    • Collaborations
    • Scope: Tools and processes to: - Improve the process of creating, reviewing and editing scientific content - Interpret, visualize or connect science knowledge - Provide tools/ideas for measuring the impact of these improvements. June 2008: 71 Submissions from 15 countries. August 2008: 10 Semi-finalists teams, access to: - 500,000 full text articles - Plus EMTREE, EmBase, Scopus - Created tool/demo - Presented to the Judges - Wrote a paper (accepted for JWeb Semantics) April 2009: Judges selected 4 Finalist teams. And the winners are:
    • Scope: Tools and processes to: - Improve the process of creating, reviewing and editing scientific content 2 Related Work - Interpret, visualize or connect science knowledge Using link text for summarisation has been explo - Provide tools/ideas for measuring the impact of these previously by Amitay and Paris (2000). They ide improvements. fied situations when it was possible to generate su June 2008: 71 Submissions from 15 countries. maries of web-pages by recycling human-autho descriptions of links from anchor text. In our wo August 2008: 10 Semi-finalists teams, access to: we use the anchor text as the reading context to p - 500,000 full text articles vide an elaborative summary for the linked do - Plus EMTREE, EmBase, Scopus ment. Our work is similar in domain to that of the 2 - Created tool/demo CLEF WiQA shared task.4 However, in contras - Presented to the Judges our application scenario, the end goal of the sha - Wrote a paper (accepted for JWeb Semantics) task focuses on suggesting editing updates fo April 2009: Judges selected 4 Finalist teams. particular document and not on elaborating on user’s reading context. And the winners are: A related task was explored at the Document
    • Scope: Tools and processes to: - Improve the process of creating, reviewing and editing scientific content 2 Related Work - Interpret, visualize or connect science knowledge Using link text for summarisation has been explo - Provide tools/ideas for measuring the impact of these previously by Amitay and Paris (2000). They ide improvements. fied situations when it was possible to generate su June 2008: 71 Submissions from 15 countries. maries of web-pages by recycling human-autho descriptions of links from anchor text. In our wo August 2008: 10 Semi-finalists teams, access to: we use the anchor text as the reading context to p - 500,000 full text articles vide an elaborative summary for the linked do - Plus EMTREE, EmBase, Scopus ment. Our work is similar in domain to that of the 2 - Created tool/demo CLEF WiQA shared task.4 However, in contras - Presented to the Judges our application scenario, the end goal of the sha - Wrote a paper (accepted for JWeb Semantics) task focuses on suggesting editing updates fo April 2009: Judges selected 4 Finalist teams. particular document and not on elaborating on user’s reading context. And the winners are: A related task was explored at the Document
    • Scope: Tools and processes to: - Improve the process of creating, reviewing and editing scientific content 2 Related Work - Interpret, visualize or connect science knowledge Using link text for summarisation has been explo - Provide tools/ideas for measuring the impact of these previously by Amitay and Paris (2000). They ide improvements. fied situations when it was possible to generate su June 2008: 71 Submissions from 15 countries. maries of web-pages by recycling human-autho descriptions of links from anchor text. In our wo August 2008: 10 Semi-finalists teams, access to: we use the anchor text as the reading context to p - 500,000 full text articles vide an elaborative summary for the linked do - Plus EMTREE, EmBase, Scopus ment. Our work is similar in domain to that of the 2 - Created tool/demo CLEF WiQA shared task.4 However, in contras - Presented to the Judges our application scenario, the end goal of the sha - Wrote a paper (accepted for JWeb Semantics) task focuses on suggesting editing updates fo April 2009: Judges selected 4 Finalist teams. particular document and not on elaborating on user’s reading context. And the winners are: A related task was explored at the Document
    • Scope: Tools and processes to: - Improve the process of creating, reviewing and editing scientific content 2 Related Work - Interpret, visualize or connect science knowledge Using link text for summarisation has been explo - Provide tools/ideas for measuring the impact of these previously by Amitay and Paris (2000). They ide improvements. fied situations when it was possible to generate su June 2008: 71 Submissions from 15 countries. maries of web-pages by recycling human-autho descriptions of links from anchor text. In our wo August 2008: 10 Semi-finalists teams, access to: we use the anchor text as the reading context to p - 500,000 full text articles vide an elaborative summary for the linked do - Plus EMTREE, EmBase, Scopus ment. Our work is similar in domain to that of the 2 - Created tool/demo CLEF WiQA shared task.4 However, in contras - Presented to the Judges our application scenario, the end goal of the sha - Wrote a paper (accepted for JWeb Semantics) task focuses on suggesting editing updates fo April 2009: Judges selected 4 Finalist teams. particular document and not on elaborating on user’s reading context. And the winners are: A related task was explored at the Document
    • Harvard, Fall 2010 FoRC: The Future of Research Communication Improve ways to: - create, review, edit scientific content - interpret, visualize, connect scientific knowledge - measure the impact of these improvements - present new paradigms in publishing - serve global academic knowledge communities - communicate between collaboratories - share research data - support complex knowledge ecosystems.
    • Harvard, Fall 2010 FoRC: The Future of Research Communication Improve ways to: - create, review, edit scientific content - interpret, visualize, connect scientific knowledge - measure the impact of these improvements - present new paradigms in publishing - serve global academic knowledge communities - communicate between collaboratories - share research data - support complex knowledge ecosystems. New ways of communicating science requires new ways of communicating Conference registrants form a community: - Website is their meeting place, continues as long as users want to - The physical conference is synchronous manifestation of the community - Others can participate through a virtual environment at other time/place
    • Acknowledgments HypER: - Funding: - Harvard/MGH: FP7-Cordis Tim Clark NWO Casimir Project Elizabeth Wu - UUtrecht: - DERI: Leen Breure, Siegfried Handschuh Tudor Groza Henk Pander Maat Matthias Samwald Ted Sanders Paul Buitelaar - ISI: - Xerox Research: Gully Burns Agnes Sandor Ed Hovy - Open University: - Elsevier: Simon Buckingham Shum David Marques David Shotton Darin McBeath Jack Park Stefano Bocconi Clara Mancini Adriaan Klinkenberg Emilie Marcus - Oxford University: Annamaria Carusi - Challenge judges and participants: David Shotton EMBL Team, CMU Team David Shotton - Tilburg U: Piroska Lendvai Alfonso Valencia