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What WikiCite can learn from biomedical citation networks--Wikicite2017--2017-05-22

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This is a quick, high-level tour of some ideas from evidence-based medicine, citation-related ontologies for argumentation and evidence curation and biomedicine.

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What WikiCite can learn from biomedical citation networks--Wikicite2017--2017-05-22

  1. 1. What WikiCite can learn from biomedical citation networks Jodi Schneider WikiCite, 2017-05-22 jschneider@pobox.com http://jodischneider.com/jodi.html @jschneider
  2. 2. My hats • Librarian now: Professor of future librarians and info managers • Ontologist • Journal editor/founder (not quite a publisher!) co-founder of open access Code4Lib Journal c. 2007 • Researcher scholarly communication, Biomedical informatics, Linked Data, argumentation, Computer-Supported Collaboration, Wikipedia • Wikipedian mainly EN.WP, EN.WikiQuote • User acawiki.org (Community Manager c. 2009) bibliographic management software articles, books, etc. in many, many fields
  3. 3. Acawiki.org
  4. 4. Which evidence do we take into account for a given purpose?
  5. 5. Hierarchy of Evidence Figure credit: SUNY Downstate Medical Center. Medical Research Library of Brooklyn. Evidence Based Medicine Course. A Guide to Research Methods: The Evidence Pyramid: http://library.downstate.edu/EBM2/2100.htm
  6. 6. BUT: we cannot judge evidence in isolation.
  7. 7. Approaches include: • Appraisal
  8. 8. Approaches include: • Appraisal • Aggregation Figure credit: Forest plot from Underhill, Kristen, Paul Montgomery, and Don Operario. "Sexual abstinence only programmes to prevent HIV infection in high income countries: systematic review." BMJ 335.7613 (2007): 248.
  9. 9. Figure credit: Duke University Medical Center Library. Introduction to Evidence-based Practice. What is Evidence-Based Practice (EBP)? http://guides.mclibrary.duke.edu/c.php?g=158201&p=1036021 • Appraisal • Aggregation • Contextualization Approaches include:
  10. 10. How trustworthy and valid is a given scientific “fact”?
  11. 11. How fragile is this knowledge?
  12. 12. What supports it? What holds it up? By Biochem1 (Own work) CC BY-SA 3.0 via Wikimedia Commons https://commons.wikimedia.org/wiki/File:‫.جنگا_ست_یک‬JPG
  13. 13. Can it be shored up? By Biochem1 (Own work) CC BY-SA 3.0 via Wikimedia Commons https://commons.wikimedia.org/wiki/Category:Jenga#/media/File: ‫.جنگا‬JPG
  14. 14. Do citations show the lineage of an idea?
  15. 15. {{Existing “facts”}} + {{New “facts”}}
  16. 16. {{Existing “facts”}} + {{New “facts”}} {{Stuff you cite}}
  17. 17. Examples from discussion sections of reports of Randomized Controlled Trials
  18. 18. “This” work agrees with… • “This is in accordance with earlier studies in the ambulatory surgical setting [3]” - PMC1637100 Jodi Schneider, Graciela Rosemblat, Shabnam Tafreshi and Halil Kilicoglu. Rhetorical moves and audience considerations in the discussion sections of Randomized Controlled Trials of health interventions. To be presented at European Conference on Argumentation, June 2017
  19. 19. Definitions and background info • “Self-efficacy, which may relate to motivation, is the perceived confidence in one's ability to accomplish a specific task [19].” - PMC2194735 Jodi Schneider, Graciela Rosemblat, Shabnam Tafreshi and Halil Kilicoglu. Rhetorical moves and audience considerations in the discussion sections of Randomized Controlled Trials of health interventions. To be presented at European Conference on Argumentation, June 2017
  20. 20. Presenting a range of evidence • “Except in one study [20], short-term administration of GH transiently worsened insulin resistance [19,53] and increased fasting glucose levels [53].” - PMC1865086 Jodi Schneider, Graciela Rosemblat, Shabnam Tafreshi and Halil Kilicoglu. Rhetorical moves and audience considerations in the discussion sections of Randomized Controlled Trials of health interventions. To be presented at European Conference on Argumentation, June 2017
  21. 21. Clause-level changes in meaning • “Two of four randomised clinical trials …have found a difference in admission rate [12,19] and two have not [22,23].” - PMC1142326 Jodi Schneider, Graciela Rosemblat, Shabnam Tafreshi and Halil Kilicoglu. Rhetorical moves and audience considerations in the discussion sections of Randomized Controlled Trials of health interventions. To be presented at European Conference on Argumentation, June 2017
  22. 22. A single citation can support a whole paragraph • Dutton and colleagues [8] described a series of 81 coagulopathic trauma patients treated with rFVIIa. Of these, 20 received rFVIIa for treatment of coagulopathy related to TBI. Six of these patients had additional polytrauma. The outcome of these patients was poor and 15 of 20 patients died. The authors attributed this high mortality rate to the severity of brain injury. None of the 81 trauma patients in this series had any clinical indication of TE events.” Jodi Schneider, Graciela Rosemblat, Shabnam Tafreshi and Halil Kilicoglu. Rhetorical moves and audience considerations in the discussion sections of Randomized Controlled Trials of health interventions. To be presented at European Conference on Argumentation, June 2017
  23. 23. Discussing treatments, outcomes, other authors’ conclusions • Dutton and colleagues [8] described a series of 81 coagulopathic trauma patients treated with rFVIIa. Of these, 20 received rFVIIa for treatment of coagulopathy related to TBI. Six of these patients had additional polytrauma. The outcome of these patients was poor and 15 of 20 patients died. The authors attributed this high mortality rate to the severity of brain injury. None of the 81 trauma patients in this series had any clinical indication of TE events.” Jodi Schneider, Graciela Rosemblat, Shabnam Tafreshi and Halil Kilicoglu. Rhetorical moves and audience considerations in the discussion sections of Randomized Controlled Trials of health interventions. To be presented at European Conference on Argumentation, June 2017
  24. 24. Sometimes several parallel paragraphs. • Dutton and colleagues [8] described a series of 81 …patients treated with rFVIIa” • “Zaaroor and Bar-Lavie [23] reported the first series of five patients …” • “Morenski and colleagues [24] described …three pediatric … cases” Jodi Schneider, Graciela Rosemblat, Shabnam Tafreshi and Halil Kilicoglu. Rhetorical moves and audience considerations in the discussion sections of Randomized Controlled Trials of health interventions. To be presented at European Conference on Argumentation, June 2017
  25. 25. Multiple citations in a paragraph • “Berger et al. [42] compared the efficacy of hypertonic saline and mannitol to reduce ICP after a combination of two different neuronal injuries. Initially, ….The authors demonstrated that …After …. It is remarkable that … An accumulation …These different effects … [42]. Furthermore, Prough et al. observed a higher regional cerebral blood flow in dogs with induced intracerebral hemorrhage after hypertonic saline without any increase of the CPP [43].” - PMC1297608 Jodi Schneider, Graciela Rosemblat, Shabnam Tafreshi and Halil Kilicoglu. Rhetorical moves and audience considerations in the discussion sections of Randomized Controlled Trials of health interventions. To be presented at European Conference on Argumentation, June 2017
  26. 26. Avoiding a 1-sentence paragraph? • “Berger et al. [42] compared the efficacy of hypertonic saline and mannitol to reduce ICP after a combination of two different neuronal injuries. Initially, ….The authors demonstrated that …After …. It is remarkable that … An accumulation …These different effects … [42]. Furthermore, Prough et al. observed a higher regional cerebral blood flow in dogs with induced intracerebral hemorrhage after hypertonic saline without any increase of the CPP [43].” - PMC1297608 Jodi Schneider, Graciela Rosemblat, Shabnam Tafreshi and Halil Kilicoglu. Rhetorical moves and audience considerations in the discussion sections of Randomized Controlled Trials of health interventions. To be presented at European Conference on Argumentation, June 2017
  27. 27. “[Y]ou can transform a fact into fiction or a fiction into fact just by adding or subtracting references” - Bruno Latour
  28. 28. ... two miRNAs, miRNA-372 and-373, function as potential novel oncogenes in testicular germ cell tumors by inhibition of LATS2 expression, which suggests that Lats2 is an important tumor suppressor (Voorhoeve et al., 2006). Raver-Shapira et.al, JMolCell 2007 miR-372 and miR-373 target the Lats2 tumor suppressor (Voorhoeve et al., 2006) Yabuta, JBioChem 2007: As claims get cited, they become 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, Voorhoeve et al, Cell, 2006: Hypothesis Implication Cited Implication Fact Slide credit: Anita DeWaard: 'Stories that persuade with data' - talk at CENDI meeting January 9 2014 https://www.slideshare.net/anitawaard/stories-that-persuade-with-data-talk-at-cendi-meeting-january- 9-2014/6
  29. 29. “The conversion of hypothesis to fact through citation alone.” - Stephen Greenberg
  30. 30. Greenberg, Steven A. "Understanding belief using citation networks." Journal of evaluation in clinical practice 17.2 (2011): 389-393. http://dx.doi.org/ 10.1111/j.1365- 2753.2011.01646.x
  31. 31. “The conversion of hypothesis to fact through citation alone.” - Stephen Greenberg Greenberg, Steven A. "How citation distortions create unfounded authority: analysis of a citation network." BMJ 339 (2009): b2680. https://doi.org/10.1136/bmj.b2680
  32. 32. Funded grants with citation bias & citation distortion. Greenberg, Steven A. "How citation distortions create unfounded authority: analysis of a citation network." BMJ 339 (2009): b2680. https://doi.org/10.1136/bmj.b2680
  33. 33. Modeling arguments and evidence
  34. 34. SEPIO – evidence lines Brush, Matthew, Kent Shefchek, and Melissa Haendel. "SEPIO: a semantic model for the integration and analysis of scientific evidence." International Conference on Biomedical Ontology and BioCreative. 2016. http://ceur-ws.org/Vol-1747/IT605_ICBO2016.pdf “A proposition has_evidence one or more evidence lines, which have_supporting_data one or more data items used in evaluation of the proposition’s truth.”
  35. 35. SEPIO – evidence lines example Brush, Matthew, Kent Shefchek, and Melissa Haendel. "SEPIO: a semantic model for the integration and analysis of scientific evidence." International Conference on Biomedical Ontology and BioCreative. 2016. http://ceur-ws.org/Vol-1747/IT605_ICBO2016.pdf “A simplified account of existing evidence related to this proposition is presented below, presenting summaries of five evidence lines (E1-E5) from five studies relevant to the classification of the variant for Fabry Disease: E1. Six affected individuals with the variant were found to have reduced GLA enzyme activity. E2. The variant was absent from 528 unaffected controls. E3. The variant is predicted to cause abnormal splicing that inserts additional sequence. E4. Pedigree analyses showed Fabry Disease phenotypes segregating with the variant. E5. Population databases show high frequency of individuals homozygous for the variant.”
  36. 36. SEPIO – evidence lines example Brush, Matthew, Kent Shefchek, and Melissa Haendel. "SEPIO: a semantic model for the integration and analysis of scientific evidence." International Conference on Biomedical Ontology and BioCreative. 2016. http://ceur-ws.org/Vol-1747/IT605_ICBO2016.pdf “A simplified account of existing evidence related to this proposition is presented below, presenting summaries of five evidence lines (E1-E5) from five studies relevant to the classification of the variant for Fabry Disease: E1. Six affected individuals with the variant were found to have reduced GLA enzyme activity. E2. The variant was absent from 528 unaffected controls. E3. The variant is predicted to cause abnormal splicing that inserts additional sequence. E4. Pedigree analyses showed Fabry Disease phenotypes segregating with the variant. E5. Population databases show high frequency of individuals homozygous for the variant.”
  37. 37. Modeling arguments and evidence
  38. 38. SEE Bö̈ lling, Christian, Michael Weidlich, and Hermann-Georg Holzhütter. "SEE: structured representation of scientific evidence in the biomedical domain using Semantic Web techniques." Journal of Biomedical Semantics 5.1 (2014): 1.
  39. 39. SEE Bö̈ lling, Christian, Michael Weidlich, and Hermann-Georg Holzhütter. "SEE: structured representation of scientific evidence in the biomedical domain using Semantic Web techniques." Journal of Biomedical Semantics 5.1 (2014): 1.
  40. 40. Modeling arguments and evidence
  41. 41. Micropublications Clark, Tim, Paolo N. Ciccarese, and Carole A. Goble. "Micropublications: a semantic model for claims, evidence, arguments and annotations in biomedical communications." Journal of Biomedical Semantics 5.28 (2014). http://dx.doi.org/10.1186/2041-1480-5-28
  42. 42. Jodi Schneider, Paolo Ciccarese, Tim Clark, Richard D. Boyce. “Using the Micropublications ontology and the Open Annotation Data Model to represent evidence within a drug-drug interaction knowledge base.” Linked Science at ISWC 2014 http://ceur-ws.org/Vol-1282/lisc2014_submission_8.pdf
  43. 43. Formalizing knowledge
  44. 44. Cataloging evidence types for knowledge bases. Boyce, R.D.: A Draft Evidence Taxonomy and Inclusion Criteria for the Drug Interaction Knowledge Base (DIKB), http://purl.net/net/drug-interaction-knowledge-base/evidence-types-and- inclusion-criteria
  45. 45. Biological Expression Language Rastegar-Mojarad, Majid, Ravikumar Komandur Elayavilli, and Hongfang Liu. "BELTracker: evidence sentence retrieval for BEL statements." Database 2016 (2016). See also: http://openbel.org
  46. 46. Corpora of Interest
  47. 47. Voorhoeve et al. (116) employed a novel strategy by combining an miRNA vector library and corresponding bar code array… miR-372 and miR-373 were consequently found to permit proliferation and tumorigenesis of these primary cells carrying both oncogenic RAS and wild-type p53, probably through direct inhibition of the expression of the tumor-suppressor LATS2 and subsequent neutralization of the p53 pathway. to identify miRNAs that when overexpressed could substitute for p53 loss and allow continued proliferation in the context of Ras activation TAC Corpus: Curated Collection of 500 Citing > 50 Cited Papers Voorhoeve et al. (2006), A Genetic Screen … In mammals, a near-perfect complementarity between miRNAs and protein coding genes almost never exists, making it difficult to directly pinpoint relevant downstream targets of a miRNA. Several algorithms were developed that predict miRNA targets, most notably TargetScanS, PicTar, and miRanda (John et al., 2004, Lewis et al., 2005 and Robins et al., 2005). These programs predict dozens to hundreds of target genes per miRNA, making it difficult to directly infer the cellular pathways affected by a given miRNA. Furthermore, the biological effect of the downregulation depends greatly on the cellular context, which exemplifies the need to deduce miRNA functions by in vivo genetic screens in well-defined model systems. The cancerous process can be modeled by in vitro neoplastic transformation assays in primary human cells (Hahn et al., 1999). Using this system, sets of genetic elements required for transformation were identified. For example, the joint expression of the telomerase reverse transcriptase subunit (hTERT), oncogenic H-RASV12, and SV40-small t antigen combined with the suppression of p53 and p16INK4A were sufficient to render primary human fibroblasts tumorigenic (Voorhoeve and Agami, 2003). Goal Method Result Con clusion Citing PapersReference Paper Slide credit: Anita DeWaard: Argumentation in biology papers https://www.slideshare.net/anitawaard/argumentation-in-biology-papers/27
  48. 48. Take away messages • Biomedicine has evolved multiple approaches for managing and appraising individual papers and bodies of “facts”. • Citations come in many shapes and sizes. • Citations may support “facts” – as part of a larger scientific fabric that includes data, evidence, arguments. • Powermove: identify the critical supports (think Jenga)
  49. 49. Take away messages • Network analysis may help identify problematic citation practices. • Modeling arguments can help identify the robustness of a claimed “fact”. • Semantic models could enable inference- based reasoning and citation network querying. • Relevant citation corpora exist.
  50. 50. Slide credit: Anita DeWaard: Epistemics, https://www.slideshare.net/anitawaard/epistemics/6
  51. 51. Anita’s insight: Detect and Track Metadiscourse • Voorhoeve et al., 2006: “These miRNAs neutralize p53- mediated CDK inhibition, possibly through direct inhibition of the expression of the tumor suppressor LATS2.” • Kloosterman and Plasterk, 2006: “In a genetic screen, miR-372 and miR-373 were found to allow proliferation of primary human cells that express oncogenic RAS and active p53, possibly by inhibiting the tumor suppressor LATS2 (Voorhoeve et al., 2006).” • Yabuta et al., 2007: “[On the other hand,] two miRNAs, miRNA-372 and-373, function as potential novel oncogenes in testicular germ cell tumors by inhibition of LATS2 expression, which suggests that Lats2 is an important tumor suppressor (Voorhoeve et al., 2006).” • Okada et al., 2011: “Two oncogenic miRNAs, miR-372 and miR-373, directly inhibit the expression of Lats2, thereby allowing tumorigenic growth in the presence of p53 (Voorhoeve et al., 2006).” Slide credit: Based on Anita DeWaard: How to persuade with data https://www.slideshare.net/anitawaard/stories-thatpersuadev-4/18
  52. 52. Metadiscourse: some progress • Hedging cues, speculative language, modality/negation: • Light et al [6]: finding speculative language • Wilbur et al (Hagit) [7]: focus, polarity, certainty, evidence, and directionality • Thompson et al (Sophia) [8]: level of speculation, type/source of the evidence and level of certainty • Sentiment detection (e.g. Kim and Hovy [9] a.m.o.): • Holder of the opinion, strength, polarity as ‘mathematical function’ acting on main propositional content • Can make this part of the semantic web: (e.g., Ontology for Reasoning, Certainty and Attribution, ORCA [10]): • Value (Presumed True, Probable, Possible, Unknown) • Source (Author, Named Other, Unknown) • Basis (Data, Reasoning, Unknown) Slide credit: Anita DeWaard: How to persuade with data https://www.slideshare.net/anita waard/stories-thatpersuadev- 4/19
  53. 53. Anita’s citations [6] Light M, Qiu XY, Srinivasan P. (2004). The language of bioscience: facts, speculations, and statements in between. BioLINK 2004: Linking Biological Literature, Ontologies and Databases 2004:17-24. [7] Wilbur WJ, Rzhetsky A, Shatkay H (2006). New directions in biomedical text annotations: definitions, guidelines and corpus construction. BMC Bioinformatics 2006, 7:356. [8] Thompson P., Venturi G., McNaught J, Montemagni S, Ananiadou S. (2008). Categorising modality in biomedical texts. Proc. LREC 2008 Wkshp Building and Evaluating Resources for Biomedical Text Mining 2008. [9] Kim, S-M. Hovy, E.H. (2004). Determining the Sentiment of Opinions. Proceedings of the COLING conference, Geneva, 2004. [10] de Waard, A. and Schneider, J. (2012) An Ontology of Reasoning, Certainty and Attribution (ORCA), ISWC 2012, http://ceur-ws.org/Vol- 930/p2.pdf

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