ContentMining for Synthetic Biology
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Published on May 18, 2015 by PMR Basics of ContentMining presented to Synthetic Biologists. This was followed by a lively discussion of what components could be extracted from the literature
![http://www.nytimes.com/2015/04/08/opinion/yes-we-were-warned-about-
ebola.html
We were stunned recently when we stumbled across an article by European
researchers in Annals of Virology [1982]: “The results seem to indicate that
Liberia has to be included in the Ebola virus endemic zone.” In the future,
the authors asserted, “medical personnel in Liberian health centers should be
aware of the possibility that they may come across active cases and thus be
prepared to avoid nosocomial epidemics,” referring to hospital-acquired
infection.
Adage in public health: “The road to inaction is paved with research
papers.”
Bernice Dahn (chief medical officer of Liberia’s Ministry of Health)
Vera Mussah (director of county health services)
Cameron Nutt (Ebola response adviser to Partners in Health)
A System Failure of Scholarly Publishing](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
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ContentMining for Synthetic Biology
- 1. Mining Bioscience Literature Peter Murray-Rust, University of Cambridge and TheContentMine SynBio, Cambridge UK, 2015-05-18 Much Scientific Data lies hidden in text and images, in articles, theses, reports, patents, lab-books… The ContentMine has Open collaborative tools that anyone can use to find facts and re-use for their own research
- 2. http://www.nytimes.com/2015/04/08/opinion/yes-we-were-warned-about- ebola.html We were stunned recently when we stumbled across an article by European researchers in Annals of Virology [1982]: “The results seem to indicate that Liberia has to be included in the Ebola virus endemic zone.” In the future, the authors asserted, “medical personnel in Liberian health centers should be aware of the possibility that they may come across active cases and thus be prepared to avoid nosocomial epidemics,” referring to hospital-acquired infection. Adage in public health: “The road to inaction is paved with research papers.” Bernice Dahn (chief medical officer of Liberia’s Ministry of Health) Vera Mussah (director of county health services) Cameron Nutt (Ebola response adviser to Partners in Health) A System Failure of Scholarly Publishing
- 3. Scientific and Medical publication (STM)[+] • World Citizens pay $400,000,000,000… • … for research in 1,500,000 articles … • … cost $300,000 each to create … • … $7000 each to “publish” [*]… • … $10,000,000,000 from academic libraries … • … to “publishers” who forbid access to 99.9% of citizens of the world … • 85% of medical research is wasted (not published, badly conceived, duplicated, …) [+] Figures probably +- 50 % [*] arXiV preprint server costs $7 USD per paper
- 4. The Right to Read is the Right to Mine http://contentmine.org
- 5. Facts Marked by “non-scientists” in ContentMine workshops With Wikipedia everyone can be a scientist
- 6. ContentMine Workshops and Hackdays Open Science Brazil, 2014-08 Easily distributed software Get started in 30 mins Build application in a morning Start simple: bagOfWords, Stemming, Regex, templates
- 7. Oxford 2013 Berlin 2014 Delhi 2014 Jenny Molloy with mascot AMI
- 8. OUR TEAM @jenny_molloy Ross Mounce @rmounce Richard Smith- Unna @blahah404 Stephanie Smith- Unna @treblesteph Jenny Molloy Mark MacGillivray @cottagelabs Peter Murray- Rust @petermurrayrust Charles Oppenheim @CharlesOppenh Graham Steel @McDawg
- 9. Workshops (1-hour -> full day or more) 2014-May->Nov • Budapest/Shuttleworth • Leicester Univ • Electronic Theses and Dissertations • Austrian Science Fund AT • OKFest DE • Eur. Bioinformatics Institute • Open Science Rio de Janeiro BR • Sci DataCon , Delhi IN • Univ of Chicago US • OpenCon 2014, Wash DC. US • JISC , London 2015 • LIBER • Cochrane • BL • Wellcome Trust (April) • WHO Collaborators • Wikimedia/Wikidata • Mozilla • Open Knowledge • LIBER (European Research Libraries) • British Library • Wellcome Trust • EBI (Eur. Bioinf. Inst.) • JISC • Open Access Button • SPARC • Creative Commons • CORE • EuropePubmedCentral
- 10. Content-Mining (TDM*) • Now COMPLETELY LEGAL IN UK since 2014-06-01 (“Hargreaves”)… • … Whatever the publishers tell you. Do NOT sign their APIs • UK can legally IGNORE contractual restrictions • Movement to extend this to Europe (Julia Reda, MEP proposal) • And STM publishers are spending millions to stop us *Text and Data Mining
- 11. What is “Content”? http://www.plosone.org/article/fetchObject.action?uri=info:doi/10.1371/journal.pone.01113 03&representation=PDF CC-BY SECTIONS MAPS TABLES CHEMISTRY TEXT MATH contentmine.org tackles these
- 12. “nuggets” in a scientific paper quantity units Value ranges Humans aren’t designed to mine this … chemical project places
- 13. What is “Content”? Emily Sena (neuroscience.ed.ac.uk) spends half a day digitising a diagram like this ContentMine will soon be able to do it in 1 second
- 14. • CRAWL the web for scientific documents (articles, grey literature, repositories) • quickSCRAPE pages (text, graphics, images, data) • NORMA-lize page to semantic form …Open semantic science … • MINE pages with your methods and tools (AMI) • CAT-alogue results in searchable index • Automate daily process (CANARY) contentmine.org Infrastructure
- 15. https://en.wikipedia.org/wiki/Irrigation#mediaviewer/File:Pump- enabled_Riverside_Irrigation_in_Comilla,_Bangladesh,_25_April_2014.jpg CC BY-SA 3.0 Daily Stream of 100,000 Open Facts Twitter?Indexed by CAT http://catalogue.cottagelabs.com/browsehttp://catalogue.cottagelabs.com/graph
- 16. quickscrape Crawl Feed Norma Index & Transform PDF XML URL DOI Scientific literature Repositories DOC CSV sHTML Plugins Regex SequencesSpecies Bespoke Scrapers XPathPer-Journal Taggers Per- Journal MetadataChemistry Phylogenetics Farming AMI BadHTML OCR Diagrams Open NORMA-lized Scientific Literature + Facts CANARY pipeline CAT-alogue index
- 17. PLoSONE BMC 1 BMC 2 Closed1 Closed2Hybrid CATalog Enhanced annotated articles FACTSFACTS Daily Crawl Crawl … Scrape … Normalize … Mine Linked OpenData Semantic Scientific Objects 2000-5000 Articles
- 19. PLoSONE BMC 1 BMC 2 Closed1 Closed2Hybrid CATalog FACTS Daily Crawl Crawl … Scrape … Normalize … Mine Open3 Closed3 Selected Retrospective REPO Articles Theses Reports Patents FACTS
- 20. Peter Murray-Rust BMC publisher Blue Obelisk paper (20 co-authors) Sub-network From CATalog
- 21. Phytochemistry extraction O. dayi “volatile composition of “ A.sibeiri A. judaica Displayed by CAT (CottageLabs)
- 22. Retrieval/Extraction Technologies • Bag Of Words https://en.wikipedia.org/wiki/Bag-of-words_model) • Term-Frequency Inverse-Document-Frequency https://en.wikipedia.org/wiki/Tf%E2%80%93idf • Regular Expressions • Templates (Information Extraction) • Natural Language Processing (NLP) • Image processing and mining • Lookup (Wikidata, Bioscience databases)
- 23. Bag of Words Theses from HAL repository
- 24. Species
- 25. Regex for Clinical Trials
- 26. CLINICAL TRIALS How to we find (mentions of) clinical trials? Is a document a (clinical) trial? What is the subject of the trial? What is the methodology used? How many/long? Does the design and practice conform to CONSORT? What are the outcomes? Can we extract specific re-usable information? Who are involved? (researchers, sponsors, patients?) Has a proposed trial been completed and reported?
- 27. Natural Language Processing Part of speech tagging (Wordnet, Brown Corpus, etc.)
- 28. Parsing chemical sentences This could be extended to much other scientific language
- 30. Automatic semantic markup of chemistry Could be used for analytical, crystallization, etc.
- 31. Open Content Mining of FACTs Machines can interpret chemical reactions We have done 500,000 patents. There are > 3,000,000 reactions/year. Added value > 1B Eur.
- 32. Ln Bacterial load per fly 11.5 11.0 10.5 10.0 9.5 9.0 6.5 6.0 Days post—infection 0 1 2 3 4 5 Bitmap Image and Tesseract OCR
- 34. Dumb PDF CSV Semantic Spectrum 2nd Derivative Smoothing Gaussian Filter Automatic extraction
- 35. Acanthisittidae Acanthizidae Acrocephalidae Callaeidae Campephagidae Cnemophilidae Corvidae 0.84 0.91 0.93 0.95 Acanthisitta Acrocephalus Ailuroedus Ailuroedus Amytornis Camptostoma AMI 23.12 34.54 37.21 38.55 Posterior probability AMI can MEASURE Branch lengths! NexML Genus Family HTML
- 36. https://blogs.ch.cam.ac.uk/pmr/2014/06/25/content-mining-we-can-now- mine-images-of-phylogenetic-trees-and-more/ for story of extraction Thinning Topology Serialization Newick
- 37. Problems • Cannot do handwriting • Scanned documents give poorer results • The older the document the poorer the result • Tables are a major problem • Always try to get the original document • XML better than > Word better than > PDF • Vector images >> PNG > JPEG • Maths, chemistry are specialist
- 38. POSSIBLE USES • Indexing/searching the literature; G***** for science • Current awareness; alerts and practices • Extraction and re-use of facts; re-computation • Multidisciplinary integration; co-occurrence • Compliance with funder/institution policies • Managing your Research Data! • Finding similar and complementary colleagues • Reproducibility, checking data and avoiding fraud
- 39. ContentMine Workshops and Hackdays Open Science Brazil, 2014-08 Easily distributed software Get started in 30 mins Build application in a morning Start simple: bagOfWords, Stemming, Regex, templates
- 40. Join our Open-Source community at http://www.contentmine.org
Editor's Notes
- Hi, I’m here to talk about AMI; a data extraction framework and tool. First, I just want highlight some of key contributors to the projects; Andy for his work on the ChemistryVisitor and Peter for the overall architecture. In this talk, I’m going to impress the importance of data in a specific format and its utility to automated machine processing. Then I’m going to demonstrate AMI’s architecture and the transformation of data as it flows through the process. I’m going to dwell a little on a core format used, Scalable Vector Graphics (SVG) before introducing the concept of visitors, which are pluggable context specific data extractors. Next, I’m going to introduce Andy’s ChemVisitor, for extracting semantic chemistry data, along with a few other visitors that can process non-chemistry specific data. Finally, I will demonstrate some uses of the ChemVisitor, within the realm of validation and metabolism.
- Because information is structured (some examples listed), we can aggregate similar objects and mine using a modular systematic approach.
- Because information is structured (some examples listed), we can aggregate similar objects and mine using a modular systematic approach.
- Can describe each collaboration, but keep this slide brief if the presentation is short.