Building a massive biomedical knowledge graph with citizen science

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    14-Jul-2015

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Building a massive biomedical knowledge graph with citizen scienceBenjamin Good The Scripps Research Institute @bgoodNot paying attention? be a citizen scientist at http://mark2cure.orgHigh level goal: improve access to published knowledge22articles added to PubMed per year1 every 30 seconds, more than million a yearknowledge graphChemicals & drugsGenesOrganismsArea of studyBiological ProcessAuto!Knowledge Graph~10,000 articlesNgly1 gene?New drug candidate? Knowledge graph problems Assigning meaning to relations Incorrect relations Missing relations Facts of life in computer processing of human language False Positives and False Negatives always Human annotators remain the gold standard There are not nearly enough professional human annotators to process every document published5 Not paying attention? be a citizen scientist at http://mark2cure.orgObservations There are about 2.92 billion Internet users Lots of them can read English6 http://www.statista.com/statistics/273018/number-of-internet-users-worldwide/Hypothesis We can generate the equivalent of massive numbers of professional annotators by aggregating the labor of large numbers of non-professional CITIZEN SCIENTISTS!!!7Building a Knowledge Graph1. Find mentions of concepts in text 2. Identify relationships between concepts8Before we try for citizens.. Can non-scientists collectively identify concepts in biomedical texts with high quality? We used the Amazon Mechanical Turk crowdsourcing platform to answer the question9 Not paying attention? be a citizen scientist at http://mark2cure.orgHighlight the disease.Answer was yes By combining the responses of multiple non-professional members of the crowd, we achieved equivalent quality to professional annotatorsGood et al. Microtask crowdsourcing for disease mention annotation in pubmed abstracts. Pacific Symposium on Biocomputing 2015 http://psb.stanford.edu/psb-online/proceedings/psb15/good.pdfMark2Cure.orgSame task, different contextExperiment 1 in progressEvaluating quality and quantity of volunteer annotators Goal is to complete about 600 abstracts, with 15 volunteers per abstract Almost there! mark2cure experiment 1Tasks/10New usersLaunchTweetBlog postSan Diego Union Tribune Article11:00am Feb. 9 5423, tasks complete 230 signups, 130 have completed a taskNot paying attention? be a citizen scientist at http://mark2cure.orgNext steps Implement and test a relation extraction workflow Start disease-focused knowledge capture missions First disease: NGLY1 deficiency http://ngly1.orgThanks to the mark2cure team!Max NanisAndrew Su@bgood bgood@scripps.eduGinger TsuengChunlei WuThank you to the citizen scientists making this possible!Why do I Mark2Cure?In memory of my daughter who had Cystic Fibrosis Studied biology in college and I really miss it! My 4 year old daughter Phoebe is living with and battling rare disease. I have Ehlers Danlos Syndrome. I hope to help people learn about this painful and debilitating disorder, so that others like me can receive more effective medical care. I am retired, have a doctorate in medical humanities, and have two children with Gaucher disease. I am just looking for some way to put my education to use. To give back I Mark2Cure in memory of my son Mike who had type 1 diabetes. Take part in something that helps humanity. Increase precision with voting201 or more votes (K=1)This molecule inhibits the growth of a broad panel of cancer cell lines, and is particularly efficacious in leukemia cells, including orthotopic leukemia preclinical models as well as in ex vivo acute myeloid leukemia (AML) and chronic lymphocytic leukemia (CLL) patient tumor samples. Thus, inhibition of CDK9 may represent an interesting approach as a cancer therapeutic target especially in hematologic malignancies.K=2This molecule inhibits the growth of a broad panel of cancer cell lines, and is particularly efficacious in leukemia cells, including orthotopic leukemia preclinical models as well as in ex vivo acute myeloid leukemia (AML) and chronic lymphocytic leukemia (CLL) patient tumor samples. Thus, inhibition of CDK9 may represent an interesting approach as a cancer therapeutic target especially in hematologic malignancies.K=3This molecule inhibits the growth of a broad panel of cancer cell lines, and is particularly efficacious in leukemia cells, including orthotopic leukemia preclinical models as well as in ex vivo acute myeloid leukemia (AML) and chronic lymphocytic leukemia (CLL) patient tumor samples. Thus, inhibition of CDK9 may represent an interesting approach as a cancer therapeutic target especially in hematologic malignancies.K=4This molecule inhibits the growth of a broad panel of cancer cell lines, and is particularly efficacious in leukemia cells, including orthotopic leukemia preclinical models as well as in ex vivo acute myeloid leukemia (AML) and chronic lymphocytic leukemia (CLL) patient tumor samples. Thus, inhibition of CDK9 may represent an interesting approach as a cancer therapeutic target especially in hematologic malignancies.Aggregation functionAMT results: 589 abstracts compared to gold standard21F = 0.87, k = 6

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