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- 1. A little semantics … can go a long way! What is the Semantic Web and how can it be used to accelerate translational research and biological discovery Helena F. Deus
- 2. Data is what you find on the Web
- 3. Data, data everywhere Sequences Microarrays Electrophoresis Chrystalography In vitro experiments
- 4. What pathways is my protein involved in?
- 5. Building bridges If you could have only 3 apps to do all your work, which ones would they be?
- 7. Building bridges species cc5 sub- type
- 8. Biological Knowledge Continuum Metabolome Knowledge Continuum Medical Records Microarrays Proteome Microbiome Genome Sequences Protein Gels
- 10. Re-Using Data in Biology ~20 000 genes ~100 interesting genes/proteins ~ 10 interesting pathways ~5 genes/proteins testable in the lab High-throughput technologies Literature Browse databases Computational statistics Hypothesis Generation “I like to call it low-input, high-throughput, no-output biology.”
- 11. Writing the story ??
- 12. !!
- 13. Computers can make life easier! Statistics
- 14. A Little Semantics mecA Strain1 hasGene “resistance to met” causes mecA Strain1 Sample1 origin pneumon disease Sample1
- 15. Principle #1 Use URL to name things Principle #2 Organize data in Triples A Little Semantics http://mecA http://Strain1 hasGene “resistance to met” causes mecA http://Strain1 Sample1 origin pneumon disease Sample1
- 16. A Little Semantics http://mecA http://Strain1 hasGene “resistance to met” causes http://mecA http://Strain1 Sample1 origin pneumon disease Sample1
- 17. ... a lot of knowledge networking! epidermal growth factor receptor rea:Membrane nci:has_description rea:keyword CCCCGGCGCAGCGCGGCCGCAGCAGCCTCCGCCCCCCGCACGGTGTGAGCGCCCGACGCGGCCGAGGCGG … nih:sequence rea:Receptor nih:EGFR nih:EGFR rea:keyword nih:organism rea:keyword Homo sapiens rea:Transferase nih:interacts nih:EGF nih:organism Reactome NCBI
- 18. Linked Data Cloud – the Story so Far Src: http://linkeddata.org/
- 19. How to make use of that data? What are the microbial Staphylococcus strains, belonging to clonal complex 5 and collected in Portugal? And when were they collected? Staphylococcus Clonal Complex 5 Date of Collection Portugal
- 20. How to make use of that data? What are the microbial Staphylococcus strains, belonging to clonal complex 5 and collected in Portugal? ?Strain :hasClonalComplex 5 :hasSpeciesStaphylococcus :hasOrigin Portugal And when were those isolates collected? ?Sample :hasIsolate ?Strain ; :wasCollected ?Date
- 21. Linking genomes
- 22. Linking Diseases Src: Kwang-Il Goh et al. The human disease network PNAS 2007 104 (21)
- 23. Genetic Landscape Source: Science 22 January 2010: Vol. 327 no. 5964 pp. 425-431
- 24. How about the statistics?
- 25. Plugging data to the Web of the Future
- 27. 2001: The Semantic Web Semantic Web A web where computers, not just humans, can read and write
Notes de l'éditeur
- Vivemos no mundo dos dadosA internet tornou o acessoaos dados de umacoisalimitada a umacoisasuperabundante
- Alemn disso, nemtodosos dados saoiguaisNa biologiaem particular, a explosao dos dados estaacoplada a heterogeneidade dos dados
- Porcausadaheterogeneidade,por um lado, e daabundancia de dados muitodisposerosna web poroutro, e cadavezmaisdificlencontraros dados queitneressamA maiorparta das bases de dados queexistemexigemque se conhecamuitobemnao so osnossos dados, mastambem a interface das bases de dados...Este processo e taodemoradoqueacabapornaofazersentido
- The problem today is that experimental data, such as gene expression results or sequences, are being deposited in proprietary databases, which often do not share the models and therefore are difficult to interoperate. The current state of affairs is that data is brought into these databases, but researchers from different fields are kept out, making collaboration difficult. To create and environment where scientist from different areas can interconnect, share knowledge and ideas, we need to create a knowledge continuum. The knowledge continuum in biology can be used by multiple communities at the same time to provide an answer to complicated questions such as cancer.The semantic web technologies are seen as the ideal starting point for the creation of social machines where knowledge and data can be shared, because they rely entirely on the lessons learned from using the Web.
- Messages:Finding the mathematics of biology;patterns and interrealtedness of biological entitiesBiological data in computational formats; automate data analysis and annotation is a dream which is not yet achievedTechnologies that could help make such a dream reality; transform the www into a computational platform where read and write operations are supported and boundaries between knowledge systems are erased
- What if computers could do that for us?
- Unlinked data would look something like this; the nih would have some information about the EGFR gene; when you go to reactome, some more information about it can be found; what linked data does is eliminate the boundaries between the systems and enable the joining of the data through its identifiers
- Links to our origins
- Simplified views of the complexity in the cell
- the tcga model in s3db was indeed at the root of several studies that make use of the integrative capabilities of S3DB to integrate data that would otherwise require significant amounts of time parsing and aggregating
- In 2001, Tim Berners Lee, who was also the inventor of the World Wide Web, planted the seeds for a new solution. He called it the Semantic Web.The primary goal of the Semantic Web was to create a space where data would be linked in such as way that not only humans, but also machines could read and interact with it. Ultimately, these machines or agents would become the main way of interaction between people and the data on the web. Instead of browsing the web, users could ask these agents to collect the necessary information to answers a question or schedule an appointment.