1. The document describes a kidney and urinary pathway knowledge base (KUP KB) that integrates various types of biological data using semantic web technologies.
2. The KUP KB aims to provide background knowledge for data mining experiments and act as a collaborative repository for kidney and urinary pathway data.
3. An ontology is being developed to represent the kidney and urinary pathway domain and enable querying across the integrated data sources in the KUP KB.
Keynote presented at the Phenotype Foundation first annual meeting.
Describes data sharing, data annotation and the needs for further tool and ontology and ontology mapping development.
Amsterdam, January 18, 2016
Keynote presented at the Phenotype Foundation first annual meeting.
Describes data sharing, data annotation and the needs for further tool and ontology and ontology mapping development.
Amsterdam, January 18, 2016
Ontologies and Semantic Web technologies play an important role in the life sciences to help make data more interoperable and reusable. There are now many publicly available ontologies that enable biologists to describe everything from gene function through to animal physiology and disease.
Various efforts such as the Open Biomedical Ontologies (OBO) foundry provide central registries for biomedical ontologies and ensure they remain interoperable through a set of common shared development principles.
At EMBL-EBI we contribute to the development of biomedical ontologies and make extensive use of them in the annotation of public datasets. Biological data typically comes with rich and often complex metadata, so the ontologies provide a standard way to capture “what the data is about” and gives us hooks to connect to more data about similar things.
These ontology annotations have been put to good use in a number of large-scale data integration efforts and there’s an increasing recognition of the need for ontologies in making data FAIR (Findable, Accessible, Interoperable and Reusable).
EMBL-EBI build a number of integrative data platforms where ontologies are at the core of our domain models. One example is the Open Targets platform, where data about disease from 18 different databases can be aggregated and grouped based on therapeutic areas in the ontology and used to identify potential drug targets.
The ontologies team at EMBL-EBI provide a suite of services that are aimed at making ontologies more accessible for both humans and machines. We work with scientific data curators and software developers to integrate ontologies and semantics into both the data generation and data presentation workflows. We provide:
– An ontology lookup service (OLS) that provides search and visualisation services to over 200+ ontologies
– Services for automating the annotation of metadata and learning from previous annotations (Zooma)
– An ontology mapping and alignment service (OXO)
– Tools for working with metadata and ontologies in spreadsheets (Webulous)
– Software for enriching documents in search engines to support “semantic” query expansion
I’ll present how we are using these services at EMBL-EBI to scale up the semantic annotation of metadata. I’ll talk about our open source technology stack and describe how we utilise a polyglot persistence approach (graph databases, triples stores, document stores etc) to optimize how we deliver ontologies and semantics to our users.
The DNA Data Bank of Japan (DDBJ) is a biological database that collects DNA sequences. It is located at the National Institute of Genetics (NIG) in the Shizuoka prefecture of Japan. It is also a member of the International Nucleotide Sequence Database Collaboration or INSDC.
INTRODUCTION.
NCBI.
EMBL.
DDBJ.
CONCLUSION.
REFERENSE.
The National Center for Biotechnology Information (NCBI) is part of the United States National Library of Medicine (NLM), a branch of the National Institutes of Health.
The NCBI is located in Bethesda, Maryland and was founded in 1988 through legislation sponsored by Senator Claude Pepper.
The NCBI houses a series of databases relevant to biotechnology and biomedicine. Major databases include GenBank for DNA sequences and PubMed, a bibliographic database for the biomedical literature.
All these databases are available online through the Entrez search engine.
European Molecular Biology Laboratory (EMBL)- European Bioinformatics Institu...ExternalEvents
http://www.fao.org/about/meetings/wgs-on-food-safety-management/en/
Building the Database with International Isolates: European Molecular Biology Laboratory (EMBL)- European Bioinformatics Institute (EBI). Presentation from the Technical Meeting on the impact of Whole Genome Sequencing (WGS) on food safety management -23-25 May 2016, Rome, Italy.
Presentation pathway extensions using knowledge integration and network approaches presented at the Systems Biology Institute in Luxembourg on November 28 2012.
Ontologies and Semantic Web technologies play an important role in the life sciences to help make data more interoperable and reusable. There are now many publicly available ontologies that enable biologists to describe everything from gene function through to animal physiology and disease.
Various efforts such as the Open Biomedical Ontologies (OBO) foundry provide central registries for biomedical ontologies and ensure they remain interoperable through a set of common shared development principles.
At EMBL-EBI we contribute to the development of biomedical ontologies and make extensive use of them in the annotation of public datasets. Biological data typically comes with rich and often complex metadata, so the ontologies provide a standard way to capture “what the data is about” and gives us hooks to connect to more data about similar things.
These ontology annotations have been put to good use in a number of large-scale data integration efforts and there’s an increasing recognition of the need for ontologies in making data FAIR (Findable, Accessible, Interoperable and Reusable).
EMBL-EBI build a number of integrative data platforms where ontologies are at the core of our domain models. One example is the Open Targets platform, where data about disease from 18 different databases can be aggregated and grouped based on therapeutic areas in the ontology and used to identify potential drug targets.
The ontologies team at EMBL-EBI provide a suite of services that are aimed at making ontologies more accessible for both humans and machines. We work with scientific data curators and software developers to integrate ontologies and semantics into both the data generation and data presentation workflows. We provide:
– An ontology lookup service (OLS) that provides search and visualisation services to over 200+ ontologies
– Services for automating the annotation of metadata and learning from previous annotations (Zooma)
– An ontology mapping and alignment service (OXO)
– Tools for working with metadata and ontologies in spreadsheets (Webulous)
– Software for enriching documents in search engines to support “semantic” query expansion
I’ll present how we are using these services at EMBL-EBI to scale up the semantic annotation of metadata. I’ll talk about our open source technology stack and describe how we utilise a polyglot persistence approach (graph databases, triples stores, document stores etc) to optimize how we deliver ontologies and semantics to our users.
The DNA Data Bank of Japan (DDBJ) is a biological database that collects DNA sequences. It is located at the National Institute of Genetics (NIG) in the Shizuoka prefecture of Japan. It is also a member of the International Nucleotide Sequence Database Collaboration or INSDC.
INTRODUCTION.
NCBI.
EMBL.
DDBJ.
CONCLUSION.
REFERENSE.
The National Center for Biotechnology Information (NCBI) is part of the United States National Library of Medicine (NLM), a branch of the National Institutes of Health.
The NCBI is located in Bethesda, Maryland and was founded in 1988 through legislation sponsored by Senator Claude Pepper.
The NCBI houses a series of databases relevant to biotechnology and biomedicine. Major databases include GenBank for DNA sequences and PubMed, a bibliographic database for the biomedical literature.
All these databases are available online through the Entrez search engine.
European Molecular Biology Laboratory (EMBL)- European Bioinformatics Institu...ExternalEvents
http://www.fao.org/about/meetings/wgs-on-food-safety-management/en/
Building the Database with International Isolates: European Molecular Biology Laboratory (EMBL)- European Bioinformatics Institute (EBI). Presentation from the Technical Meeting on the impact of Whole Genome Sequencing (WGS) on food safety management -23-25 May 2016, Rome, Italy.
Presentation pathway extensions using knowledge integration and network approaches presented at the Systems Biology Institute in Luxembourg on November 28 2012.
Issues and activities in authoring ontologiesrobertstevens65
Departmental seminar at Department of Computer Science, university of Birmingham, 6 November, 2014
abstract: Ontologies are complex knowledge representation artefacts used across biomedical sciences, the media and other domains for defining terminologies and providing metadata. Their use is increasing rapidly, but so far, ontology authoring tools have not benefited from empirical research into the ontology authoring process. Understanding how people build ontologies is key to developing tools that can properly support common authoring activities. In this talk I will first present the outcomes of qualative interviews with ontology authors and the issues it reveals. Second, I will present the results of a study that identifies common activity patterns through analysis of the event logs, screen capture and eye-tracking data collected from the popular authoring tool, Protege. Results from this bottom-up investigation suggest that the class hierarchy is the central focus of activity, playing a role beyond simple class representation. We also find that checking how updates to the ontology is hard and performance is hindered by inadequate support in the user interface. From this investigation we propose design guidelines for bulk editing, efficient reasoning and increased situational awareness in ontology authoring.
Data analysis & integration challenges in genomicsmikaelhuss
Presentation given at the Genomics Today and Tomorrow event in Uppsala, Sweden, 19 March 2015. (http://connectuppsala.se/events/genomics-today-and-tomorrow/) Topics include APIs, "querying by data set", machine learning.
The flood of nextgen sequencing data is changing the landscape of computation biology, pushing the need for more robust infrastructures, tools, and visualization techniques.
Chattanooga Research Institute PresentationPhilip Bourne
A presentation made to Chattanooga officials about the importance of computational biology to the future of health care and what it might mean to the Chattanooga Research Institute (CRI).
Connecting life sciences data at the European Bioinformatics InstituteConnected Data World
Tony Burdett's slides from his talk at Connected Data London. Tony is a Senior Software Engineer at The European Bioinformatics Institute. He presented the complexity of data at the EMBL-EBI and what is their solution to make sense of all this data.
Function and Phenotype Prediction through Data and Knowledge FusionKarin Verspoor
The biomedical literature captures the most current biomedical knowledge and is a tremendously rich resource for research. With over 24 million publications currently indexed in the US National Library of Medicine’s PubMed index, however, it is becoming increasingly challenging for biomedical researchers to keep up with this literature. Automated strategies for extracting information from it are required. Large-scale processing of the literature enables direct biomedical knowledge discovery. In this presentation, I will introduce the use of text mining techniques to support analysis of biological data sets, and will specifically discuss applications in protein function and phenotype prediction, exploring the integration of literature data with complementary structured resources.
OBOPedia: An Encyclopaedia of Biology Using OBO OntologiesObopedia swat4ls-20...robertstevens65
A talk on OBOPedia (HTTP://www.obopedia.org.uk) given at Semantic Web Applicaitons and Tools for Life Sciences (SWAT4Ls) 2015 in cambridge, UK December 2015
The state of the nation for ontology developmentrobertstevens65
Invited talk at European Ontology Network (EUON) 2014
Ontologies are now quite big, both literally and metaphorically. They have become central resources in disciplines such as biology, medicine, healthcare and others. Such developments rely on people, tools and methods to deliver ontologies that do the desired job, on-time and on-budget. In this talk I wil ask the question of whether the tools and methods we have are capable of doing what is necessary to deliver robust and maintainable ontologies. To explore this question I will borro from the Capability Maturity Model used to assess the capabilities of institutions to deliver software projects. Instead of institutional assessment, I will bend the CCM to the discipline of ontology engineering. The levels of the CMM range from the ad hoc to one where metrics are used to monitor and adjust ontology development. In this talk I will use some audience participation to gather views on ontology engineering maturity level and then deliver my own view of that maturity.
Properties and Individuals in OWL: Reasoning About Family Historyrobertstevens65
Slides used in an advanced OWL tutorial in 2012. The tutorial is based on family history and uses OWL individuals as a first class citizen in the learning.
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...University of Maribor
Slides from:
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Track: Artificial Intelligence
https://www.etran.rs/2024/en/home-english/
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
Salas, V. (2024) "John of St. Thomas (Poinsot) on the Science of Sacred Theol...Studia Poinsotiana
I Introduction
II Subalternation and Theology
III Theology and Dogmatic Declarations
IV The Mixed Principles of Theology
V Virtual Revelation: The Unity of Theology
VI Theology as a Natural Science
VII Theology’s Certitude
VIII Conclusion
Notes
Bibliography
All the contents are fully attributable to the author, Doctor Victor Salas. Should you wish to get this text republished, get in touch with the author or the editorial committee of the Studia Poinsotiana. Insofar as possible, we will be happy to broker your contact.
Phenomics assisted breeding in crop improvementIshaGoswami9
As the population is increasing and will reach about 9 billion upto 2050. Also due to climate change, it is difficult to meet the food requirement of such a large population. Facing the challenges presented by resource shortages, climate
change, and increasing global population, crop yield and quality need to be improved in a sustainable way over the coming decades. Genetic improvement by breeding is the best way to increase crop productivity. With the rapid progression of functional
genomics, an increasing number of crop genomes have been sequenced and dozens of genes influencing key agronomic traits have been identified. However, current genome sequence information has not been adequately exploited for understanding
the complex characteristics of multiple gene, owing to a lack of crop phenotypic data. Efficient, automatic, and accurate technologies and platforms that can capture phenotypic data that can
be linked to genomics information for crop improvement at all growth stages have become as important as genotyping. Thus,
high-throughput phenotyping has become the major bottleneck restricting crop breeding. Plant phenomics has been defined as the high-throughput, accurate acquisition and analysis of multi-dimensional phenotypes
during crop growing stages at the organism level, including the cell, tissue, organ, individual plant, plot, and field levels. With the rapid development of novel sensors, imaging technology,
and analysis methods, numerous infrastructure platforms have been developed for phenotyping.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
I will finally argue that deep variability is both the problem and solution of frictionless reproducibility, calling the software science community to develop new methods and tools to manage variability and foster reproducibility in software systems.
Exposé invité Journées Nationales du GDR GPL 2024
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Kidney and Urinary Pathways Knowledge Base (part of e-LICO)
1. Kidney and Urinary Pathways Knowledge Base
(part of e-LICO)
Simon Jupp
University of Manchester
Bio-ontologies, Boston
July 9 2010
July 9, 2010Bio-ontologies, Boston
2. Kidney and Urinary Knowledge Base and Ontology
KUP KB
(RDF store)
Specialised repository of KUP related data
KUP ontology for integration, query and inference
Background knowledge for data mining experiments
Collaborative update by the community
July 9, 2010Bio-ontologies, Boston
3. Chronic Renal Disease
Obstructive nephropathy
- first cause of end-stage
renal disease in children.
Dialysis or transplantation
- 8000$/patient
A plumbing problem
Kidney
Ureter
Bladder
Urine
July 9, 2010Bio-ontologies, Boston
5. Genome Proteome MetabolomeOR OR
Identification of pathways instead of molecules
July 9, 2010Bio-ontologies, Boston
6. Genome Proteome MetabolomeAND AND
Identification of pathways instead of molecules
!
Identification of nodes in the pathophysiology of obstruction
July 9, 2010Bio-ontologies, Boston
7. e-LICO
Expression data
KUP KB
(RDF store)
Text-mining / Image mining
New models
And hypothesis
Further wet lab
experiments
e-LICO FP7 EU project.
e-Laboratory for Interdisciplinary Collaborative research in
data-mining and data-intensive sciences.
http://www.e-lico.eu
July 9, 2010Bio-ontologies, Boston
8. e-LICO
Expression data
Text-mining / Image mining
New models
And hypothesis
Further wet lab
experiments
e-LICO FP7 EU project.
e-Laboratory for Interdisciplinary Collaborative research in
data-mining and data-intensive sciences.
http://www.e-lico.eu
KUP KB
(RDF store)
Use Semantic Web technologies (RDF/OWL)
for this part of our infrastructure
July 9, 2010Bio-ontologies, Boston
9. REQUIREMENTS
Need low cost platform for data integration
Flexible data model
– Community extensions
Use of controlled vocabularies
– Ontologies for query and inferencing
KUP KB requirements
July 9, 2010Bio-ontologies, Boston
10. Kidney and Urinary Pathway Knowledge Base
1. Background knowledge to data-mining experiment
2. Repository of KUP experiments
http://www.e-lico.eu/kupkb
-omics data
Experimental data
July 9, 2010Bio-ontologies, Boston
11. KUP KB prototype
Currently contain set of example queries that use the
KUP ontology to query the data:
– Which Human genes have evidence for upregulation in the glomerulus?
– In which tissue is "PLA2G4A" expressed and in which biological processes does
it participate?
– What proteins participate in TGF-beta signaling pathways are where are they
upregulated in the kidney?
July 9, 2010Bio-ontologies, Boston
12. Querying the graph
KUPO Ontology
Entre gene
Gene X GO:0054426
go:biological_process
Gene Y
MA:00345
kupo:002444
PT epithelial cell
rdfs:label
ro:part_of
MA:00456
kupo:004672
DT epithelial cell
rdfs:label
ro:part_of
Higgings Dataset
MA:000345
kupo:expressed_in
Gene Y
MA:00456
kupo:expressed_in
Proximal tubule
Distal tubule
Gene X
Query: What are the genes involved in
Proteins transport expressed in Proximal Tubule Epithelial Cell?
July 9, 2010Bio-ontologies, Boston
13. KUP KB: KUP ontology (alpha)
Anatomy (MAO)Anatomy (MAO) Gene Biological
processes(GO)
Gene Biological
processes(GO)
Cells (CTO)Cells (CTO)
part-of
participate-in
Renal
proximal
tubule
Renal
proximal
tubule
Proximal
straight
tubule
Proximal
straight
tubule
Proximal
convoluted
tubule
Proximal
convoluted
tubule
Assertion
Inference
subClassOf
Proximal
tubule
epithelial cell
Proximal
tubule
epithelial cell
Proximal
straight
tubule
epithelial
cell
Proximal
straight
tubule
epithelial
cell
Proximal
convoluted
tubule
epithelial cell
Proximal
convoluted
tubule
epithelial cell
subClassOf
part-of
Renal sodium
absorption
Renal sodium
absorption
Renal sodium
ion absorption
Renal sodium
ion absorption
participates-in
part-of
participates-in
Kidney CortexKidney Cortex
part-of
part-of
Each kidney cell is currently described by its localisation and function
July 9, 2010Bio-ontologies, Boston
14. The KUPO development process
Collaborative
Spreadsheet
Collaborative
Spreadsheet
Individual
Spreadsheet
Individual
Spreadsheet
Issue TrackerIssue Tracker
OPPL
Script
Formulation
OPPL
Script
Formulation
Generate
OWL
Generate
OWL
Reasoned
Ontology
Reasoned
Ontology
View OntologyView Ontology
July 9, 2010Bio-ontologies, Boston
15. KUP KB: –omics data
Asserted relationship
geneid:17638geneid:17638
Entrez
Gene ID
Entrez
Gene ID
type
FaslFasl
symbol
AC18765AC18765
encodes
UNIPROT
ID
UNIPROT
ID
type
We can represent -omics data as a graph
KEGG
pathway
ID
KEGG
pathway
ID
has:00527has:00527
type
participates-in
Fas-ligandFas-ligand
symbol
ApoptosisApoptosis
symbol
July 9, 2010Bio-ontologies, Boston
16. KUP KB: experimental data
Asserted relationship
Geneid:17638Geneid:17638
GEO
Experiment ID
GEO
Experiment ID
GEO:028364GEO:028364
type
sample
Differentially
expressed genes
Differentially
expressed genes
KUPO:
Proximal
straight tubule
KUPO:
Proximal
straight tubule
observation
contains
Higgins et alHiggins et al
contributor
We can represent experimental data as a graph
July 9, 2010Bio-ontologies, Boston
17. Connecting the graphs
GEO:028364GEO:028364
sample
Differentially
expressed genes
Differentially
expressed genes
observation
contains
Higgins et alHiggins et al
contributor geneid:17638geneid:17638
FaslFasl
symbol
AC18765AC18765 has:00527has:00527
participates-in
Fas-ligandFas-ligand
symbol
ApoptosisApoptosis
symbol
Renal
proximal
tubule
Renal
proximal
tubule
Proximal
straight
tubule
Proximal
straight
tubule
Proximal
convoluted
tubule
Proximal
convoluted
tubule
subClassOf
Proximal
tubule
epithelial cell
Proximal
tubule
epithelial cell
Proximal
straight
tubule
epithelial
cell
Proximal
straight
tubule
epithelial
cell
Proximal
convoluted
tubule
epithelial cell
Proximal
convoluted
tubule
epithelial cell
subClassOf
part-of
Renal sodium
absorption
Renal sodium
absorption
Renal sodium
ion absorption
Renal sodium
ion absorption
participates-inpart-of
participates-in
July 9, 2010Bio-ontologies, Boston
18. Bio2RDF
Best practices from W3C Health Care and Life Science Working group.
Bio2RDF ontology as a schema
KUP KB
(RDF store)
July 9, 2010Bio-ontologies, Boston
19. So why RDF over RDMS?
Having a standard representation simply makes my life easier
Lots of heterogeneous KUP data to be integrated
RDF allows me to to simply pile more data in
Natural support for ontologies
Although limited
RDF alone isn’t enough
Next step, intelligent agents and crawlers…
How do we harness all this connected data
July 9, 2010Bio-ontologies, Boston
20. Challenges
Bad modelling (?)
– Conflation of instances and classes
Cells bears some function (that is realised in some
process) vs Cell participates in some Process
False statements and vague semantics
– Trying to accommodate the biologists queries
– Mapping natural language to semantic relationships
– Experiments, expression data, gene lists etc.. It’s hard
Plus a whole list of general Semantic Web related issues
July 9, 2010Bio-ontologies, Boston
21. Data mining
Data mining experiments just started
SPARQL query to generate tables for background knowledge to
data mining tools
Mine results for associations, clusters and predictive models.
Build user friendly tools to hide the underlying technology
Results expected Y2 (later this year….)
July 9, 2010Bio-ontologies, Boston
22. Summary
Rapid and low cost data integration
– Thanks to existing community efforts!!
Single SPARQL endpoint provides flexible queries
– Especially useful for our data-mining queries
Rapid ontology development
– Spreadsheets to engage domain experts
July 9, 2010Bio-ontologies, Boston
23. KUP Knowledge Base in e-LICO
KUP KB
(RDF store)
KUP KB
(RDF store)
Bio2RDF
http://www.e-lico.eu/kupkb
E-LICO
Workflows
Use case data
Raw data
E-LICO
DB
E-LICO
DB
E-LICO
Data Analysis
Web interface
Linked Open Data /
Semantic Web /
Bio ontologies
Linked Open Data /
Semantic Web /
Bio ontologies
Query
Results
Shared meta-data
July 9, 2010Bio-ontologies, Boston
24. Julie Klein, Joost Schanstra
– Inserm, France
Robert Stevens
– University of Manchester
EuroKUP members who already contributed to the
ontology
Acknowledgements
July 9, 2010Bio-ontologies, Boston
25. Challenges
KUP KB implemented as triple store (Sesame)
– Scalable
– Limited inference (RDFS)
Experiments with OWL
– Classification possible (Fact++)
– DL Query language lack desirable features
• Joins, Unions, Filters etc..
July 9, 2010Bio-ontologies, Boston
26. Challenges 2
Re-use existing RDF datasets
– Bio2RDF could be improved
– URI guidelines unclear
• PURLs or OBO URI?
Bio-portal, OBO foundry, Bio2RDF….
– RDF endpoint to bio-portal is great!
July 9, 2010Bio-ontologies, Boston
27. Challenges 4
Warehoused data
– I don’t want to maintain other peoples data
Linked data and query federation
– What is possible now?
– SADI framework
July 9, 2010Bio-ontologies, Boston
Editor's Notes
We initially chose a KUP portion of the FMA, but domain experts found that there was too much detail in some sections and not enough in others. In addition, too many ontological distinctions were made within the portion of the FMA and the consequent dispersal of information made it hard to use. In time, we could have refined the FMA to do the job required, but we found that the MAO had all the detail for our needs. Although the connecting tubule is absent in mouse and present in humans, the MAO has this entity. Therefore the MAO can act as a substitute for the human anatomy.
The should have seen this before, also the KUP day at manchester in november. Year 2 add urinary pathway, diseases
The should have seen this before, also the KUP day at manchester in november. Year 2 add urinary pathway, diseases
The should have seen this before, also the KUP day at manchester in november. Year 2 add urinary pathway, diseases