The Monarch Initiative: A semantic phenomics approach to disease discovery

8. Mar 2016
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
1 von 28

Más contenido relacionado

Was ist angesagt?

GA4GH Monarch Driver Project IntroductionGA4GH Monarch Driver Project Introduction
GA4GH Monarch Driver Project Introductionmhaendel
The Application of the Human Phenotype Ontology The Application of the Human Phenotype Ontology
The Application of the Human Phenotype Ontology mhaendel
On the frontier of genotype-2-phenotype data integrationOn the frontier of genotype-2-phenotype data integration
On the frontier of genotype-2-phenotype data integrationmhaendel
Semantics for rare disease phenotyping, diagnostics, and discoverySemantics for rare disease phenotyping, diagnostics, and discovery
Semantics for rare disease phenotyping, diagnostics, and discoverymhaendel
Making the most of phenotypes in ontology-based biomedical knowledge discoveryMaking the most of phenotypes in ontology-based biomedical knowledge discovery
Making the most of phenotypes in ontology-based biomedical knowledge discoveryMichel Dumontier
Data Translator: an Open Science Data Platform for Mechanistic Disease DiscoveryData Translator: an Open Science Data Platform for Mechanistic Disease Discovery
Data Translator: an Open Science Data Platform for Mechanistic Disease Discoverymhaendel

Was ist angesagt?(20)

Destacado

ACMG Practice Guideline: lack of evidence for MTHFR  polymorphism testingACMG Practice Guideline: lack of evidence for MTHFR  polymorphism testing
ACMG Practice Guideline: lack of evidence for MTHFR polymorphism testingAsha Reddy
Dataset description using the W3C HCLS standardDataset description using the W3C HCLS standard
Dataset description using the W3C HCLS standardmhaendel
Acmg secondary findings open forum 3 28-12 finalAcmg secondary findings open forum 3 28-12 final
Acmg secondary findings open forum 3 28-12 finalerikanature
The ClinGen Sequence Variant Interpretation Working Group: Refining Criteria ...The ClinGen Sequence Variant Interpretation Working Group: Refining Criteria ...
The ClinGen Sequence Variant Interpretation Working Group: Refining Criteria ...Human Variome Project
How open is open?  An evaluation rubric for public knowledgebasesHow open is open?  An evaluation rubric for public knowledgebases
How open is open? An evaluation rubric for public knowledgebasesmhaendel
Creating presentations that don't suckCreating presentations that don't suck
Creating presentations that don't suckmhaendel

Similar a The Monarch Initiative: A semantic phenomics approach to disease discovery

Festival of Genomics 2016 London: Challenges of Big Medical Data?Festival of Genomics 2016 London: Challenges of Big Medical Data?
Festival of Genomics 2016 London: Challenges of Big Medical Data?Matthieu Schapranow
Gesundheit geht uns alle an: Smart Data ermöglicht passendere Entscheidungen...Gesundheit geht uns alle an: Smart Data ermöglicht passendere Entscheidungen...
Gesundheit geht uns alle an: Smart Data ermöglicht passendere Entscheidungen...Matthieu Schapranow
"When time matters...""When time matters..."
"When time matters..."Matthieu Schapranow
Analyze Genomes Services for Precision MedicineAnalyze Genomes Services for Precision Medicine
Analyze Genomes Services for Precision MedicineMatthieu Schapranow
Analyze Genomes Services for Precision MedicineAnalyze Genomes Services for Precision Medicine
Analyze Genomes Services for Precision MedicineMatthieu Schapranow
Big Data in Life SciencesBig Data in Life Sciences
Big Data in Life SciencesMatthieu Schapranow

Similar a The Monarch Initiative: A semantic phenomics approach to disease discovery(20)

Más de mhaendel

The Software and Data Licensing Solution: Not Your Dad’s UBMTA The Software and Data Licensing Solution: Not Your Dad’s UBMTA
The Software and Data Licensing Solution: Not Your Dad’s UBMTA mhaendel
Equivalence is in the (ID) of the beholderEquivalence is in the (ID) of the beholder
Equivalence is in the (ID) of the beholdermhaendel
Building (and traveling) the data-brick road:  A report from the front lines ...Building (and traveling) the data-brick road:  A report from the front lines ...
Building (and traveling) the data-brick road: A report from the front lines ...mhaendel
Reusable data for biomedicine:  A data licensing odysseyReusable data for biomedicine:  A data licensing odyssey
Reusable data for biomedicine: A data licensing odysseymhaendel
Science in the open, what does it take?Science in the open, what does it take?
Science in the open, what does it take?mhaendel
Credit where credit is due: acknowledging all types of contributionsCredit where credit is due: acknowledging all types of contributions
Credit where credit is due: acknowledging all types of contributionsmhaendel

Último

RS_Energy_function_V2.pdfRS_Energy_function_V2.pdf
RS_Energy_function_V2.pdfRakesh Sengupta
GSD-Grassy Shoot Disease of Sugarcane.pdfGSD-Grassy Shoot Disease of Sugarcane.pdf
GSD-Grassy Shoot Disease of Sugarcane.pdfShubhangi Patil
Self-Organisation Programming: a Functional Reactive Macro Approach (FRASP) [...Self-Organisation Programming: a Functional Reactive Macro Approach (FRASP) [...
Self-Organisation Programming: a Functional Reactive Macro Approach (FRASP) [...Roberto Casadei
Astronomaly at Scale: Searching for Anomalies Amongst 4 Million GalaxiesAstronomaly at Scale: Searching for Anomalies Amongst 4 Million Galaxies
Astronomaly at Scale: Searching for Anomalies Amongst 4 Million GalaxiesSérgio Sacani
Cormas RMoDCormas RMoD
Cormas RMoDOleksandr Zaitsev
SDS PAGE, WESTERN BLOTTING, AND ELISASDS PAGE, WESTERN BLOTTING, AND ELISA
SDS PAGE, WESTERN BLOTTING, AND ELISAParulSharma130721

Último(20)

The Monarch Initiative: A semantic phenomics approach to disease discovery

Hinweis der Redaktion

  1. We understand central hypothesis DNA RNA Protein  building blocks We’ve found reliable methods to describe and move genetic information around with computers. that we can see/ assess phenotype, but how do you computationally describe it ? Massive amounts of genetic data must also be able to be aligned with a phenotype – in a way that a machine can reason and infer an undiagnosed genetic patient having several phenotypes (asymmetry of face, temporal bulging, café au lait on neck, asymmetric smile/ facial animation, uneven eyes.
  2. There is a lot we don’t know about the genome
  3. Adding phenotype
  4. Our approach is to try and get the machine to understand the terms so that it can assist us intelligently.
  5. Represent organism as a biological subject Represent diseases/genotypes as collections of nodes in the graph 3. Interoperable with other bioinformatics resources and leverage modern semantic standards
  6. We can match in “fuzzy” ways by making semantic associations, and leveraging underlying logic, such as anatomy
  7. OWLsim algorithm About HPO 2: We want the vocabulary to be enable sophisticated phenotypic matching within and across species
  8. Data from mouse, rat, zebrafish, worm, fruitfly
  9. Gene-Phenotype Data Genomic data Gene functions Disease/Phenotype vocabularies
  10. This was the novel case we solved. The UDP patient had a number of signs and symptoms including various platelet abnormalities. The same heterozygous, missense mutation was seen in 2 patients and ranked top by Exomiser. It had never been seen in any of the SNP databases and was predicted maximally pathogenic. Finally a mouse curated by MGI involving a heterozygous, missense point mutation introduced by chemical mutagenesis exhibited strikingly similar platelet abnormalities.
  11. Going through HPO and systematically adding synonyms; flagging those that are relevant to the layperson
  12. Fully translational – from bench to bedside – group of stakeholders, contributors and partners