SlideShare a Scribd company logo
1 of 105
Medical data and text mining 
Linking diseases, drugs, and 
adverse reactions 
Lars Juhl Jensen
structured data
Jensen et al., Nature Reviews Genetics, 2012
unstructured data
central registries
individual hospitals
opt-out
opt-in
Danish registries
civil registration system
CPR number
established in 1968
Jensen et al., Nature Reviews Genetics, 2012
national discharge registry
14 years
6.2 million patients
45 million admissions
68 million records
119 million diagnosis
ICD-10
Jensen et al., Nature Reviews Genetics, 2012
not research
reimbursement
diagnosis trajectories
naïve approach
comorbidity
Jensen et al., Nature Reviews Genetics, 2012
confounding factors
“known knowns”
gender
age
type of hospital encounter
Jensen et al., Nature Communications, 2014
“known unknowns”
smoking
diet
“unknown unknowns”
reporting biases
matched controls
temporal correlations
multiple testing
trajectories
Jensen et al., Nature Communications, 2014
trajectory networks
Jensen et al., Nature Communications, 2014
key diagnoses
Jensen et al., Nature Communications, 2014
direct medical implications
electronic health records
structured data
Jensen et al., Nature Reviews Genetics, 2012
unstructured data
free text
Danish
busy doctors
typos
psychiatric patients
text mining
computer
as smart as a dog
teach it specific tricks
comprehensive dictionary
diseases
drugs
adverse drug reactions
expansion rules
Clozapine
Clozapine 
clozapi 
n 
clossapi 
n 
klozapin 
e 
chlosapi 
n 
chlozapi 
chlosapi 
ne 
n 
chlozapi 
ne 
klossapi 
n 
closapin 
e 
klozapi 
klosapi n 
n
flexible matching
compound nouns
post-coordination rules
failure of kidney
kidney failure
“black list”
three-letter acronyms
pharmacovigilance
clinical trials
spontaneous reports
underreporting
data mining
structured data
medication
semi-structured data
drug indications
known ADRs
unstructured data
adverse drug reactions
temporal correlations
hand-crafted rules
Drug introduction Adverse event Drug discontinuation 
Negative modifier Indication Pre-existing Adverse event 
Eriksson et al., Drug Safety, 2014 
condition 
Adverse drug reaction Possible 
adverse drug reaction 
ADR of 
additional drug
Drug introduction Identification star t Adverse event Drug discontinuation 
Negative modifier Indication Pre-existing Adverse event 
Eriksson et al., Drug Safety, 2014 
condition 
Adverse drug reaction Possible 
adverse drug reaction 
ADR of 
additional drug
Drug introduction Drug discontinuation 
Negative modifier Indication Pre-existing Adverse event 
Eriksson et al., Drug Safety, 2014 
condition 
Adverse drug reaction Possible 
adverse drug reaction 
Adverse event 
ADR of 
additional drug 
Identification star t
Drug introduction Drug discontinuation 
Negative modifier Indication Pre-existing Adverse event 
Eriksson et al., Drug Safety, 2014 
condition 
Adverse drug reaction Possible 
adverse drug reaction 
Adverse event 
ADR of 
additional drug 
Identification star t
recall known ADRs
estimate ADR frequencies
Eriksson et al., Drug Safety, 2014
discover new ADRs
Drug substance ADE p-value 
Chlordiazepoxide Nystagmus 4.0e-8 
Simvastatin Personality 
changes 
8.4e-8 
Dipyridamole Visual impairment 4.4e-4 
Citalopram Psychosis 8.8e-4 
Bendroflumethiazi 
Apoplexy 8.5e-3 
de 
Eriksson et al., Drug Safety, 2014
Acknowledgments 
Disease trajectories 
Anders Bøck Jensen 
Tudor Oprea 
Pope Moseley 
Søren Brunak 
Adverse drug reactions 
Robert Eriksson 
Thomas Werge 
Søren Brunak 
EHR text mining 
Peter Bjødstrup 
Jensen 
Robert Eriksson 
Henriette Schmock 
Francisco S. Roque 
Anders Juul 
Marlene Dalgaard 
Massimo Andreatta 
Sune Frankild 
Eva Roitmann 
Thomas Hansen 
Karen Søeby 
Søren Bredkjær 
Thomas Werge 
Søren Brunak

More Related Content

What's hot

Data and text mining of Danish electronic health records
Data and text mining of Danish electronic health recordsData and text mining of Danish electronic health records
Data and text mining of Danish electronic health recordsLars Juhl Jensen
 
Medical data and text mining: Linking diseases, drugs, and adverse reactions
Medical data and text mining: Linking diseases, drugs, and adverse reactionsMedical data and text mining: Linking diseases, drugs, and adverse reactions
Medical data and text mining: Linking diseases, drugs, and adverse reactionsLars Juhl Jensen
 
Data and text mining of electronic health records
Data and text mining of electronic health recordsData and text mining of electronic health records
Data and text mining of electronic health recordsLars Juhl Jensen
 
Medical data and text mining - Linking diseases, drugs, and adverse reactions
Medical data and text mining - Linking diseases, drugs, and adverse reactionsMedical data and text mining - Linking diseases, drugs, and adverse reactions
Medical data and text mining - Linking diseases, drugs, and adverse reactionsLars Juhl Jensen
 
Medical data and text mining: Linking diseases, drugs, and adverse reactions
Medical data and text mining: Linking diseases, drugs, and adverse reactionsMedical data and text mining: Linking diseases, drugs, and adverse reactions
Medical data and text mining: Linking diseases, drugs, and adverse reactionsLars Juhl Jensen
 
Statistical analysis of the health profile of Field ganj (Area C),Ludhiana ,I...
Statistical analysis of the health profile of Field ganj (Area C),Ludhiana ,I...Statistical analysis of the health profile of Field ganj (Area C),Ludhiana ,I...
Statistical analysis of the health profile of Field ganj (Area C),Ludhiana ,I...Jerin Kuruvilla
 
IMA perspective of pharmacovigilance
IMA perspective of pharmacovigilanceIMA perspective of pharmacovigilance
IMA perspective of pharmacovigilancePHARMAQUEST Vydehi
 
A SEEMINGLY BENIGN DRUG IN THE SPOTLIGHT: AN EDUCATIONAL INTERVENTION TO REDU...
A SEEMINGLY BENIGN DRUG IN THE SPOTLIGHT: AN EDUCATIONAL INTERVENTION TO REDU...A SEEMINGLY BENIGN DRUG IN THE SPOTLIGHT: AN EDUCATIONAL INTERVENTION TO REDU...
A SEEMINGLY BENIGN DRUG IN THE SPOTLIGHT: AN EDUCATIONAL INTERVENTION TO REDU...Khushboo Gandhi
 
Role of Personal Protective Measures in Prevention of COVID-19 Spread Among P...
Role of Personal Protective Measures in Prevention of COVID-19 Spread Among P...Role of Personal Protective Measures in Prevention of COVID-19 Spread Among P...
Role of Personal Protective Measures in Prevention of COVID-19 Spread Among P...NurFathihaTahiatSeeu
 
BZDs Patients Substance Abuse2010 Zuschlag M
BZDs Patients Substance Abuse2010 Zuschlag MBZDs Patients Substance Abuse2010 Zuschlag M
BZDs Patients Substance Abuse2010 Zuschlag Mzuschette
 
Sinusite Bacteriana Aguda na Infância: Diagnóstico e Tratamento
Sinusite Bacteriana Aguda na Infância: Diagnóstico e Tratamento Sinusite Bacteriana Aguda na Infância: Diagnóstico e Tratamento
Sinusite Bacteriana Aguda na Infância: Diagnóstico e Tratamento blogped1
 

What's hot (18)

Data and text mining of Danish electronic health records
Data and text mining of Danish electronic health recordsData and text mining of Danish electronic health records
Data and text mining of Danish electronic health records
 
Medical data and text mining: Linking diseases, drugs, and adverse reactions
Medical data and text mining: Linking diseases, drugs, and adverse reactionsMedical data and text mining: Linking diseases, drugs, and adverse reactions
Medical data and text mining: Linking diseases, drugs, and adverse reactions
 
Data and text mining of electronic health records
Data and text mining of electronic health recordsData and text mining of electronic health records
Data and text mining of electronic health records
 
Medical Data Mining
Medical Data MiningMedical Data Mining
Medical Data Mining
 
Medical Data Mining
Medical Data MiningMedical Data Mining
Medical Data Mining
 
Medical data and text mining - Linking diseases, drugs, and adverse reactions
Medical data and text mining - Linking diseases, drugs, and adverse reactionsMedical data and text mining - Linking diseases, drugs, and adverse reactions
Medical data and text mining - Linking diseases, drugs, and adverse reactions
 
Medical data and text mining: Linking diseases, drugs, and adverse reactions
Medical data and text mining: Linking diseases, drugs, and adverse reactionsMedical data and text mining: Linking diseases, drugs, and adverse reactions
Medical data and text mining: Linking diseases, drugs, and adverse reactions
 
Statistical analysis of the health profile of Field ganj (Area C),Ludhiana ,I...
Statistical analysis of the health profile of Field ganj (Area C),Ludhiana ,I...Statistical analysis of the health profile of Field ganj (Area C),Ludhiana ,I...
Statistical analysis of the health profile of Field ganj (Area C),Ludhiana ,I...
 
IMA perspective of pharmacovigilance
IMA perspective of pharmacovigilanceIMA perspective of pharmacovigilance
IMA perspective of pharmacovigilance
 
SCHS Topic6: Medical Errors
SCHS Topic6: Medical ErrorsSCHS Topic6: Medical Errors
SCHS Topic6: Medical Errors
 
A SEEMINGLY BENIGN DRUG IN THE SPOTLIGHT: AN EDUCATIONAL INTERVENTION TO REDU...
A SEEMINGLY BENIGN DRUG IN THE SPOTLIGHT: AN EDUCATIONAL INTERVENTION TO REDU...A SEEMINGLY BENIGN DRUG IN THE SPOTLIGHT: AN EDUCATIONAL INTERVENTION TO REDU...
A SEEMINGLY BENIGN DRUG IN THE SPOTLIGHT: AN EDUCATIONAL INTERVENTION TO REDU...
 
1138-4368-3-PB.pdf
1138-4368-3-PB.pdf1138-4368-3-PB.pdf
1138-4368-3-PB.pdf
 
Role of Personal Protective Measures in Prevention of COVID-19 Spread Among P...
Role of Personal Protective Measures in Prevention of COVID-19 Spread Among P...Role of Personal Protective Measures in Prevention of COVID-19 Spread Among P...
Role of Personal Protective Measures in Prevention of COVID-19 Spread Among P...
 
ISPOR podium presentation
ISPOR podium presentationISPOR podium presentation
ISPOR podium presentation
 
Asthma
AsthmaAsthma
Asthma
 
Adult Attention Deficit Hyperactivity Disorder in Patients with Fibromyalgia ...
Adult Attention Deficit Hyperactivity Disorder in Patients with Fibromyalgia ...Adult Attention Deficit Hyperactivity Disorder in Patients with Fibromyalgia ...
Adult Attention Deficit Hyperactivity Disorder in Patients with Fibromyalgia ...
 
BZDs Patients Substance Abuse2010 Zuschlag M
BZDs Patients Substance Abuse2010 Zuschlag MBZDs Patients Substance Abuse2010 Zuschlag M
BZDs Patients Substance Abuse2010 Zuschlag M
 
Sinusite Bacteriana Aguda na Infância: Diagnóstico e Tratamento
Sinusite Bacteriana Aguda na Infância: Diagnóstico e Tratamento Sinusite Bacteriana Aguda na Infância: Diagnóstico e Tratamento
Sinusite Bacteriana Aguda na Infância: Diagnóstico e Tratamento
 

Viewers also liked

Protein networks: A basis for large-scale data mining
Protein networks: A basis for large-scale data miningProtein networks: A basis for large-scale data mining
Protein networks: A basis for large-scale data miningLars Juhl Jensen
 
Data integration with STRING
Data integration with STRINGData integration with STRING
Data integration with STRINGLars Juhl Jensen
 
Systems biology: Large-scale biomedical data mining
Systems biology: Large-scale biomedical data miningSystems biology: Large-scale biomedical data mining
Systems biology: Large-scale biomedical data miningLars Juhl Jensen
 
The pragmatic text miner: It's just another type of poorly standardized data
The pragmatic text miner: It's just another type of poorly standardized dataThe pragmatic text miner: It's just another type of poorly standardized data
The pragmatic text miner: It's just another type of poorly standardized dataLars Juhl Jensen
 
Network biology: A basis for large-scale biomedical data mining
Network biology: A basis for large-scale biomedical data miningNetwork biology: A basis for large-scale biomedical data mining
Network biology: A basis for large-scale biomedical data miningLars Juhl Jensen
 
Using networks to derive function
Using networks to derive functionUsing networks to derive function
Using networks to derive functionLars Juhl Jensen
 
One tagger, many uses - Illustrating the power of ontologies in named entity ...
One tagger, many uses - Illustrating the power of ontologies in named entity ...One tagger, many uses - Illustrating the power of ontologies in named entity ...
One tagger, many uses - Illustrating the power of ontologies in named entity ...Lars Juhl Jensen
 

Viewers also liked (9)

Protein networks: A basis for large-scale data mining
Protein networks: A basis for large-scale data miningProtein networks: A basis for large-scale data mining
Protein networks: A basis for large-scale data mining
 
Applied text mining
Applied text miningApplied text mining
Applied text mining
 
Data integration with STRING
Data integration with STRINGData integration with STRING
Data integration with STRING
 
Systems biology: Large-scale biomedical data mining
Systems biology: Large-scale biomedical data miningSystems biology: Large-scale biomedical data mining
Systems biology: Large-scale biomedical data mining
 
The pragmatic text miner: It's just another type of poorly standardized data
The pragmatic text miner: It's just another type of poorly standardized dataThe pragmatic text miner: It's just another type of poorly standardized data
The pragmatic text miner: It's just another type of poorly standardized data
 
Network biology: A basis for large-scale biomedical data mining
Network biology: A basis for large-scale biomedical data miningNetwork biology: A basis for large-scale biomedical data mining
Network biology: A basis for large-scale biomedical data mining
 
Applied text mining
Applied text miningApplied text mining
Applied text mining
 
Using networks to derive function
Using networks to derive functionUsing networks to derive function
Using networks to derive function
 
One tagger, many uses - Illustrating the power of ontologies in named entity ...
One tagger, many uses - Illustrating the power of ontologies in named entity ...One tagger, many uses - Illustrating the power of ontologies in named entity ...
One tagger, many uses - Illustrating the power of ontologies in named entity ...
 

Similar to Medical data and text mining: Linking diseases, drugs, and adverse reactions

Medical data and text mining - Linking diseases, drugs, and adverse reactions
Medical data and text mining - Linking diseases, drugs, and adverse reactionsMedical data and text mining - Linking diseases, drugs, and adverse reactions
Medical data and text mining - Linking diseases, drugs, and adverse reactionsLars Juhl Jensen
 
Medical data and text mining: Linking diseases, drugs, and adverse reactions
Medical data and text mining: Linking diseases, drugs, and adverse reactionsMedical data and text mining: Linking diseases, drugs, and adverse reactions
Medical data and text mining: Linking diseases, drugs, and adverse reactionsLars Juhl Jensen
 
Medical data and text mining: Linking diseases, drugs, and adverse reactions
Medical data and text mining: Linking diseases, drugs, and adverse reactionsMedical data and text mining: Linking diseases, drugs, and adverse reactions
Medical data and text mining: Linking diseases, drugs, and adverse reactionsLars Juhl Jensen
 
Medical data and text mining: Linking diseases, drugs, and adverse reactions
Medical data and text mining: Linking diseases, drugs, and adverse reactionsMedical data and text mining: Linking diseases, drugs, and adverse reactions
Medical data and text mining: Linking diseases, drugs, and adverse reactionsLars Juhl Jensen
 
Large-scale biomedical data and text integration
Large-scale biomedical data and text integrationLarge-scale biomedical data and text integration
Large-scale biomedical data and text integrationLars Juhl Jensen
 
Medical text mining: Linking diseases, drugs, and adverse reactions
Medical text mining: Linking diseases, drugs, and adverse reactionsMedical text mining: Linking diseases, drugs, and adverse reactions
Medical text mining: Linking diseases, drugs, and adverse reactionsLars Juhl Jensen
 
Hvordan bør vi udnytte mulighederne for analyse af registre og sundhedsdata i...
Hvordan bør vi udnytte mulighederne foranalyse af registre og sundhedsdata i...Hvordan bør vi udnytte mulighederne foranalyse af registre og sundhedsdata i...
Hvordan bør vi udnytte mulighederne for analyse af registre og sundhedsdata i...Lars Juhl Jensen
 
Large-scale integration of data and text
Large-scale integration of data and textLarge-scale integration of data and text
Large-scale integration of data and textLars Juhl Jensen
 
Medical network analysis: Linking diseases and genes through data and text mi...
Medical network analysis: Linking diseases and genes through data and text mi...Medical network analysis: Linking diseases and genes through data and text mi...
Medical network analysis: Linking diseases and genes through data and text mi...Lars Juhl Jensen
 
Holistic dentistry 18 nov-11-1
Holistic dentistry 18 nov-11-1Holistic dentistry 18 nov-11-1
Holistic dentistry 18 nov-11-1Iyad Abou Rabii
 
Large-scale integration of data and text
Large-scale integration of data and textLarge-scale integration of data and text
Large-scale integration of data and textLars Juhl Jensen
 
Open data and open access - A biomedical data- and text-mining perspective
Open data and open access - A biomedical data- and text-mining perspectiveOpen data and open access - A biomedical data- and text-mining perspective
Open data and open access - A biomedical data- and text-mining perspectiveLars Juhl Jensen
 
Spontaneous Reporting and Prescription Event Monitoring.pptx
Spontaneous Reporting and Prescription Event Monitoring.pptxSpontaneous Reporting and Prescription Event Monitoring.pptx
Spontaneous Reporting and Prescription Event Monitoring.pptxDrRajeshHadia
 
Physicians being deceived
Physicians being deceivedPhysicians being deceived
Physicians being deceivedPaul Coelho, MD
 
Wekerle CIHR Team - Personality and Risk for Substance Abuse: The Preventure ...
Wekerle CIHR Team - Personality and Risk for Substance Abuse: The Preventure ...Wekerle CIHR Team - Personality and Risk for Substance Abuse: The Preventure ...
Wekerle CIHR Team - Personality and Risk for Substance Abuse: The Preventure ...Christine Wekerle
 

Similar to Medical data and text mining: Linking diseases, drugs, and adverse reactions (20)

Medical data and text mining - Linking diseases, drugs, and adverse reactions
Medical data and text mining - Linking diseases, drugs, and adverse reactionsMedical data and text mining - Linking diseases, drugs, and adverse reactions
Medical data and text mining - Linking diseases, drugs, and adverse reactions
 
Medical data and text mining: Linking diseases, drugs, and adverse reactions
Medical data and text mining: Linking diseases, drugs, and adverse reactionsMedical data and text mining: Linking diseases, drugs, and adverse reactions
Medical data and text mining: Linking diseases, drugs, and adverse reactions
 
Medical data and text mining: Linking diseases, drugs, and adverse reactions
Medical data and text mining: Linking diseases, drugs, and adverse reactionsMedical data and text mining: Linking diseases, drugs, and adverse reactions
Medical data and text mining: Linking diseases, drugs, and adverse reactions
 
Medical data and text mining: Linking diseases, drugs, and adverse reactions
Medical data and text mining: Linking diseases, drugs, and adverse reactionsMedical data and text mining: Linking diseases, drugs, and adverse reactions
Medical data and text mining: Linking diseases, drugs, and adverse reactions
 
Medical data mining
Medical data miningMedical data mining
Medical data mining
 
Large-scale biomedical data and text integration
Large-scale biomedical data and text integrationLarge-scale biomedical data and text integration
Large-scale biomedical data and text integration
 
Medical text mining: Linking diseases, drugs, and adverse reactions
Medical text mining: Linking diseases, drugs, and adverse reactionsMedical text mining: Linking diseases, drugs, and adverse reactions
Medical text mining: Linking diseases, drugs, and adverse reactions
 
Medical Data Mining
Medical Data MiningMedical Data Mining
Medical Data Mining
 
Medical data mining
Medical data miningMedical data mining
Medical data mining
 
Hvordan bør vi udnytte mulighederne for analyse af registre og sundhedsdata i...
Hvordan bør vi udnytte mulighederne foranalyse af registre og sundhedsdata i...Hvordan bør vi udnytte mulighederne foranalyse af registre og sundhedsdata i...
Hvordan bør vi udnytte mulighederne for analyse af registre og sundhedsdata i...
 
Large-scale integration of data and text
Large-scale integration of data and textLarge-scale integration of data and text
Large-scale integration of data and text
 
Medical network analysis: Linking diseases and genes through data and text mi...
Medical network analysis: Linking diseases and genes through data and text mi...Medical network analysis: Linking diseases and genes through data and text mi...
Medical network analysis: Linking diseases and genes through data and text mi...
 
Holistic dentistry 18 nov-11-1
Holistic dentistry 18 nov-11-1Holistic dentistry 18 nov-11-1
Holistic dentistry 18 nov-11-1
 
Large-scale integration of data and text
Large-scale integration of data and textLarge-scale integration of data and text
Large-scale integration of data and text
 
Open data and open access - A biomedical data- and text-mining perspective
Open data and open access - A biomedical data- and text-mining perspectiveOpen data and open access - A biomedical data- and text-mining perspective
Open data and open access - A biomedical data- and text-mining perspective
 
Cellular Network Biology
Cellular Network BiologyCellular Network Biology
Cellular Network Biology
 
Spontaneous Reporting and Prescription Event Monitoring.pptx
Spontaneous Reporting and Prescription Event Monitoring.pptxSpontaneous Reporting and Prescription Event Monitoring.pptx
Spontaneous Reporting and Prescription Event Monitoring.pptx
 
Physicians being deceived
Physicians being deceivedPhysicians being deceived
Physicians being deceived
 
New pattern clinical study
New pattern clinical studyNew pattern clinical study
New pattern clinical study
 
Wekerle CIHR Team - Personality and Risk for Substance Abuse: The Preventure ...
Wekerle CIHR Team - Personality and Risk for Substance Abuse: The Preventure ...Wekerle CIHR Team - Personality and Risk for Substance Abuse: The Preventure ...
Wekerle CIHR Team - Personality and Risk for Substance Abuse: The Preventure ...
 

More from Lars Juhl Jensen

One tagger, many uses: Illustrating the power of dictionary-based named entit...
One tagger, many uses: Illustrating the power of dictionary-based named entit...One tagger, many uses: Illustrating the power of dictionary-based named entit...
One tagger, many uses: Illustrating the power of dictionary-based named entit...Lars Juhl Jensen
 
One tagger, many uses: Simple text-mining strategies for biomedicine
One tagger, many uses: Simple text-mining strategies for biomedicineOne tagger, many uses: Simple text-mining strategies for biomedicine
One tagger, many uses: Simple text-mining strategies for biomedicineLars Juhl Jensen
 
Extract 2.0: Text-mining-assisted interactive annotation
Extract 2.0: Text-mining-assisted interactive annotationExtract 2.0: Text-mining-assisted interactive annotation
Extract 2.0: Text-mining-assisted interactive annotationLars Juhl Jensen
 
Network visualization: A crash course on using Cytoscape
Network visualization: A crash course on using CytoscapeNetwork visualization: A crash course on using Cytoscape
Network visualization: A crash course on using CytoscapeLars Juhl Jensen
 
STRING & STITCH : Network integration of heterogeneous data
STRING & STITCH: Network integration of heterogeneous dataSTRING & STITCH: Network integration of heterogeneous data
STRING & STITCH : Network integration of heterogeneous dataLars Juhl Jensen
 
Biomedical text mining: Automatic processing of unstructured text
Biomedical text mining: Automatic processing of unstructured textBiomedical text mining: Automatic processing of unstructured text
Biomedical text mining: Automatic processing of unstructured textLars Juhl Jensen
 
Network Biology: A crash course on STRING and Cytoscape
Network Biology: A crash course on STRING and CytoscapeNetwork Biology: A crash course on STRING and Cytoscape
Network Biology: A crash course on STRING and CytoscapeLars Juhl Jensen
 
Cellular Network Biology: Large-scale integration of data and text
Cellular Network Biology: Large-scale integration of data and textCellular Network Biology: Large-scale integration of data and text
Cellular Network Biology: Large-scale integration of data and textLars Juhl Jensen
 
Statistics on big biomedical data: Methods and pitfalls when analyzing high-t...
Statistics on big biomedical data: Methods and pitfalls when analyzing high-t...Statistics on big biomedical data: Methods and pitfalls when analyzing high-t...
Statistics on big biomedical data: Methods and pitfalls when analyzing high-t...Lars Juhl Jensen
 
STRING & related databases: Large-scale integration of heterogeneous data
STRING & related databases: Large-scale integration of heterogeneous dataSTRING & related databases: Large-scale integration of heterogeneous data
STRING & related databases: Large-scale integration of heterogeneous dataLars Juhl Jensen
 
Tagger: Rapid dictionary-based named entity recognition
Tagger: Rapid dictionary-based named entity recognitionTagger: Rapid dictionary-based named entity recognition
Tagger: Rapid dictionary-based named entity recognitionLars Juhl Jensen
 
Network Biology: Large-scale integration of data and text
Network Biology: Large-scale integration of data and textNetwork Biology: Large-scale integration of data and text
Network Biology: Large-scale integration of data and textLars Juhl Jensen
 
Network biology: Large-scale integration of data and text
Network biology: Large-scale integration of data and textNetwork biology: Large-scale integration of data and text
Network biology: Large-scale integration of data and textLars Juhl Jensen
 
Network biology: Large-scale integration of data and text
Network biology: Large-scale integration of data and textNetwork biology: Large-scale integration of data and text
Network biology: Large-scale integration of data and textLars Juhl Jensen
 
Biomarker bioinformatics: Network-based candidate prioritization
Biomarker bioinformatics: Network-based candidate prioritizationBiomarker bioinformatics: Network-based candidate prioritization
Biomarker bioinformatics: Network-based candidate prioritizationLars Juhl Jensen
 
The Art of Counting: Scoring and ranking co-occurrences in literature
The Art of Counting: Scoring and ranking co-occurrences in literatureThe Art of Counting: Scoring and ranking co-occurrences in literature
The Art of Counting: Scoring and ranking co-occurrences in literatureLars Juhl Jensen
 
Text-mining-based retrieval of protein networks
Text-mining-based retrieval of protein networksText-mining-based retrieval of protein networks
Text-mining-based retrieval of protein networksLars Juhl Jensen
 
Gene association networks: Large-scale integration of data and text
Gene association networks: Large-scale integration of data and textGene association networks: Large-scale integration of data and text
Gene association networks: Large-scale integration of data and textLars Juhl Jensen
 
Protein association networks: Large-scale integration of data and text
Protein association networks: Large-scale integration of data and textProtein association networks: Large-scale integration of data and text
Protein association networks: Large-scale integration of data and textLars Juhl Jensen
 

More from Lars Juhl Jensen (20)

One tagger, many uses: Illustrating the power of dictionary-based named entit...
One tagger, many uses: Illustrating the power of dictionary-based named entit...One tagger, many uses: Illustrating the power of dictionary-based named entit...
One tagger, many uses: Illustrating the power of dictionary-based named entit...
 
One tagger, many uses: Simple text-mining strategies for biomedicine
One tagger, many uses: Simple text-mining strategies for biomedicineOne tagger, many uses: Simple text-mining strategies for biomedicine
One tagger, many uses: Simple text-mining strategies for biomedicine
 
Extract 2.0: Text-mining-assisted interactive annotation
Extract 2.0: Text-mining-assisted interactive annotationExtract 2.0: Text-mining-assisted interactive annotation
Extract 2.0: Text-mining-assisted interactive annotation
 
Network visualization: A crash course on using Cytoscape
Network visualization: A crash course on using CytoscapeNetwork visualization: A crash course on using Cytoscape
Network visualization: A crash course on using Cytoscape
 
STRING & STITCH : Network integration of heterogeneous data
STRING & STITCH: Network integration of heterogeneous dataSTRING & STITCH: Network integration of heterogeneous data
STRING & STITCH : Network integration of heterogeneous data
 
Biomedical text mining: Automatic processing of unstructured text
Biomedical text mining: Automatic processing of unstructured textBiomedical text mining: Automatic processing of unstructured text
Biomedical text mining: Automatic processing of unstructured text
 
Network Biology: A crash course on STRING and Cytoscape
Network Biology: A crash course on STRING and CytoscapeNetwork Biology: A crash course on STRING and Cytoscape
Network Biology: A crash course on STRING and Cytoscape
 
Cellular networks
Cellular networksCellular networks
Cellular networks
 
Cellular Network Biology: Large-scale integration of data and text
Cellular Network Biology: Large-scale integration of data and textCellular Network Biology: Large-scale integration of data and text
Cellular Network Biology: Large-scale integration of data and text
 
Statistics on big biomedical data: Methods and pitfalls when analyzing high-t...
Statistics on big biomedical data: Methods and pitfalls when analyzing high-t...Statistics on big biomedical data: Methods and pitfalls when analyzing high-t...
Statistics on big biomedical data: Methods and pitfalls when analyzing high-t...
 
STRING & related databases: Large-scale integration of heterogeneous data
STRING & related databases: Large-scale integration of heterogeneous dataSTRING & related databases: Large-scale integration of heterogeneous data
STRING & related databases: Large-scale integration of heterogeneous data
 
Tagger: Rapid dictionary-based named entity recognition
Tagger: Rapid dictionary-based named entity recognitionTagger: Rapid dictionary-based named entity recognition
Tagger: Rapid dictionary-based named entity recognition
 
Network Biology: Large-scale integration of data and text
Network Biology: Large-scale integration of data and textNetwork Biology: Large-scale integration of data and text
Network Biology: Large-scale integration of data and text
 
Network biology: Large-scale integration of data and text
Network biology: Large-scale integration of data and textNetwork biology: Large-scale integration of data and text
Network biology: Large-scale integration of data and text
 
Network biology: Large-scale integration of data and text
Network biology: Large-scale integration of data and textNetwork biology: Large-scale integration of data and text
Network biology: Large-scale integration of data and text
 
Biomarker bioinformatics: Network-based candidate prioritization
Biomarker bioinformatics: Network-based candidate prioritizationBiomarker bioinformatics: Network-based candidate prioritization
Biomarker bioinformatics: Network-based candidate prioritization
 
The Art of Counting: Scoring and ranking co-occurrences in literature
The Art of Counting: Scoring and ranking co-occurrences in literatureThe Art of Counting: Scoring and ranking co-occurrences in literature
The Art of Counting: Scoring and ranking co-occurrences in literature
 
Text-mining-based retrieval of protein networks
Text-mining-based retrieval of protein networksText-mining-based retrieval of protein networks
Text-mining-based retrieval of protein networks
 
Gene association networks: Large-scale integration of data and text
Gene association networks: Large-scale integration of data and textGene association networks: Large-scale integration of data and text
Gene association networks: Large-scale integration of data and text
 
Protein association networks: Large-scale integration of data and text
Protein association networks: Large-scale integration of data and textProtein association networks: Large-scale integration of data and text
Protein association networks: Large-scale integration of data and text
 

Recently uploaded

Introduction to Viruses
Introduction to VirusesIntroduction to Viruses
Introduction to VirusesAreesha Ahmad
 
Module for Grade 9 for Asynchronous/Distance learning
Module for Grade 9 for Asynchronous/Distance learningModule for Grade 9 for Asynchronous/Distance learning
Module for Grade 9 for Asynchronous/Distance learninglevieagacer
 
Factory Acceptance Test( FAT).pptx .
Factory Acceptance Test( FAT).pptx       .Factory Acceptance Test( FAT).pptx       .
Factory Acceptance Test( FAT).pptx .Poonam Aher Patil
 
Bacterial Identification and Classifications
Bacterial Identification and ClassificationsBacterial Identification and Classifications
Bacterial Identification and ClassificationsAreesha Ahmad
 
SAMASTIPUR CALL GIRL 7857803690 LOW PRICE ESCORT SERVICE
SAMASTIPUR CALL GIRL 7857803690  LOW PRICE  ESCORT SERVICESAMASTIPUR CALL GIRL 7857803690  LOW PRICE  ESCORT SERVICE
SAMASTIPUR CALL GIRL 7857803690 LOW PRICE ESCORT SERVICEayushi9330
 
Human & Veterinary Respiratory Physilogy_DR.E.Muralinath_Associate Professor....
Human & Veterinary Respiratory Physilogy_DR.E.Muralinath_Associate Professor....Human & Veterinary Respiratory Physilogy_DR.E.Muralinath_Associate Professor....
Human & Veterinary Respiratory Physilogy_DR.E.Muralinath_Associate Professor....muralinath2
 
FAIRSpectra - Enabling the FAIRification of Spectroscopy and Spectrometry
FAIRSpectra - Enabling the FAIRification of Spectroscopy and SpectrometryFAIRSpectra - Enabling the FAIRification of Spectroscopy and Spectrometry
FAIRSpectra - Enabling the FAIRification of Spectroscopy and SpectrometryAlex Henderson
 
development of diagnostic enzyme assay to detect leuser virus
development of diagnostic enzyme assay to detect leuser virusdevelopment of diagnostic enzyme assay to detect leuser virus
development of diagnostic enzyme assay to detect leuser virusNazaninKarimi6
 
9654467111 Call Girls In Raj Nagar Delhi Short 1500 Night 6000
9654467111 Call Girls In Raj Nagar Delhi Short 1500 Night 60009654467111 Call Girls In Raj Nagar Delhi Short 1500 Night 6000
9654467111 Call Girls In Raj Nagar Delhi Short 1500 Night 6000Sapana Sha
 
Thyroid Physiology_Dr.E. Muralinath_ Associate Professor
Thyroid Physiology_Dr.E. Muralinath_ Associate ProfessorThyroid Physiology_Dr.E. Muralinath_ Associate Professor
Thyroid Physiology_Dr.E. Muralinath_ Associate Professormuralinath2
 
Conjugation, transduction and transformation
Conjugation, transduction and transformationConjugation, transduction and transformation
Conjugation, transduction and transformationAreesha Ahmad
 
module for grade 9 for distance learning
module for grade 9 for distance learningmodule for grade 9 for distance learning
module for grade 9 for distance learninglevieagacer
 
Kochi ❤CALL GIRL 84099*07087 ❤CALL GIRLS IN Kochi ESCORT SERVICE❤CALL GIRL
Kochi ❤CALL GIRL 84099*07087 ❤CALL GIRLS IN Kochi ESCORT SERVICE❤CALL GIRLKochi ❤CALL GIRL 84099*07087 ❤CALL GIRLS IN Kochi ESCORT SERVICE❤CALL GIRL
Kochi ❤CALL GIRL 84099*07087 ❤CALL GIRLS IN Kochi ESCORT SERVICE❤CALL GIRLkantirani197
 
Sector 62, Noida Call girls :8448380779 Model Escorts | 100% verified
Sector 62, Noida Call girls :8448380779 Model Escorts | 100% verifiedSector 62, Noida Call girls :8448380779 Model Escorts | 100% verified
Sector 62, Noida Call girls :8448380779 Model Escorts | 100% verifiedDelhi Call girls
 
GBSN - Microbiology (Unit 1)
GBSN - Microbiology (Unit 1)GBSN - Microbiology (Unit 1)
GBSN - Microbiology (Unit 1)Areesha Ahmad
 
FAIRSpectra - Enabling the FAIRification of Analytical Science
FAIRSpectra - Enabling the FAIRification of Analytical ScienceFAIRSpectra - Enabling the FAIRification of Analytical Science
FAIRSpectra - Enabling the FAIRification of Analytical ScienceAlex Henderson
 
COST ESTIMATION FOR A RESEARCH PROJECT.pptx
COST ESTIMATION FOR A RESEARCH PROJECT.pptxCOST ESTIMATION FOR A RESEARCH PROJECT.pptx
COST ESTIMATION FOR A RESEARCH PROJECT.pptxFarihaAbdulRasheed
 
9999266834 Call Girls In Noida Sector 22 (Delhi) Call Girl Service
9999266834 Call Girls In Noida Sector 22 (Delhi) Call Girl Service9999266834 Call Girls In Noida Sector 22 (Delhi) Call Girl Service
9999266834 Call Girls In Noida Sector 22 (Delhi) Call Girl Servicenishacall1
 
❤Jammu Kashmir Call Girls 8617697112 Personal Whatsapp Number 💦✅.
❤Jammu Kashmir Call Girls 8617697112 Personal Whatsapp Number 💦✅.❤Jammu Kashmir Call Girls 8617697112 Personal Whatsapp Number 💦✅.
❤Jammu Kashmir Call Girls 8617697112 Personal Whatsapp Number 💦✅.Nitya salvi
 

Recently uploaded (20)

Introduction to Viruses
Introduction to VirusesIntroduction to Viruses
Introduction to Viruses
 
Site Acceptance Test .
Site Acceptance Test                    .Site Acceptance Test                    .
Site Acceptance Test .
 
Module for Grade 9 for Asynchronous/Distance learning
Module for Grade 9 for Asynchronous/Distance learningModule for Grade 9 for Asynchronous/Distance learning
Module for Grade 9 for Asynchronous/Distance learning
 
Factory Acceptance Test( FAT).pptx .
Factory Acceptance Test( FAT).pptx       .Factory Acceptance Test( FAT).pptx       .
Factory Acceptance Test( FAT).pptx .
 
Bacterial Identification and Classifications
Bacterial Identification and ClassificationsBacterial Identification and Classifications
Bacterial Identification and Classifications
 
SAMASTIPUR CALL GIRL 7857803690 LOW PRICE ESCORT SERVICE
SAMASTIPUR CALL GIRL 7857803690  LOW PRICE  ESCORT SERVICESAMASTIPUR CALL GIRL 7857803690  LOW PRICE  ESCORT SERVICE
SAMASTIPUR CALL GIRL 7857803690 LOW PRICE ESCORT SERVICE
 
Human & Veterinary Respiratory Physilogy_DR.E.Muralinath_Associate Professor....
Human & Veterinary Respiratory Physilogy_DR.E.Muralinath_Associate Professor....Human & Veterinary Respiratory Physilogy_DR.E.Muralinath_Associate Professor....
Human & Veterinary Respiratory Physilogy_DR.E.Muralinath_Associate Professor....
 
FAIRSpectra - Enabling the FAIRification of Spectroscopy and Spectrometry
FAIRSpectra - Enabling the FAIRification of Spectroscopy and SpectrometryFAIRSpectra - Enabling the FAIRification of Spectroscopy and Spectrometry
FAIRSpectra - Enabling the FAIRification of Spectroscopy and Spectrometry
 
development of diagnostic enzyme assay to detect leuser virus
development of diagnostic enzyme assay to detect leuser virusdevelopment of diagnostic enzyme assay to detect leuser virus
development of diagnostic enzyme assay to detect leuser virus
 
9654467111 Call Girls In Raj Nagar Delhi Short 1500 Night 6000
9654467111 Call Girls In Raj Nagar Delhi Short 1500 Night 60009654467111 Call Girls In Raj Nagar Delhi Short 1500 Night 6000
9654467111 Call Girls In Raj Nagar Delhi Short 1500 Night 6000
 
Thyroid Physiology_Dr.E. Muralinath_ Associate Professor
Thyroid Physiology_Dr.E. Muralinath_ Associate ProfessorThyroid Physiology_Dr.E. Muralinath_ Associate Professor
Thyroid Physiology_Dr.E. Muralinath_ Associate Professor
 
Conjugation, transduction and transformation
Conjugation, transduction and transformationConjugation, transduction and transformation
Conjugation, transduction and transformation
 
module for grade 9 for distance learning
module for grade 9 for distance learningmodule for grade 9 for distance learning
module for grade 9 for distance learning
 
Kochi ❤CALL GIRL 84099*07087 ❤CALL GIRLS IN Kochi ESCORT SERVICE❤CALL GIRL
Kochi ❤CALL GIRL 84099*07087 ❤CALL GIRLS IN Kochi ESCORT SERVICE❤CALL GIRLKochi ❤CALL GIRL 84099*07087 ❤CALL GIRLS IN Kochi ESCORT SERVICE❤CALL GIRL
Kochi ❤CALL GIRL 84099*07087 ❤CALL GIRLS IN Kochi ESCORT SERVICE❤CALL GIRL
 
Sector 62, Noida Call girls :8448380779 Model Escorts | 100% verified
Sector 62, Noida Call girls :8448380779 Model Escorts | 100% verifiedSector 62, Noida Call girls :8448380779 Model Escorts | 100% verified
Sector 62, Noida Call girls :8448380779 Model Escorts | 100% verified
 
GBSN - Microbiology (Unit 1)
GBSN - Microbiology (Unit 1)GBSN - Microbiology (Unit 1)
GBSN - Microbiology (Unit 1)
 
FAIRSpectra - Enabling the FAIRification of Analytical Science
FAIRSpectra - Enabling the FAIRification of Analytical ScienceFAIRSpectra - Enabling the FAIRification of Analytical Science
FAIRSpectra - Enabling the FAIRification of Analytical Science
 
COST ESTIMATION FOR A RESEARCH PROJECT.pptx
COST ESTIMATION FOR A RESEARCH PROJECT.pptxCOST ESTIMATION FOR A RESEARCH PROJECT.pptx
COST ESTIMATION FOR A RESEARCH PROJECT.pptx
 
9999266834 Call Girls In Noida Sector 22 (Delhi) Call Girl Service
9999266834 Call Girls In Noida Sector 22 (Delhi) Call Girl Service9999266834 Call Girls In Noida Sector 22 (Delhi) Call Girl Service
9999266834 Call Girls In Noida Sector 22 (Delhi) Call Girl Service
 
❤Jammu Kashmir Call Girls 8617697112 Personal Whatsapp Number 💦✅.
❤Jammu Kashmir Call Girls 8617697112 Personal Whatsapp Number 💦✅.❤Jammu Kashmir Call Girls 8617697112 Personal Whatsapp Number 💦✅.
❤Jammu Kashmir Call Girls 8617697112 Personal Whatsapp Number 💦✅.
 

Medical data and text mining: Linking diseases, drugs, and adverse reactions