SlideShare ist ein Scribd-Unternehmen logo
1 von 85
Integration of biomedical data and electronic publications Lars Juhl Jensen EMBL Heidelberg
printed publications
dead wood
electronic publications
virtual dead wood
de Lichtenberg et al., Science, 2005
small font sizes
 
“ no”
Jensen et al., Nature Reviews Genetics, 2006
small font sizes
hyperlinks
 
“ no”
“ hell no”
why?
archival
reanalysis
data mining
reader interaction
what?
raw data
processed data
final data
“ facts”
where?
part of the document
too much data
too coarse grained
escalates the problem
institutional repositories
too many types of data
lack of standardization
difficult to download all data
public databases
specialization
standardization
mandatory deposition
easy to download all data
cross references
examples from biomedicine
GenBank
 
17.9 million sequences
80 billion nucleotides
UniProt
 
 
4.7 million sequences
Ensembl
 
35 complete genomes
PDB
 
44000 protein structures
GEO
 
5800 data sets
152000 samples
ArrayExpress
 
1800 data sets
BioGRID
 
186000 interactions
129000 proteins
MINT
 
103000 interactions
28000 proteins
PubChem
 
7.5 million compounds
PubMed Central
 
330 open access journals
12000 open access papers
downloadable
standardized formats
cross-referenced
archival
reanalysis
data mining
reader interaction
thank you!

Weitere ähnliche Inhalte

Was ist angesagt?

Ondex: Data integration and visualisation
Ondex: Data integration and visualisationOndex: Data integration and visualisation
Ondex: Data integration and visualisationBiogeeks
 
Karl kjer : Thinking about science
Karl kjer : Thinking about scienceKarl kjer : Thinking about science
Karl kjer : Thinking about scienceKarl Kjer
 
Idcc kansa-kansa-arbuckle
Idcc kansa-kansa-arbuckleIdcc kansa-kansa-arbuckle
Idcc kansa-kansa-arbuckleEric Kansa
 
Presentation from Code Camp 2017
Presentation from Code Camp 2017Presentation from Code Camp 2017
Presentation from Code Camp 2017Mitch Miller
 
Building a flexible infrastructure with Bioclipse, open source, and federated...
Building a flexible infrastructure with Bioclipse, open source, and federated...Building a flexible infrastructure with Bioclipse, open source, and federated...
Building a flexible infrastructure with Bioclipse, open source, and federated...Ola Spjuth
 
Considerations and challenges in building an end to-end microbiome workflow
Considerations and challenges in building an end to-end microbiome workflowConsiderations and challenges in building an end to-end microbiome workflow
Considerations and challenges in building an end to-end microbiome workflowEagle Genomics
 
American Society for Mass Spectrometry Conference 2013
American Society for Mass Spectrometry Conference 2013American Society for Mass Spectrometry Conference 2013
American Society for Mass Spectrometry Conference 2013Dmitry Grapov
 
Improving discovery in Life Sciences Linked Open Data Cloud
Improving discovery in Life Sciences Linked Open Data CloudImproving discovery in Life Sciences Linked Open Data Cloud
Improving discovery in Life Sciences Linked Open Data CloudSyed Muhammad Ali Hasnain
 
Project Unity: The Way of the Future for Plant Breeding
Project Unity: The Way of the Future for Plant BreedingProject Unity: The Way of the Future for Plant Breeding
Project Unity: The Way of the Future for Plant BreedingPhenome Networks
 
Analyzing Perturbed Co-Expression Networks in Cancer Using a Graph Database
Analyzing Perturbed Co-Expression Networks in Cancer Using a Graph DatabaseAnalyzing Perturbed Co-Expression Networks in Cancer Using a Graph Database
Analyzing Perturbed Co-Expression Networks in Cancer Using a Graph DatabaseNeo4j
 
EiTESAL eHealth Conference 14&15 May 2017
EiTESAL eHealth Conference 14&15 May 2017 EiTESAL eHealth Conference 14&15 May 2017
EiTESAL eHealth Conference 14&15 May 2017 EITESANGO
 
G4 prez with recording final
G4 prez with recording finalG4 prez with recording final
G4 prez with recording finalangelatwong
 
GENOME DATA ANALYSIS
GENOME DATA ANALYSISGENOME DATA ANALYSIS
GENOME DATA ANALYSISAmeldaAkoijam
 
Charleston Conference 2016
Charleston Conference 2016Charleston Conference 2016
Charleston Conference 2016Anita de Waard
 
Mash camp 2011 presentation
Mash camp 2011 presentationMash camp 2011 presentation
Mash camp 2011 presentationmissye2
 
Getting More Phylotastic
Getting More PhylotasticGetting More Phylotastic
Getting More PhylotasticArlin Stoltzfus
 
STRING - Cross-species integration of known and predicted protein-protein int...
STRING - Cross-species integration of known and predicted protein-protein int...STRING - Cross-species integration of known and predicted protein-protein int...
STRING - Cross-species integration of known and predicted protein-protein int...Lars Juhl Jensen
 

Was ist angesagt? (20)

Dr Justin Schonfeld - Bioinformatics Applications
Dr Justin Schonfeld - Bioinformatics ApplicationsDr Justin Schonfeld - Bioinformatics Applications
Dr Justin Schonfeld - Bioinformatics Applications
 
Ondex: Data integration and visualisation
Ondex: Data integration and visualisationOndex: Data integration and visualisation
Ondex: Data integration and visualisation
 
Text mining exercise
Text mining exerciseText mining exercise
Text mining exercise
 
Karl kjer : Thinking about science
Karl kjer : Thinking about scienceKarl kjer : Thinking about science
Karl kjer : Thinking about science
 
Idcc kansa-kansa-arbuckle
Idcc kansa-kansa-arbuckleIdcc kansa-kansa-arbuckle
Idcc kansa-kansa-arbuckle
 
Locus link
Locus linkLocus link
Locus link
 
Presentation from Code Camp 2017
Presentation from Code Camp 2017Presentation from Code Camp 2017
Presentation from Code Camp 2017
 
Building a flexible infrastructure with Bioclipse, open source, and federated...
Building a flexible infrastructure with Bioclipse, open source, and federated...Building a flexible infrastructure with Bioclipse, open source, and federated...
Building a flexible infrastructure with Bioclipse, open source, and federated...
 
Considerations and challenges in building an end to-end microbiome workflow
Considerations and challenges in building an end to-end microbiome workflowConsiderations and challenges in building an end to-end microbiome workflow
Considerations and challenges in building an end to-end microbiome workflow
 
American Society for Mass Spectrometry Conference 2013
American Society for Mass Spectrometry Conference 2013American Society for Mass Spectrometry Conference 2013
American Society for Mass Spectrometry Conference 2013
 
Improving discovery in Life Sciences Linked Open Data Cloud
Improving discovery in Life Sciences Linked Open Data CloudImproving discovery in Life Sciences Linked Open Data Cloud
Improving discovery in Life Sciences Linked Open Data Cloud
 
Project Unity: The Way of the Future for Plant Breeding
Project Unity: The Way of the Future for Plant BreedingProject Unity: The Way of the Future for Plant Breeding
Project Unity: The Way of the Future for Plant Breeding
 
Analyzing Perturbed Co-Expression Networks in Cancer Using a Graph Database
Analyzing Perturbed Co-Expression Networks in Cancer Using a Graph DatabaseAnalyzing Perturbed Co-Expression Networks in Cancer Using a Graph Database
Analyzing Perturbed Co-Expression Networks in Cancer Using a Graph Database
 
EiTESAL eHealth Conference 14&15 May 2017
EiTESAL eHealth Conference 14&15 May 2017 EiTESAL eHealth Conference 14&15 May 2017
EiTESAL eHealth Conference 14&15 May 2017
 
G4 prez with recording final
G4 prez with recording finalG4 prez with recording final
G4 prez with recording final
 
GENOME DATA ANALYSIS
GENOME DATA ANALYSISGENOME DATA ANALYSIS
GENOME DATA ANALYSIS
 
Charleston Conference 2016
Charleston Conference 2016Charleston Conference 2016
Charleston Conference 2016
 
Mash camp 2011 presentation
Mash camp 2011 presentationMash camp 2011 presentation
Mash camp 2011 presentation
 
Getting More Phylotastic
Getting More PhylotasticGetting More Phylotastic
Getting More Phylotastic
 
STRING - Cross-species integration of known and predicted protein-protein int...
STRING - Cross-species integration of known and predicted protein-protein int...STRING - Cross-species integration of known and predicted protein-protein int...
STRING - Cross-species integration of known and predicted protein-protein int...
 

Ähnlich wie Integration of biomedical data and electronic publications

Computational approaches to cell cycle analysis: Data and databases
Computational approaches to cell cycle analysis: Data and databasesComputational approaches to cell cycle analysis: Data and databases
Computational approaches to cell cycle analysis: Data and databasesLars Juhl Jensen
 
Integration of biomedical literature and databases
Integration of biomedical literature and databasesIntegration of biomedical literature and databases
Integration of biomedical literature and databasesLars Juhl Jensen
 
Integration of biomedical literature and databases
Integration of biomedical literature and databasesIntegration of biomedical literature and databases
Integration of biomedical literature and databasesLars Juhl Jensen
 
Systems biology - Understanding biology at the systems level
Systems biology - Understanding biology at the systems levelSystems biology - Understanding biology at the systems level
Systems biology - Understanding biology at the systems levelLars 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
 
STRING: Large-scale data and text mining
STRING: Large-scale data and text miningSTRING: Large-scale data and text mining
STRING: Large-scale data and text miningLars Juhl Jensen
 
Networks of proteins and diseases
Networks of proteins and diseasesNetworks of proteins and diseases
Networks of proteins and diseasesLars Juhl Jensen
 
Exploring proteins, chemicals and their interactions with STRING and STITCH
Exploring proteins, chemicals and their interactions with STRING and STITCHExploring proteins, chemicals and their interactions with STRING and STITCH
Exploring proteins, chemicals and their interactions with STRING and STITCHbiocs
 
Network biology: Large-scale data and text mining
Network biology: Large-scale data and text miningNetwork biology: Large-scale data and text mining
Network biology: Large-scale data and text miningLars Juhl Jensen
 
Data analysis & integration challenges in genomics
Data analysis & integration challenges in genomicsData analysis & integration challenges in genomics
Data analysis & integration challenges in genomicsmikaelhuss
 
Protein interaction networks
Protein interaction networksProtein interaction networks
Protein interaction networksLars Juhl Jensen
 
The STITCH and Reflect web resources
The STITCH and Reflect web resourcesThe STITCH and Reflect web resources
The STITCH and Reflect web resourcesLars 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
 
Protein interaction networks from yeast to human
Protein interaction networks from yeast to humanProtein interaction networks from yeast to human
Protein interaction networks from yeast to humanLars 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
 
Integration of heterogeneous data
Integration of heterogeneous dataIntegration of heterogeneous data
Integration of heterogeneous dataLars Juhl Jensen
 
protein databases.ppt
protein databases.pptprotein databases.ppt
protein databases.pptSanthiyaAK
 
Bioinformatics - Discovering the Bio Logic Of Nature
Bioinformatics - Discovering the Bio Logic Of NatureBioinformatics - Discovering the Bio Logic Of Nature
Bioinformatics - Discovering the Bio Logic Of NatureRobert Cormia
 
Connecting life sciences data at the European Bioinformatics Institute
Connecting life sciences data at the European Bioinformatics InstituteConnecting life sciences data at the European Bioinformatics Institute
Connecting life sciences data at the European Bioinformatics InstituteConnected Data World
 

Ähnlich wie Integration of biomedical data and electronic publications (20)

Computational approaches to cell cycle analysis: Data and databases
Computational approaches to cell cycle analysis: Data and databasesComputational approaches to cell cycle analysis: Data and databases
Computational approaches to cell cycle analysis: Data and databases
 
Integration of biomedical literature and databases
Integration of biomedical literature and databasesIntegration of biomedical literature and databases
Integration of biomedical literature and databases
 
Integration of biomedical literature and databases
Integration of biomedical literature and databasesIntegration of biomedical literature and databases
Integration of biomedical literature and databases
 
Systems biology - Understanding biology at the systems level
Systems biology - Understanding biology at the systems levelSystems biology - Understanding biology at the systems level
Systems biology - Understanding biology at the systems level
 
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
 
STRING: Large-scale data and text mining
STRING: Large-scale data and text miningSTRING: Large-scale data and text mining
STRING: Large-scale data and text mining
 
Networks of proteins and diseases
Networks of proteins and diseasesNetworks of proteins and diseases
Networks of proteins and diseases
 
Exploring proteins, chemicals and their interactions with STRING and STITCH
Exploring proteins, chemicals and their interactions with STRING and STITCHExploring proteins, chemicals and their interactions with STRING and STITCH
Exploring proteins, chemicals and their interactions with STRING and STITCH
 
Network biology: Large-scale data and text mining
Network biology: Large-scale data and text miningNetwork biology: Large-scale data and text mining
Network biology: Large-scale data and text mining
 
Data analysis & integration challenges in genomics
Data analysis & integration challenges in genomicsData analysis & integration challenges in genomics
Data analysis & integration challenges in genomics
 
Introduction to Biological databases
Introduction to Biological databasesIntroduction to Biological databases
Introduction to Biological databases
 
Protein interaction networks
Protein interaction networksProtein interaction networks
Protein interaction networks
 
The STITCH and Reflect web resources
The STITCH and Reflect web resourcesThe STITCH and Reflect web resources
The STITCH and Reflect web resources
 
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
 
Protein interaction networks from yeast to human
Protein interaction networks from yeast to humanProtein interaction networks from yeast to human
Protein interaction networks from yeast to human
 
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
 
Integration of heterogeneous data
Integration of heterogeneous dataIntegration of heterogeneous data
Integration of heterogeneous data
 
protein databases.ppt
protein databases.pptprotein databases.ppt
protein databases.ppt
 
Bioinformatics - Discovering the Bio Logic Of Nature
Bioinformatics - Discovering the Bio Logic Of NatureBioinformatics - Discovering the Bio Logic Of Nature
Bioinformatics - Discovering the Bio Logic Of Nature
 
Connecting life sciences data at the European Bioinformatics Institute
Connecting life sciences data at the European Bioinformatics InstituteConnecting life sciences data at the European Bioinformatics Institute
Connecting life sciences data at the European Bioinformatics Institute
 

Mehr von 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
 
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
 
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
 
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
 
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
 
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
 
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
 
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
 

Mehr von 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
 
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
 
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...
 
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
 
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
 
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
 
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
 
Cellular Network Biology
Cellular Network BiologyCellular Network Biology
Cellular Network Biology
 
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
 

Kürzlich hochgeladen

Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024The Digital Insurer
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdfhans926745
 
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure serviceWhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure servicePooja Nehwal
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024The Digital Insurer
 
Top 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live StreamsTop 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live StreamsRoshan Dwivedi
 
Developing An App To Navigate The Roads of Brazil
Developing An App To Navigate The Roads of BrazilDeveloping An App To Navigate The Roads of Brazil
Developing An App To Navigate The Roads of BrazilV3cube
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processorsdebabhi2
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfEnterprise Knowledge
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking MenDelhi Call girls
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)Gabriella Davis
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonAnna Loughnan Colquhoun
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountPuma Security, LLC
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonetsnaman860154
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘RTylerCroy
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Scriptwesley chun
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationMichael W. Hawkins
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024The Digital Insurer
 
Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Paola De la Torre
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking MenDelhi Call girls
 

Kürzlich hochgeladen (20)

Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf
 
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure serviceWhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024
 
Top 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live StreamsTop 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live Streams
 
Developing An App To Navigate The Roads of Brazil
Developing An App To Navigate The Roads of BrazilDeveloping An App To Navigate The Roads of Brazil
Developing An App To Navigate The Roads of Brazil
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonets
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day Presentation
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024
 
Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men
 

Integration of biomedical data and electronic publications