SlideShare ist ein Scribd-Unternehmen logo
1 von 252
Downloaden Sie, um offline zu lesen
Lars Juhl Jensen Integration of heterogeneous data
Lars Juhl Jensen Integration of heterogeneous data
Lars Juhl Jensen Integration of heterogeneous data
 
 
what went wrong?
a good question
signaling networks
Oda & Kitano,  Molecular Systems Biology , 2006
long way to go
mass spectrometry
Linding, Jensen, Ostheimer et al.,  Cell , 2007
phosphorylation sites
in vivo
kinases are unknown
peptide assays
Miller, Jensen et al.,  Science Signaling , 2008
sequence specificity
kinase-specific
in vitro
no context
what a kinase could do
not what it actually does
computational methods
sequence specificity
Miller, Jensen et al.,  Science Signaling , 2008
kinase-specific
no context
what a kinase could do
not what it actually does
in vitro
in vivo
context
co-activators
scaffolders
expression
association networks
Linding, Jensen, Ostheimer et al.,  Cell , 2007
a good idea
Linding, Jensen, Ostheimer et al.,  Cell , 2007
Part I sequence motifs
curated motifs
PROSITE
ELM
HPRD
regular expressions
[ST]P.[KR]
no score
Miller, Jensen et al.,  Science Signaling , 2008
insufficient
machine learning
NetPhosK
PredPhospho
PHOSITE
GPS
KinasePhos
PPSP
GANNPhos
PhoScan
no regular updates
NetPhorest
Miller, Jensen et al.,  Science Signaling , 2008
data sources
Phospho.ELM
Diella et al.,  Nucleic Acids Res. , 2008
Diella et al.,  Nucleic Acids Res. , 2008
Scansite
Obenauer et al.,  Nucleic Acids Res. , 2003
Miller, Jensen et al.,  Science Signaling , 2008
common basis
Miller, Jensen et al.,  Science Signaling , 2008
automated pipeline
compilation of datasets
classification vs. prediction
Miller, Jensen et al.,  Science Signaling , 2008
homology reduction
Miller, Jensen et al.,  Science Signaling , 2008
training and evaluation
cross-validation
Miller, Jensen et al.,  Science Signaling , 2008
classifier selection
Miller, Jensen et al.,  Science Signaling , 2008
motif atlas
 
179 kinases
93 SH2 domains
8 PTB domains
BRCT domains
WW domains
14-3-3 proteins
phosphatases
model organisms
S. cerevisiae
D. melanogaster
C. elegans
biological insights
docking domains
Miller, Jensen et al.,  Science Signaling , 2008
disease-related kinases
Miller, Jensen et al.,  Science Signaling , 2008
predictive power
ROC curves
Miller, Jensen et al.,  Science Signaling , 2008
comparison
Miller, Jensen et al.,  Science Signaling , 2008
conclusions
data collection
automation
benchmarking
homology reduction!
Part II association networks
STRING
Jensen, Kuhn et al.,  Nucleic Acids Research , 2009
functional associations
data integration
common basis
630 genomes
model organism databases
Ensembl
RefSeq
genomic context methods
gene fusion
Korbel et al.,  Nature Biotechnology , 2004
conserved neighborhood
operons
Korbel et al.,  Nature Biotechnology , 2004
bidirectional promoters
Korbel et al.,  Nature Biotechnology , 2004
phylogenetic profiles
Korbel et al.,  Nature Biotechnology , 2004
primary experimental data
protein interactions
yeast two-hybrid
affinity purification
fragment complementation
Jensen & Bork,  Science , 2008
genetic interactions
Beyer et al.,  Nature Reviews Genetics , 2007
BIND Biomolecular Interaction Network Database
BioGRID General Repository for Interaction Datasets
DIP Database of Interacting Proteins
IntAct
MINT Molecular Interactions Database
HPRD Human Protein Reference Database
PDB Protein Data Bank
inferred associations
gene coexpression
 
GEO Gene Expression Omnibus
expression compendia
curated knowledge
complexes
MIPS Munich Information center for Protein Sequences
Gene Ontology
pathways
Letunic & Bork,  Trends in Biochemical Sciences , 2008
KEGG Kyoto Encyclopedia of Genes and Genomes
MetaCyc
Reactome
PID NCI-Nature Pathway Interaction Database
literature mining
M EDLINE
SGD Saccharomyces Genome Database
The Interactive Fly
OMIM Online Mendelian Inheritance in Man
co-mentioning
statistical methods
NLP Natural Language Processing
[object Object],[object Object],[object Object],[object Object],[object Object]
 
easy in theory …
…  but not in practice
different formats
parsers
different identifiers
thesaurus
redundant sources
book keeping
variable quality
raw quality scores
reproducibility
von Mering et al.,  Nucleic Acids Research , 2005
benchmarking
von Mering et al.,  Nucleic Acids Research , 2005
spread over 630 genomes
transfer by orthology
von Mering et al.,  Nucleic Acids Research , 2005
two modes
COG mode
von Mering et al.,  Nucleic Acids Research , 2005
protein mode
von Mering et al.,  Nucleic Acids Research , 2005
combine all evidence
visualize
Frishman et al.,  Modern Genome Annotation , 2009
STITCH
 
metabolite–enzyme links
pathway databases
Letunic & Bork,  Trends in Biochemical Sciences , 2008
drug–target links
Drugbank
PDSP K i
MATADOR
Campillos & Kuhn et al.,  Science , 2008
chemical–chemical links
shared targets
fingerprint similarity
chemical–protein network
 
conclusions
more data is better
quality scores
benchmarking
cross-species integration
Part III putting it all together
Linding, Jensen, Ostheimer et al.,  Cell , 2007
NetworKIN
 
benchmarking
Linding, Jensen, Ostheimer et al.,  Cell , 2007
2.5-fold better accuracy
context is crucial
localization
Linding, Jensen, Ostheimer et al.,  Cell , 2007
DNA damage response
Linding, Jensen, Ostheimer et al.,  Cell , 2007
Linding, Jensen, Ostheimer et al.,  Cell , 2007
small-scale validation
ATM phosphorylates Rad50
Linding, Jensen, Ostheimer et al.,  Cell , 2007
Cdk1 phosphorylates 53BP1
Linding, Jensen, Ostheimer et al.,  Cell , 2007
high-throughput validation
multiple reaction monitoring
Linding, Jensen, Ostheimer et al.,  Cell , 2007
systematic validation
kinase inhibitor matrix
Fedorov et al.,  PNAS , 2007
design optimal experiments
integration with literature
Reflect
 
 
 
conclusions
complementary data
visualization
a good question
 
Acknowledgments ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
 

Weitere ähnliche Inhalte

Was ist angesagt?

Introduction to data integration in bioinformatics
Introduction to data integration in bioinformaticsIntroduction to data integration in bioinformatics
Introduction to data integration in bioinformaticsYan Xu
 
NetBioSIG2013-Talk Thomas Kelder
NetBioSIG2013-Talk Thomas KelderNetBioSIG2013-Talk Thomas Kelder
NetBioSIG2013-Talk Thomas KelderAlexander Pico
 
NetBioSIG2014-Talk by Gerald Quon
NetBioSIG2014-Talk by Gerald QuonNetBioSIG2014-Talk by Gerald Quon
NetBioSIG2014-Talk by Gerald QuonAlexander Pico
 
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
 
Literature mining: what is it, and should I care?
Literature mining: what is it, and should I care?Literature mining: what is it, and should I care?
Literature mining: what is it, and should I care?Lars Juhl Jensen
 
NetBioSIG2013-KEYNOTE Stefan Schuster
NetBioSIG2013-KEYNOTE Stefan SchusterNetBioSIG2013-KEYNOTE Stefan Schuster
NetBioSIG2013-KEYNOTE Stefan SchusterAlexander Pico
 
Data analysis & integration challenges in genomics
Data analysis & integration challenges in genomicsData analysis & integration challenges in genomics
Data analysis & integration challenges in genomicsmikaelhuss
 
Introduction to Bioinformatics.
 Introduction to Bioinformatics. Introduction to Bioinformatics.
Introduction to Bioinformatics.Elena Sügis
 
Cross-species data integration
Cross-species data integrationCross-species data integration
Cross-species data integrationLars 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
 
'Stories that persuade with data' - talk at CENDI meeting January 9 2014
'Stories that persuade with data' - talk at CENDI meeting January 9 2014'Stories that persuade with data' - talk at CENDI meeting January 9 2014
'Stories that persuade with data' - talk at CENDI meeting January 9 2014Anita de Waard
 
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
 
Exploiting technical replicate variance in omics data analysis (RepExplore)
Exploiting technical replicate variance in omics data analysis (RepExplore)Exploiting technical replicate variance in omics data analysis (RepExplore)
Exploiting technical replicate variance in omics data analysis (RepExplore)Enrico Glaab
 
Whole genome taxonomic classi cation for prokaryotic plant pathogens
Whole genome taxonomic classication for prokaryotic plant pathogensWhole genome taxonomic classication for prokaryotic plant pathogens
Whole genome taxonomic classi cation for prokaryotic plant pathogensLeighton Pritchard
 
BM405 Lecture Slides 21/11/2014 University of Strathclyde
BM405 Lecture Slides 21/11/2014 University of StrathclydeBM405 Lecture Slides 21/11/2014 University of Strathclyde
BM405 Lecture Slides 21/11/2014 University of StrathclydeLeighton Pritchard
 
The pLoc bal-mHum is a powerful web-serve for predicting the subcellular loca...
The pLoc bal-mHum is a powerful web-serve for predicting the subcellular loca...The pLoc bal-mHum is a powerful web-serve for predicting the subcellular loca...
The pLoc bal-mHum is a powerful web-serve for predicting the subcellular loca...IJBNT Journal
 

Was ist angesagt? (20)

Introduction to data integration in bioinformatics
Introduction to data integration in bioinformaticsIntroduction to data integration in bioinformatics
Introduction to data integration in bioinformatics
 
Naveen Kumar Resume
Naveen Kumar ResumeNaveen Kumar Resume
Naveen Kumar Resume
 
NetBioSIG2013-Talk Thomas Kelder
NetBioSIG2013-Talk Thomas KelderNetBioSIG2013-Talk Thomas Kelder
NetBioSIG2013-Talk Thomas Kelder
 
NetBioSIG2014-Talk by Gerald Quon
NetBioSIG2014-Talk by Gerald QuonNetBioSIG2014-Talk by Gerald Quon
NetBioSIG2014-Talk by Gerald Quon
 
E1062632
E1062632E1062632
E1062632
 
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
 
Literature mining: what is it, and should I care?
Literature mining: what is it, and should I care?Literature mining: what is it, and should I care?
Literature mining: what is it, and should I care?
 
NetBioSIG2013-KEYNOTE Stefan Schuster
NetBioSIG2013-KEYNOTE Stefan SchusterNetBioSIG2013-KEYNOTE Stefan Schuster
NetBioSIG2013-KEYNOTE Stefan Schuster
 
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 Bioinformatics.
 Introduction to Bioinformatics. Introduction to Bioinformatics.
Introduction to Bioinformatics.
 
Cross-species data integration
Cross-species data integrationCross-species data integration
Cross-species data integration
 
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
 
'Stories that persuade with data' - talk at CENDI meeting January 9 2014
'Stories that persuade with data' - talk at CENDI meeting January 9 2014'Stories that persuade with data' - talk at CENDI meeting January 9 2014
'Stories that persuade with data' - talk at CENDI meeting January 9 2014
 
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
 
Exploiting technical replicate variance in omics data analysis (RepExplore)
Exploiting technical replicate variance in omics data analysis (RepExplore)Exploiting technical replicate variance in omics data analysis (RepExplore)
Exploiting technical replicate variance in omics data analysis (RepExplore)
 
Weber-Thesis
Weber-ThesisWeber-Thesis
Weber-Thesis
 
Whole genome taxonomic classi cation for prokaryotic plant pathogens
Whole genome taxonomic classication for prokaryotic plant pathogensWhole genome taxonomic classication for prokaryotic plant pathogens
Whole genome taxonomic classi cation for prokaryotic plant pathogens
 
BM405 Lecture Slides 21/11/2014 University of Strathclyde
BM405 Lecture Slides 21/11/2014 University of StrathclydeBM405 Lecture Slides 21/11/2014 University of Strathclyde
BM405 Lecture Slides 21/11/2014 University of Strathclyde
 
The pLoc bal-mHum is a powerful web-serve for predicting the subcellular loca...
The pLoc bal-mHum is a powerful web-serve for predicting the subcellular loca...The pLoc bal-mHum is a powerful web-serve for predicting the subcellular loca...
The pLoc bal-mHum is a powerful web-serve for predicting the subcellular loca...
 
iOmics
iOmicsiOmics
iOmics
 

Andere mochten auch

Network integration of heterogeneous data
Network integration of heterogeneous dataNetwork integration of heterogeneous data
Network integration of heterogeneous dataLars Juhl Jensen
 
Mining heterogeneous data: Understanding systems at the level of complexes an...
Mining heterogeneous data: Understanding systems at the level of complexes an...Mining heterogeneous data: Understanding systems at the level of complexes an...
Mining heterogeneous data: Understanding systems at the level of complexes an...Lars Juhl Jensen
 
Integrating and Interpreting Social Data from Heterogeneous Sources
Integrating and Interpreting Social Data from Heterogeneous SourcesIntegrating and Interpreting Social Data from Heterogeneous Sources
Integrating and Interpreting Social Data from Heterogeneous SourcesMatthew Rowe
 
Chi-Square test of Homogeneity by Pops P. Macalino (TSU-MAEd)
Chi-Square test of Homogeneity by Pops P. Macalino (TSU-MAEd)Chi-Square test of Homogeneity by Pops P. Macalino (TSU-MAEd)
Chi-Square test of Homogeneity by Pops P. Macalino (TSU-MAEd)pops macalino
 
Heterogeneous data fusion with multiple kernel growing self organizing maps
Heterogeneous data fusion with multiple kernel growing self organizing mapsHeterogeneous data fusion with multiple kernel growing self organizing maps
Heterogeneous data fusion with multiple kernel growing self organizing mapsPruthuvi Maheshakya Wijewardena
 
Statistical software packages
Statistical software packagesStatistical software packages
Statistical software packagesKm Ashif
 
Domain specific Software Architecture
Domain specific Software Architecture Domain specific Software Architecture
Domain specific Software Architecture DIPEN SAINI
 
Twitter For Business The What, Why And How To Get Started Jonnie Jensen I...
Twitter For Business   The What, Why And How To Get Started   Jonnie Jensen I...Twitter For Business   The What, Why And How To Get Started   Jonnie Jensen I...
Twitter For Business The What, Why And How To Get Started Jonnie Jensen I...jonnie jensen
 
Using side effects for drug target identification
Using side effects for drug target identificationUsing side effects for drug target identification
Using side effects for drug target identificationLars 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
 
Aplicaciones de herramientas digitales en el aula
Aplicaciones de herramientas digitales en el aulaAplicaciones de herramientas digitales en el aula
Aplicaciones de herramientas digitales en el aulaMaría Gabriela Galli
 
Live+Social - Being Remarkable - the key to social business success
Live+Social - Being Remarkable - the key to social business successLive+Social - Being Remarkable - the key to social business success
Live+Social - Being Remarkable - the key to social business successjonnie 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
 
STRING - Protein networks from data and text mining
STRING - Protein networks from data and text miningSTRING - Protein networks from data and text mining
STRING - Protein networks from data and text miningLars Juhl Jensen
 

Andere mochten auch (16)

Network integration of heterogeneous data
Network integration of heterogeneous dataNetwork integration of heterogeneous data
Network integration of heterogeneous data
 
Mining heterogeneous data: Understanding systems at the level of complexes an...
Mining heterogeneous data: Understanding systems at the level of complexes an...Mining heterogeneous data: Understanding systems at the level of complexes an...
Mining heterogeneous data: Understanding systems at the level of complexes an...
 
Integrating and Interpreting Social Data from Heterogeneous Sources
Integrating and Interpreting Social Data from Heterogeneous SourcesIntegrating and Interpreting Social Data from Heterogeneous Sources
Integrating and Interpreting Social Data from Heterogeneous Sources
 
Chi-Square test of Homogeneity by Pops P. Macalino (TSU-MAEd)
Chi-Square test of Homogeneity by Pops P. Macalino (TSU-MAEd)Chi-Square test of Homogeneity by Pops P. Macalino (TSU-MAEd)
Chi-Square test of Homogeneity by Pops P. Macalino (TSU-MAEd)
 
Heterogeneous data fusion with multiple kernel growing self organizing maps
Heterogeneous data fusion with multiple kernel growing self organizing mapsHeterogeneous data fusion with multiple kernel growing self organizing maps
Heterogeneous data fusion with multiple kernel growing self organizing maps
 
Statistical Software
Statistical SoftwareStatistical Software
Statistical Software
 
Statistical software packages
Statistical software packagesStatistical software packages
Statistical software packages
 
Domain specific Software Architecture
Domain specific Software Architecture Domain specific Software Architecture
Domain specific Software Architecture
 
Twitter For Business The What, Why And How To Get Started Jonnie Jensen I...
Twitter For Business   The What, Why And How To Get Started   Jonnie Jensen I...Twitter For Business   The What, Why And How To Get Started   Jonnie Jensen I...
Twitter For Business The What, Why And How To Get Started Jonnie Jensen I...
 
Using side effects for drug target identification
Using side effects for drug target identificationUsing side effects for drug target identification
Using side effects for drug target identification
 
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
 
Aplicaciones de herramientas digitales en el aula
Aplicaciones de herramientas digitales en el aulaAplicaciones de herramientas digitales en el aula
Aplicaciones de herramientas digitales en el aula
 
Beijing
BeijingBeijing
Beijing
 
Live+Social - Being Remarkable - the key to social business success
Live+Social - Being Remarkable - the key to social business successLive+Social - Being Remarkable - the key to social business success
Live+Social - Being Remarkable - the key to social business success
 
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 ...
 
STRING - Protein networks from data and text mining
STRING - Protein networks from data and text miningSTRING - Protein networks from data and text mining
STRING - Protein networks from data and text mining
 

Ähnlich wie Integration of heterogeneous data

Data Integration and Systems Biology
Data Integration and Systems BiologyData Integration and Systems Biology
Data Integration and Systems BiologyLars Juhl Jensen
 
Unraveling cellular phosphorylation networks using computational biology
Unraveling cellular phosphorylation networks using computational biologyUnraveling cellular phosphorylation networks using computational biology
Unraveling cellular phosphorylation networks using computational biologyLars Juhl Jensen
 
Unraveling signaling networks by large-scale data integration
Unraveling signaling networks by large-scale data integrationUnraveling signaling networks by large-scale data integration
Unraveling signaling networks by large-scale data integrationLars Juhl Jensen
 
Unraveling signal transduction networks through data integration
Unraveling signal transduction networks through data integrationUnraveling signal transduction networks through data integration
Unraveling signal transduction networks through data integrationLars Juhl Jensen
 
Computational Biology - Signaling networks and drug repositioning
Computational Biology - Signaling networks and drug repositioningComputational Biology - Signaling networks and drug repositioning
Computational Biology - Signaling networks and drug repositioningLars Juhl Jensen
 
Unraveling signaling networks by data integration
Unraveling signaling networks by data integrationUnraveling signaling networks by data integration
Unraveling signaling networks by data integrationLars Juhl Jensen
 
Data integration and functional association networks
Data integration and functional association networksData integration and functional association networks
Data integration and functional association networksLars Juhl Jensen
 
From phosphoproteomics to signaling networks
From phosphoproteomics to signaling networksFrom phosphoproteomics to signaling networks
From phosphoproteomics to signaling networksLars Juhl Jensen
 
Combining sequence motifs and protein interactions to unravel complex phospho...
Combining sequence motifs and protein interactions to unravel complex phospho...Combining sequence motifs and protein interactions to unravel complex phospho...
Combining sequence motifs and protein interactions to unravel complex phospho...Lars 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
 
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
 
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
 
Network biology - A basis for large-scale biomedica data mining
Network biology - A basis for large-scale biomedica data miningNetwork biology - A basis for large-scale biomedica data mining
Network biology - A basis for large-scale biomedica data miningLars Juhl Jensen
 
Network biology: Large-scale biomedical data and text mining
Network biology: Large-scale biomedical data and text miningNetwork biology: Large-scale biomedical data and text mining
Network biology: Large-scale biomedical data and text miningLars Juhl Jensen
 
Using networks to derive function
Using networks to derive functionUsing networks to derive function
Using networks to derive functionLars Juhl Jensen
 
Integration of heterogeneous data
Integration of heterogeneous dataIntegration of heterogeneous data
Integration of heterogeneous dataLars Juhl Jensen
 
Cellular network biology: Proteome-wide analysis of heterogeneous data
Cellular network biology: Proteome-wide analysis of heterogeneous dataCellular network biology: Proteome-wide analysis of heterogeneous data
Cellular network biology: Proteome-wide analysis of heterogeneous dataLars Juhl Jensen
 
STRING - Modeling of biological systems through cross-species data integ...
STRING - Modeling of biological systems through cross-species data integ...STRING - Modeling of biological systems through cross-species data integ...
STRING - Modeling of biological systems through cross-species data integ...Lars Juhl Jensen
 

Ähnlich wie Integration of heterogeneous data (20)

Data Integration and Systems Biology
Data Integration and Systems BiologyData Integration and Systems Biology
Data Integration and Systems Biology
 
Unraveling cellular phosphorylation networks using computational biology
Unraveling cellular phosphorylation networks using computational biologyUnraveling cellular phosphorylation networks using computational biology
Unraveling cellular phosphorylation networks using computational biology
 
Unraveling signaling networks by large-scale data integration
Unraveling signaling networks by large-scale data integrationUnraveling signaling networks by large-scale data integration
Unraveling signaling networks by large-scale data integration
 
Unraveling signal transduction networks through data integration
Unraveling signal transduction networks through data integrationUnraveling signal transduction networks through data integration
Unraveling signal transduction networks through data integration
 
Computational Biology - Signaling networks and drug repositioning
Computational Biology - Signaling networks and drug repositioningComputational Biology - Signaling networks and drug repositioning
Computational Biology - Signaling networks and drug repositioning
 
Unraveling signaling networks by data integration
Unraveling signaling networks by data integrationUnraveling signaling networks by data integration
Unraveling signaling networks by data integration
 
Data integration and functional association networks
Data integration and functional association networksData integration and functional association networks
Data integration and functional association networks
 
From phosphoproteomics to signaling networks
From phosphoproteomics to signaling networksFrom phosphoproteomics to signaling networks
From phosphoproteomics to signaling networks
 
Combining sequence motifs and protein interactions to unravel complex phospho...
Combining sequence motifs and protein interactions to unravel complex phospho...Combining sequence motifs and protein interactions to unravel complex phospho...
Combining sequence motifs and protein interactions to unravel complex phospho...
 
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
 
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
 
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
 
Network biology - A basis for large-scale biomedica data mining
Network biology - A basis for large-scale biomedica data miningNetwork biology - A basis for large-scale biomedica data mining
Network biology - A basis for large-scale biomedica data mining
 
Network biology
Network biologyNetwork biology
Network biology
 
Network biology: Large-scale biomedical data and text mining
Network biology: Large-scale biomedical data and text miningNetwork biology: Large-scale biomedical data and text mining
Network biology: Large-scale biomedical data and text mining
 
Using networks to derive function
Using networks to derive functionUsing networks to derive function
Using networks to derive function
 
Network biology
Network biologyNetwork biology
Network biology
 
Integration of heterogeneous data
Integration of heterogeneous dataIntegration of heterogeneous data
Integration of heterogeneous data
 
Cellular network biology: Proteome-wide analysis of heterogeneous data
Cellular network biology: Proteome-wide analysis of heterogeneous dataCellular network biology: Proteome-wide analysis of heterogeneous data
Cellular network biology: Proteome-wide analysis of heterogeneous data
 
STRING - Modeling of biological systems through cross-species data integ...
STRING - Modeling of biological systems through cross-species data integ...STRING - Modeling of biological systems through cross-species data integ...
STRING - Modeling of biological systems through cross-species data integ...
 

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
 
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
 
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
 

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
 
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
 
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
 

Kürzlich hochgeladen

Videogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdfVideogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdfinfogdgmi
 
20230202 - Introduction to tis-py
20230202 - Introduction to tis-py20230202 - Introduction to tis-py
20230202 - Introduction to tis-pyJamie (Taka) Wang
 
AI You Can Trust - Ensuring Success with Data Integrity Webinar
AI You Can Trust - Ensuring Success with Data Integrity WebinarAI You Can Trust - Ensuring Success with Data Integrity Webinar
AI You Can Trust - Ensuring Success with Data Integrity WebinarPrecisely
 
Linked Data in Production: Moving Beyond Ontologies
Linked Data in Production: Moving Beyond OntologiesLinked Data in Production: Moving Beyond Ontologies
Linked Data in Production: Moving Beyond OntologiesDavid Newbury
 
Basic Building Blocks of Internet of Things.
Basic Building Blocks of Internet of Things.Basic Building Blocks of Internet of Things.
Basic Building Blocks of Internet of Things.YounusS2
 
Designing A Time bound resource download URL
Designing A Time bound resource download URLDesigning A Time bound resource download URL
Designing A Time bound resource download URLRuncy Oommen
 
Using IESVE for Loads, Sizing and Heat Pump Modeling to Achieve Decarbonization
Using IESVE for Loads, Sizing and Heat Pump Modeling to Achieve DecarbonizationUsing IESVE for Loads, Sizing and Heat Pump Modeling to Achieve Decarbonization
Using IESVE for Loads, Sizing and Heat Pump Modeling to Achieve DecarbonizationIES VE
 
Igniting Next Level Productivity with AI-Infused Data Integration Workflows
Igniting Next Level Productivity with AI-Infused Data Integration WorkflowsIgniting Next Level Productivity with AI-Infused Data Integration Workflows
Igniting Next Level Productivity with AI-Infused Data Integration WorkflowsSafe Software
 
Crea il tuo assistente AI con lo Stregatto (open source python framework)
Crea il tuo assistente AI con lo Stregatto (open source python framework)Crea il tuo assistente AI con lo Stregatto (open source python framework)
Crea il tuo assistente AI con lo Stregatto (open source python framework)Commit University
 
Empowering Africa's Next Generation: The AI Leadership Blueprint
Empowering Africa's Next Generation: The AI Leadership BlueprintEmpowering Africa's Next Generation: The AI Leadership Blueprint
Empowering Africa's Next Generation: The AI Leadership BlueprintMahmoud Rabie
 
Computer 10: Lesson 10 - Online Crimes and Hazards
Computer 10: Lesson 10 - Online Crimes and HazardsComputer 10: Lesson 10 - Online Crimes and Hazards
Computer 10: Lesson 10 - Online Crimes and HazardsSeth Reyes
 
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPA
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPAAnypoint Code Builder , Google Pub sub connector and MuleSoft RPA
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPAshyamraj55
 
Building AI-Driven Apps Using Semantic Kernel.pptx
Building AI-Driven Apps Using Semantic Kernel.pptxBuilding AI-Driven Apps Using Semantic Kernel.pptx
Building AI-Driven Apps Using Semantic Kernel.pptxUdaiappa Ramachandran
 
Meet the new FSP 3000 M-Flex800™
Meet the new FSP 3000 M-Flex800™Meet the new FSP 3000 M-Flex800™
Meet the new FSP 3000 M-Flex800™Adtran
 
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019IES VE
 
Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024D Cloud Solutions
 
Cybersecurity Workshop #1.pptx
Cybersecurity Workshop #1.pptxCybersecurity Workshop #1.pptx
Cybersecurity Workshop #1.pptxGDSC PJATK
 
Comparing Sidecar-less Service Mesh from Cilium and Istio
Comparing Sidecar-less Service Mesh from Cilium and IstioComparing Sidecar-less Service Mesh from Cilium and Istio
Comparing Sidecar-less Service Mesh from Cilium and IstioChristian Posta
 
How Accurate are Carbon Emissions Projections?
How Accurate are Carbon Emissions Projections?How Accurate are Carbon Emissions Projections?
How Accurate are Carbon Emissions Projections?IES VE
 
Building Your Own AI Instance (TBLC AI )
Building Your Own AI Instance (TBLC AI )Building Your Own AI Instance (TBLC AI )
Building Your Own AI Instance (TBLC AI )Brian Pichman
 

Kürzlich hochgeladen (20)

Videogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdfVideogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdf
 
20230202 - Introduction to tis-py
20230202 - Introduction to tis-py20230202 - Introduction to tis-py
20230202 - Introduction to tis-py
 
AI You Can Trust - Ensuring Success with Data Integrity Webinar
AI You Can Trust - Ensuring Success with Data Integrity WebinarAI You Can Trust - Ensuring Success with Data Integrity Webinar
AI You Can Trust - Ensuring Success with Data Integrity Webinar
 
Linked Data in Production: Moving Beyond Ontologies
Linked Data in Production: Moving Beyond OntologiesLinked Data in Production: Moving Beyond Ontologies
Linked Data in Production: Moving Beyond Ontologies
 
Basic Building Blocks of Internet of Things.
Basic Building Blocks of Internet of Things.Basic Building Blocks of Internet of Things.
Basic Building Blocks of Internet of Things.
 
Designing A Time bound resource download URL
Designing A Time bound resource download URLDesigning A Time bound resource download URL
Designing A Time bound resource download URL
 
Using IESVE for Loads, Sizing and Heat Pump Modeling to Achieve Decarbonization
Using IESVE for Loads, Sizing and Heat Pump Modeling to Achieve DecarbonizationUsing IESVE for Loads, Sizing and Heat Pump Modeling to Achieve Decarbonization
Using IESVE for Loads, Sizing and Heat Pump Modeling to Achieve Decarbonization
 
Igniting Next Level Productivity with AI-Infused Data Integration Workflows
Igniting Next Level Productivity with AI-Infused Data Integration WorkflowsIgniting Next Level Productivity with AI-Infused Data Integration Workflows
Igniting Next Level Productivity with AI-Infused Data Integration Workflows
 
Crea il tuo assistente AI con lo Stregatto (open source python framework)
Crea il tuo assistente AI con lo Stregatto (open source python framework)Crea il tuo assistente AI con lo Stregatto (open source python framework)
Crea il tuo assistente AI con lo Stregatto (open source python framework)
 
Empowering Africa's Next Generation: The AI Leadership Blueprint
Empowering Africa's Next Generation: The AI Leadership BlueprintEmpowering Africa's Next Generation: The AI Leadership Blueprint
Empowering Africa's Next Generation: The AI Leadership Blueprint
 
Computer 10: Lesson 10 - Online Crimes and Hazards
Computer 10: Lesson 10 - Online Crimes and HazardsComputer 10: Lesson 10 - Online Crimes and Hazards
Computer 10: Lesson 10 - Online Crimes and Hazards
 
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPA
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPAAnypoint Code Builder , Google Pub sub connector and MuleSoft RPA
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPA
 
Building AI-Driven Apps Using Semantic Kernel.pptx
Building AI-Driven Apps Using Semantic Kernel.pptxBuilding AI-Driven Apps Using Semantic Kernel.pptx
Building AI-Driven Apps Using Semantic Kernel.pptx
 
Meet the new FSP 3000 M-Flex800™
Meet the new FSP 3000 M-Flex800™Meet the new FSP 3000 M-Flex800™
Meet the new FSP 3000 M-Flex800™
 
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019
IESVE Software for Florida Code Compliance Using ASHRAE 90.1-2019
 
Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024
 
Cybersecurity Workshop #1.pptx
Cybersecurity Workshop #1.pptxCybersecurity Workshop #1.pptx
Cybersecurity Workshop #1.pptx
 
Comparing Sidecar-less Service Mesh from Cilium and Istio
Comparing Sidecar-less Service Mesh from Cilium and IstioComparing Sidecar-less Service Mesh from Cilium and Istio
Comparing Sidecar-less Service Mesh from Cilium and Istio
 
How Accurate are Carbon Emissions Projections?
How Accurate are Carbon Emissions Projections?How Accurate are Carbon Emissions Projections?
How Accurate are Carbon Emissions Projections?
 
Building Your Own AI Instance (TBLC AI )
Building Your Own AI Instance (TBLC AI )Building Your Own AI Instance (TBLC AI )
Building Your Own AI Instance (TBLC AI )
 

Integration of heterogeneous data