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CPR Seminar, University of Copenhagen, Copenhagen, Denmark, February 6, 2009
Unraveling signaling networks by data integration
Unraveling signaling networks by data integration
Lars Juhl Jensen
Network biology: A basis for large-scale biomedical data mining
Network biology: A basis for large-scale biomedical data mining
Lars Juhl Jensen
Hagedorn Research Institute, Gentofte, Denmark, October 8, 2009.
Large-scale data and text mining
Large-scale data and text mining
Lars Juhl Jensen
Network biology: Large-scale biomedical data and text mining
Network biology: Large-scale biomedical data and text mining
Lars Juhl Jensen
Data integration: The STITCH database of protein-small molecule interactions
Data integration: The STITCH database of protein-small molecule interactions
Lars Juhl Jensen
Minisymposium on Glycoanalysis and Glycochemistry, University of Copenhagen, Copenhagen, Denmark, October 26, 2009.
Unraveling signal transduction networks through data integration
Unraveling signal transduction networks through data integration
Lars Juhl Jensen
BioRange, Lunteren, Netherlands, March 17-18, 2009
Unraveling signaling networks by large-scale data integration
Unraveling signaling networks by large-scale data integration
Lars Juhl Jensen
Cellular Network Biology
Cellular Network Biology
Cellular Network Biology
Lars Juhl Jensen
Recommandé
CPR Seminar, University of Copenhagen, Copenhagen, Denmark, February 6, 2009
Unraveling signaling networks by data integration
Unraveling signaling networks by data integration
Lars Juhl Jensen
Network biology: A basis for large-scale biomedical data mining
Network biology: A basis for large-scale biomedical data mining
Lars Juhl Jensen
Hagedorn Research Institute, Gentofte, Denmark, October 8, 2009.
Large-scale data and text mining
Large-scale data and text mining
Lars Juhl Jensen
Network biology: Large-scale biomedical data and text mining
Network biology: Large-scale biomedical data and text mining
Lars Juhl Jensen
Data integration: The STITCH database of protein-small molecule interactions
Data integration: The STITCH database of protein-small molecule interactions
Lars Juhl Jensen
Minisymposium on Glycoanalysis and Glycochemistry, University of Copenhagen, Copenhagen, Denmark, October 26, 2009.
Unraveling signal transduction networks through data integration
Unraveling signal transduction networks through data integration
Lars Juhl Jensen
BioRange, Lunteren, Netherlands, March 17-18, 2009
Unraveling signaling networks by large-scale data integration
Unraveling signaling networks by large-scale data integration
Lars Juhl Jensen
Cellular Network Biology
Cellular Network Biology
Cellular Network Biology
Lars Juhl Jensen
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 reactions
Lars Juhl Jensen
Advanced bioinformatics methods for proteomics
Advanced bioinformatics methods for proteomics
Lars Juhl Jensen
Exploring Modular Protein Architecture, European Molecular Biology Laboratory, Heidelberg, Germany, December 3-5, 2008
Data integration and functional association networks
Data integration and functional association networks
Lars Juhl Jensen
Chemoinformatics Course, Technical University of Denmark, Lyngby, Denmark, November 19, 2009.
Data integration: The STITCH database of protein–small molecule interactions
Data integration: The STITCH database of protein–small molecule interactions
Lars Juhl Jensen
Two news about DNA structure.
Plegable Biología
Plegable Biología
Juanita Escobar
KU Bioinformatics Workshop, University of Copenhagen, Copenhagen, Denmark, January 26, 2009
Prediction of protein-small molecule networks through large-scale data integr...
Prediction of protein-small molecule networks through large-scale data integr...
Lars Juhl Jensen
Oxytocin Modulates Female Sociosexual Behavior through a Specific Class of Prefrontal Cortical Interneurons
Oxytocin Modulates Female Sociosexual Behavior through a Specific Class of Pr...
Oxytocin Modulates Female Sociosexual Behavior through a Specific Class of Pr...
Vic Shao-Chih Chiang
Behavior- and Modality-General Representation of Confidence in Orbitofrontal Cortex
Behavior- and Modality-General Representation of Confidence in Orbitofrontal ...
Behavior- and Modality-General Representation of Confidence in Orbitofrontal ...
Vic Shao-Chih Chiang
Evolutionary plasticity of cell-cycle regulation
Evolutionary plasticity of cell-cycle regulation
Lars Juhl Jensen
Systems Biology Workshop, Technical University of Denmark, Lyngy, Denmark, May 14-15, 2009
Using networks to derive function
Using networks to derive function
Lars Juhl Jensen
Neuron class–specific responses govern adaptive myelin remodeling in the neocortex
Neuron class–specific responses govern adaptive myelin remodeling in the neoc...
Neuron class–specific responses govern adaptive myelin remodeling in the neoc...
Vic Shao-Chih Chiang
IPAM Proteomics Reunion Conference, UCLA, Lake Arrowhead, California, December 11-16, 2005
Integration of diverse large-scale datasets
Integration of diverse large-scale datasets
Lars Juhl Jensen
Centre for Computational and Systems Biology (CoSBi), Trento, Italy, January 12, 2010.
Just-in-time assembly: Transcriptional and post-translational cell-cycle regu...
Just-in-time assembly: Transcriptional and post-translational cell-cycle regu...
Lars Juhl Jensen
DNA
DNA, the great mistery
DNA, the great mistery
Juan Diego Senior
The emergence of transcriptional identity in somatosensory neurons
The emergence of transcriptional identity in somatosensory neurons
The emergence of transcriptional identity in somatosensory neurons
Vic Shao-Chih Chiang
Presentation by Michaela TerAvest, assistant professor of Biochemistry and Molecular Biology at Michigan State University, at the MSU Bioeconomy Institute in Holland, Mich., on Mar. 16, 2016.
Harnessing Microbe-Electrode Interactions for Bioenergy
Harnessing Microbe-Electrode Interactions for Bioenergy
Michigan State University Research
A Hippocampus-Accumbens Tripartite Neuronal Motif Guides Appetitive Memory in Space
A Hippocampus-Accumbens Tripartite Neuronal Motif Guides Appetitive Memory in...
A Hippocampus-Accumbens Tripartite Neuronal Motif Guides Appetitive Memory in...
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Epidemiological Evidence for a Health Risk from Mobile Phone Base Stations
Khurana et al_ijoeh-base_station_rv
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URG poster-Thu 2015_TN1.0_LCMC_v2
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Masterworks talk on Big Data and the implications of petascale science
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Deepak Singh
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 text
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2014 talk at NYU CUSP: "Biology Caught the Bus: Now what? Sequencing, Big Dat...
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Medical Research Methodology in Translational Medicine, University of Copenhagen, Copenhagen, August 24, 2010.
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One tagger, many uses: Illustrating the power of dictionary-based named entity recognition
One tagger, many uses: Illustrating the power of dictionary-based named entit...
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One tagger, many uses: Illustrating the power of dictionary-based named entit...
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Extract 2.0: Text-mining-assisted interactive annotation
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Cellular Network Biology: Large-scale integration of data and text
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The Art of Counting: Scoring and ranking co-occurrences in literature
The Art of Counting: Scoring and ranking co-occurrences in literature
Network biology - A basis for large-scale biomedica data mining
1.
Network biology A
basis for large-scale biomedical data mining Lars Juhl Jensen
2.
3.
4.
sequence analysis
5.
Jensen, Gupta et
al., Journal of Molecular Biology , 2002
6.
7.
8.
data mining
9.
de Lichtenberg, Jensen
et al., Science , 2005
10.
11.
12.
13.
data mining
14.
text mining
15.
Pafilis, O’Donoghue, Jensen
et al., Nature Biotechnology , 2009
16.
signaling networks
17.
phosphoproteomics
18.
Linding, Jensen, Ostheimer
et al., Cell , 2007
19.
in vivo
phosphosites
20.
kinases are unknown
21.
sequence motifs
22.
Miller, Jensen et
al., Science Signaling , 2008
23.
NetPhorest
24.
data organization
25.
Miller, Jensen et
al., Science Signaling , 2008
26.
automated pipeline
27.
Miller, Jensen et
al., Science Signaling , 2008
28.
motif atlas
29.
sequence specificity
30.
no context
31.
network context
32.
Linding, Jensen, Ostheimer
et al., Cell , 2007
33.
guilt by association
34.
35.
STRING
36.
630 genomes
37.
computational predictions
38.
gene fusion
39.
Korbel et al.,
Nature Biotechnology , 2004
40.
experimental data
41.
physical interactions
42.
Jensen & Bork,
Science , 2008
43.
gene coexpression
44.
45.
curated knowledge
46.
Letunic & Bork,
Trends in Biochemical Sciences , 2008
47.
>10 km
48.
literature mining
49.
Pafilis, O’Donoghue, Jensen
et al., Nature Biotechnology , 2009
50.
not comparable
51.
confidence scores
52.
von Mering et
al., Nucleic Acids Research , 2005
53.
cross-species integration
54.
von Mering et
al., Nucleic Acids Research , 2005
55.
association network
56.
Linding, Jensen, Ostheimer
et al., Cell , 2007
57.
integrate with motifs
58.
NetworKIN
59.
Linding, Jensen, Ostheimer
et al., Cell , 2007
60.
>2x better accuracy
61.
drug repositioning
62.
new uses for
old drugs
63.
drug–drug network
64.
shared target(s)
65.
chemical similarity
66.
Campillos & Kuhn
et al., Science , 2008
67.
similar drugs share
targets
68.
Campillos & Kuhn
et al., Science , 2008
69.
only trivial predictions
70.
phenotypic similarity
71.
chemical perturbations
72.
phenotypic readouts
73.
drug treatment
74.
side effects
75.
no database
76.
package inserts
77.
Campillos & Kuhn
et al., Science , 2008
78.
text mining
79.
side-effect ontology
80.
Campillos & Kuhn
et al., Science , 2008
81.
manual validation
82.
SIDER Kuhn et
al., Molecular Systems Biology , 2010
83.
side-effect correlations
84.
Campillos & Kuhn
et al., Science , 2008
85.
GSC weighting
86.
side-effect frequencies
87.
Campillos & Kuhn
et al., Science , 2008
88.
raw similarity score
89.
Campillos & Kuhn
et al., Science , 2008
90.
p-values
91.
Campillos & Kuhn
et al., Science , 2008
92.
side-effect similarity
93.
chemical similarity
94.
Campillos & Kuhn
et al., Science , 2008
95.
confidence scores
96.
drug–drug network
97.
Campillos & Kuhn
et al., Science , 2008
98.
categorization
99.
Campillos & Kuhn
et al., Science , 2008
100.
experimental validation
101.
20 drug–drug pairs
102.
in vitro
binding assays
103.
K i <10
µM for 11 of 20
104.
cell assays
105.
9 of 9
showed activity
106.
work in progress
107.
link side-effects to
targets
108.
direct target prediction
109.
110.
larsjuhljensen
Notes de l'éditeur
Integration Automation Collaboration
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