network integration of data and text

Network integration of data and text

Lars Juhl Jensen

Part 1text mining

>10 km

exponential growth

law of diminishing returns

some things are constant

~45 seconds per paper

computer

as smart as a dog

teach it specific tricks

named entity recognition

Reflect

augmented browsing

browser add-on

Pafilis, O’Donoghue, Jensen et al., Nature Biotechnology, 2009

collaborations

web services

Utopia Documents

information extraction

co-mentioning

<10 hours

no access

Part 2protein networks

STRING

Szklarczyk, Franceschini et al., Nucleic Acids Research, 2011

630 genomes

many databases

genomic context

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

experimental data

physical interactions

Jensen & Bork, Science, 2008

gene coexpression

curated knowledge

pathways

Letunic & Bork, Trends in Biochemical Sciences, 2008

text mining

many data types

many databases

different formats

different identifiers

variable quality

quality scores

calibrate vs. gold standard

von Mering et al., Nucleic Acids Research, 2005

orthology transfer

Frishman et al., Modern Genome Annotation, 2009

Part 3small molecule networks

STITCH

Kuhn et al., Nucleic Acids Research, 2010

in vitro binding assays

text mining

chemical similarity

Campillos & Kuhn et al., Science, 2008

similar drugs share targets

Campillos & Kuhn et al., Science, 2008

only trivial predictions

phenotypic similarity

chemical perturbations

phenotypic readouts

drug treatment

side effects

no database

package inserts

Campillos & Kuhn et al., Science, 2008

text mining

manual validation

side-effect correlations

Campillos & Kuhn et al., Science, 2008

side-effect frequencies

Campillos & Kuhn et al., Science, 2008

raw similarity score

Campillos & Kuhn et al., Science, 2008

p-values

Campillos & Kuhn et al., Science, 2008

side-effect similarity

chemical similarity

Campillos & Kuhn et al., Science, 2008

drug–drug network

Campillos & Kuhn et al., Science, 2008

categorization

Campillos & Kuhn et al., Science, 2008

20 drug–drug pairs

in vitro binding assays

Ki<10 µM for 11 of 20

cell assays

9 of 9 showed activity

Acknowledgments

ReflectSune Frankild

Heiko Horn

Evangelos Pafilis

Michael Kuhn

Reinhardt Schneider

Sean O’Donoghue

Side effectsMonica Campillos

Michael Kuhn

Anne-Claude Gavin

Peer Bork

STRING/STITCHDamian Szklarczyk

Andrea Franceschini

Michael Kuhn

Milan Simonovic

Alexander Roth

Pablo Minguez

Tobias Doerks

Manuel Stark

Jean Muller

Andreas Beyer

Peer Bork

Christian von Mering

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