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Network biologyLarge-scale data and text mining
Lars Juhl Jensen
protein networks
medical networks
guilt by association
protein networks
STRING
functional associations
computational predictions
gene fusion
Korbel et al., Nature Biotechnology, 2004
gene neighborhood
Korbel et al., Nature Biotechnology, 2004
phylogenetic profiles
Korbel et al., Nature Biotechnology, 2004
experimental data
gene coexpression
protein interactions
Jensen & Bork, Science, 2008
curated knowledge
complexes
pathways
Letunic & Bork, Trends in Biochemical Sciences, 2008
many databases
different formats
different identifiers
variable quality
not comparable
not same species
hard work
quality scores
von Mering et al., Nucleic Acids Research, 2005
calibrate vs. gold standard
von Mering et al., Nucleic Acids Research, 2005
homology-based transfer
Franceschini et al., Nucleic Acids Research, 2013
vizualization
string-db.org
missing most of the data
text mining
>10 km
too much to read
computer
as smart as a dog
teach it specific tricks
named entity recognition
comprehensive lexicon
CDC2
cyclin dependent kinase 1
expansion rules
hCdc2
CDC2
flexible matching
cyclin-dependent kinase 1
cyclin dependent kinase 1
“black list”
SDS
augmented browsing
Reflect
browser add-on
real-time text mining
Pafilis, O’Donoghue, Jensen et al., Nature Biotechnology, 2009O’Donoghue et al., Journal of Web Semantics, 2010
information extraction
co-mentioning
within documents
within paragraphs
within sentences
natural language processing
Gene and protein namesCue words for entity recognitionVerbs for relation extraction
[nxexpr The expression of [nxgene the cytochrome genes [nxpg CYC1 and CYC7]]]is controlled by[nxpg HAP1]
text corpus
~22 million abstracts
millions of full-text articles
medical networks
Jensen et al., Nature Reviews Genetics, 2012
opt-out
opt-in
structured data
Jensen et al., Nature Reviews Genetics, 2012
unstructured data
Danish
busy doctors
psychiatric patients
custom dictionaries
drugs
adverse drug events
complex filters
Eriksson et al., submitted, 2013
new adverse drug reactions
Eriksson et al., submitted, 2013
Drug substance ADE p-value
Chlordiazepoxide Nystagmus 4.0e-8
Simvastatin Personality changes
8.4e-8
Dipyridamole Visual impairment
4.4e-4
Citalopram Psychosis 8.8e-4
Bendroflumethiazide
Apoplexy 8.5e-3
temporal correlation
diagnosis trajectories
Jensen et al., in preparation, 2013
national discharge registry
6.2 million patients
14 years
confounding factors
age and gender
Jensen et al., submitted, 2013
Female MaleIn
-pati
ent
Out-
pati
ent
Em
erg
ency
room
lifestyle
reporting biases
complex trajectories
Jensen et al., submitted, 2013
medical implications
AcknowledgmentsSTRINGChristian von MeringDamian SzklarczykMichael KuhnManuel StarkSamuel ChaffronChris CreeveyJean MullerTobias DoerksPhilippe JulienAlexander RothMilan SimonovicJan KorbelBerend SnelMartijn HuynenPeer Bork
Text miningSune FrankildJasmin SaricEvangelos PafilisKalliopi TsafouAlberto SantosJanos BinderHeiko HornMichael KuhnNigel BrownReinhardt SchneiderSean O’ Donoghue
EHR miningAnders Boeck JensenPeter Bjødstrup JensenRobert ErikssonFrancisco S. RoqueHenriette SchmockMarlene DalgaardMassimo AndreattaThomas HansenKaren SøebySøren BredkjærAnders JuulTudor OpreaPope MoseleyThomas WergeSøren Brunak
