network biology: large-scale biomedical data and text mining

Network biologyLarge-scale biomedical data and text mining

Lars Juhl Jensen

three parts

association networks

signaling networks

drug networks

Part 1association networks

guilt by association

STRING

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

>1100 genomes

genomic context

gene fusion

Korbel et al., Nature Biotechnology, 2004

experimental data

protein interactions

Jensen & Bork, Science, 2008

curated knowledge

pathways

Letunic & Bork, Trends in Biochemical Sciences, 2008

many data types

many databases

different formats

different identifiers

variable quality

quality scores

von Mering et al., Nucleic Acids Research, 2005

calibrate vs. gold standard

von Mering et al., Nucleic Acids Research, 2005

orthology transfer

missing most of the data

>10 km

too much to read

computer

as smart as a dog

teach it specific tricks

named entity recognition

identify the concepts

proteins

comprehensive lexicon

orthographic variation

“black list”

Reflect

augmented browsing

Pafilis, O’Donoghue, Jensen et al., Nature Biotechnology, 2009O’Donoghue et al., Journal of Web Semantics, 2010

information extraction

co-mentioning

Part 2signaling networks

phosphoproteomics

in vivo phosphosites

kinases are unknown

sequence specificity

Miller, Jensen et al., Science Signaling, 2008

NetPhorest

automated pipeline

Miller, Jensen et al., Science Signaling, 2008

protein-specific

no context

co-activators

protein scaffolds

localization

expression

association network

Linding, Jensen, Ostheimer et al., Cell, 2007

NetworKIN

Linding, Jensen, Ostheimer et al., Cell, 2007

Part 3drug networks

drug repurposing

drug–drug network

chemical similarity

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

SIDER

side-effect similarity

Campillos & Kuhn et al., Science, 2008

combined similarity

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

STRINGDamian Szklarczyk

Andrea Franceschini

Michael Kuhn

Milan Simonovic

Alexander Roth

Pablo Minguez

Tobias Doerks

Manuel Stark

Jean Muller

Peer Bork

Christian von Mering

NetworKINHeiko Horn

Martin Lee Miller

Gerard Ostheimer

Francesca Diella

Claus Jørgensen

Rob Russell

Peer Bork

Benjamin Turk

Michael Yaffe

Tony Pawson

Rune Linding

larsjuhljensen