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Biomarker bioinformatics: Network-based candidate prioritization

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Lars Juhl Jensen
Lars Juhl Jensen

Biomarker bioinformatics: Network-based candidate prioritization

Science
1 of 66
Biomarker bioinformatics Network-based candidate prioritization Lars Juhl Jensen
three parts
data integration
text mining
candidate prioritization
data integration
string-db.org
9.6 million proteins
functional associations
curated knowledge
Letunic & Bork, Trends in Biochemical Sciences, 2008
experimental data
Jensen & Bork, Science, 2008
genomic context
Korbel et al., Nature Biotechnology, 2004
many databases
different formats
different identifiers
variable quality
not comparable
hard work
parsers
mapping files
quality scores
von Mering et al., Nucleic Acids Research, 2005
score calibration
von Mering et al., Nucleic Acids Research, 2005
implicit weighting by quality
common scale
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
cyclin dependent kinase 1
CDC2
hCdc2
flexible matching
cyclin dependent kinase 1
cyclin-dependent kinase 1
“black list”
SDS
co-mentioning
quality scores
candidate prioritization
biomarker evidence
quality scores
score calibration
network scaffold
heat diffusion
support from neighbors
candidate list
module identification
groups of candidates
molecular context
Thank you Damian Szklarczyk John "Scooter" Morris Helen Cook Michael Kuhn Stefan Wyder Milan Simonovic Alberto Santos Nadezhda Doncheva Alexander Roth Peer Bork Christian von Mering Thomas Skøt Jensen
Take care

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