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Applied text mining
Lars Juhl Jensen
>10 km
too much to read
exponential growth
~40 seconds per paper
computer
as smart as a dog
teach it specific tricks
information retrieval
named entity recognition
information extraction
text/data integration
medical text mining
information retrieval
find the relevant papers
ad hoc retrieval
user-specified query
“yeast AND cell cycle”
PubMed
indexing
fast lookup
stemming
word endings
dynamic query expansion
MeSH terms
Mitotic cyclin (Clb2)-bound Cdc28 (Cdk1
homolog) directly phosphorylated Swe1
and this modification served as a priming
step to promote subsequent Cdc5-
dependent Swe1 hyperphosphorylation
and degradation
no tool will find that
named entity recognition
identify the concepts
Mitotic cyclin (Clb2)-bound Cdc28 (Cdk1
homolog) directly phosphorylated Swe1
and this modification served as a priming
step to promote subsequent Cdc5-
dependent Swe1 hyperphosphorylation
and degradation
comprehensive lexicon
CDC2
cyclin dependent kinase 1
orthographic variation
flexible matching
upper- and lower-case
CDC2
Cdc2
spaces and hyphens
cyclin dependent kinase 1
cyclin-dependent kinase 1
name expansions
prefixes and suffixes
CDC2
hCDC2
“black list”
SDS
efficient tagger
Pafilis et al., PLOS ONE, 2013
benchmarking
the formal way
manually annotated corpus
precision
recall
much work
the pragmatic way
random sampling
precision
no recall
much less work
augmented browsing
Mitotic cyclin (Clb2)-bound Cdc28 (Cdk1
homolog) directly phosphorylated Swe1
and this modification served as a priming
step to promote subsequent Cdc5-
dependent Swe1 hyperphosphorylation
and degradation
Mitotic cyclin (Clb2)-bound Cdc28 (Cdk1
homolog) directly phosphorylated Swe1
and this modification served as a priming
step to promote subsequent Cdc5-
dependent Swe1 hyperphosphorylation
and degradation
Reflect
Pafilis, O’Donoghue, Jensen et al., Nature Biotechnology, 2009reflect.ws
information extraction
formalize the facts
Mitotic cyclin (Clb2)-bound Cdc28 (Cdk1
homolog) directly phosphorylated Swe1
and this modification served as a priming
step to promote subsequent Cdc5-
dependent Swe1 hyperphosphorylation
and degradation
two approaches
the formal way
NLP
Natural Language Processing
part-of-speech tagging
what you learned in school
pronoun pronoun verb preposition noun
multiword detection
semantic tagging
sentence parsing
Gene and protein names
Cue words for entity
recognition
Verbs for relation extraction
[nxexpr The expression of
[nxgene the cytochrome
genes
[nxpg CYC1 and CYC7]]]
is controlled by
[nxpg HAP1]
Saric et al., Proceedings of ACL, 2004
extract stated facts
high precision
poor recall
the pragmatic way
guilt by association
co-mentioning
counting
within documents
within paragraphs
within sentences
quality score
high recall
high precision
undirected associations
unknown type
text/data integration
STRING
protein associations
Szklarczyk et al., Nucleic Acids Research, 2015string-db.org
STITCH
STRING + 300k chemicals
Kuhn et al., Nucleic Acids Research, 2014stitch-db.org
COMPARTMENTS
subcellular localization
Binder et al., Database, 2014compartments.jensenlab.org
TISSUES
tissue expression
tissues.jensenlab.org Santos et al., submitted, 2015
DISEASES
disease–gene assocations
diseases.jensenlab.org Frankild et al., Methods, 2015
curated knowledge
pathways
Letunic & Bork, Trends in Biochemical Sciences, 2008
experimental data
gene expression
computational predictions
gene neighborhood
Korbel et al., Nature Biotechnology, 2004
many databases
different formats
different identifiers
variable quality
not comparable
hard work
common identifiers
quality scores
score calibration
visualization
web interfaces
bulk download
why so many resources?
Swiss army knife syndrome
EMBO Practical Course Computational Biology:
Genomesto Systems
Puerto Varas, 3-9April2014
Thanks for your attention!
141

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Applied text mining