Systems biology - Bioinformatics on complete biological systems
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Lars Juhl Jensen
Systems biologyBioinformatics on complete biological
systems
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can a biologist fix a radio?
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Lazebnik, Biochemistry, 2004
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one gene
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one postdoc
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knockout phenotype
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name the gene
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Lazebnik, Biochemistry, 2004
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all aspects
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one gene
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high-throughput biology
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one technology
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one lab
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all genes
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one aspect
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systems biology
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complete systems
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all aspects
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all genes
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systems-level properties
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two subfields
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mathematical modeling
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small systems
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data integration
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large systems
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mathematical modeling
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small systems
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Chen, Mol. Biol. Cell, 2004
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many equations
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Chen, Mol. Biol. Cell, 2004
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simulation
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Chen, Mol. Biol. Cell, 2004
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many parameters
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Chen, Mol. Biol. Cell, 2004
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requires detailed knowledge
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network biology
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association networks
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guilt by association
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protein networks
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STRING
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>1100 organisms
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~2.6 million proteins
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Szklarczyk, Franceschini et al., Nucleic Acids Research, 2011
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Exercise 1Go to http://string-db.org
Query for CDC28 in budding yeast
Try different evidence views
Show only high-confidence links
Show only experimental evidence
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genomic context
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gene fusion
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Korbel et al., Nature Biotechnology, 2004
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operons
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Korbel et al., Nature Biotechnology, 2004
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bidirectional promoters
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Korbel et al., Nature Biotechnology, 2004
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phylogenetic profiles
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Korbel et al., Nature Biotechnology, 2004
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a real example
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Cell
Cellulosomes
Cellulose
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experimental data
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gene coexpression
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protein interactions
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Jensen & Bork, Science, 2008
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genetic interactions
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Beyer et al., Nature Reviews Genetics, 2007
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curated knowledge
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complexes
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pathways
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Letunic & Bork, Trends in Biochemical Sciences, 2008
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chemical networks
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STITCH
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STRING + 300k chemicals
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drugs
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metabolites
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known drug targets
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high-throughput assays
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metabolic pathways
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Exercise 2Go to http://stitch-db.org
Query for TYMS in human
What is the role of thymidylate?
What is the role of dUMP
What is the role of Permetrexed
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many databases
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different formats
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different identifiers
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variable quality
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not comparable
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hard work
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quality scores
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von Mering et al., Nucleic Acids Research, 2005
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calibrate vs. gold standard
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missing most of the data
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text mining
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>10 km
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too much to read
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computer
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as smart as a dog
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teach it specific tricks
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named entity recognition
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comprehensive lexicon
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cyclin dependent kinase 1
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CDK1
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CDC2
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flexible matching
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spaces and hyphens
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cyclin dependent kinase 1
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cyclin-dependent kinase 1
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orthographic variation
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CDC2
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hCdc2
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“black list”
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SDS
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information extraction
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count co-mentioning
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within documents
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within paragraphs
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within sentences
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scoring scheme
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proteins
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small molecules
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compartments
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tissues
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phenotypes
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diseases
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adverse drug reactions
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organisms
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environments
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Exercise 3Go to http://diseases.jensenlab.org
Find TYMS disease associations
Inspect the text-mining evidence
Find genes linked to colorectal cancer
Explore the gene network
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text corpus
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~22 million abstracts
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no access
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~4 million full-text articles
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augmented browsing
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Reflect
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browser add-on
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real-time text mining
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Pafilis, O’Donoghue, Jensen et al., Nature Biotechnology, 2009O’Donoghue et al., Journal of Web Semantics, 2010
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localization and disease
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suite of web resources
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common backend database
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curated knowledge
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experimental data
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text mining
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computational predictions
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unified identifiers
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quality scores
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visualization
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COMPARTMENTS
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compartments.jensenlab.org
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TISSUES
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tissues.jensenlab.org
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more to come
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summary
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bioinformatics
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more than alignment
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data/text mining
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save you much time
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questions?