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BIOINFORMATICS
Bioinformatics• Combination of:– Theory and methods (algorithms, statistical
methods, machine learning, …)– Applications (sequence analysis, genome
assemblies, databases, ... )– Different kinds of datasets (sequence data,
microarray, next-gen data, …)
Biology Core Concepts• Molecular biology• Systems biology• Evolutionary theory• Common lab techniques• Sequence comparison• Phylogenetic analysis
Computer science• Programming• Database querying• Data mining• Visualization• Machine learning• Modeling• …
How to survive?• Knowledge of Linux/Unix• Scripting: Perl/Python• Network based data storage• Knowledge biology, genomics• Database structures• Try to keep up with all new tools!
Benifit of using (Bio)perl, exampleYou have a 1000 sequences to blast and analyse…You can do this manually Or… use a perlscript to do this for you and present you the final results!
Good journals to keep up the paceBioinformatics (
http://bioinformatics.oxfordjournals.org/ ) BMC Bioinformatics ( http://
www.biomedcentral.com/bmcbioinformatics/ ) PLoS Computational Biology (
http://www.ploscompbiol.org/ ) ...
DATABASES
Types of databases• DNA databases• Protein databases• Genome databases• Microarray databases• Next-Gen seq databases
What to find in databases?• Sequences• Motifs• Mutations, SNPs• Gene ineraction profiles• Interactions (protein protein interactions)• Transcription factor binding sites• Etc…
Databases? Good Reference• http://nar.oxfordjournals.org annual edition
NCBI: lot of options… feed the need
Amino acid databases• Uniprot– SWISS-PROT– TrEMBL– PIR
Uniprot• http://www.uniprot.org • Good quality, curated• Minimal redundancy• Extensive cross linking
to useful databases
Structural databases• Structure leads to function!
– Protein Data Base – PDB http://www.pdb.org – SCOP & CATH databases (structural classification)
http://scop.mrc-lmb.cam.ac.uk/scop/ ; http://www.cathdb.info/
Structure prediction (modeling) SWISS-MODEL & Repository ( http:// swissmodel.expasy.org/ )
MODELLER & MODBASE ( http://salilab.org )
Study of interactions (docking) & drug design
SNPs and pharma
• To collect, encode, and disseminate knowledge about the impact of human genetic variations on drug response.
http://www.pharmgkb.org/
DNA Microarray Databases• Standard: MIAME = minimum information about
microarray experiment
• Databases:– ArrayExpress (EBI)http://www.ebi.ac.uk/arrayexpress/
– GEO (NCBI)http://www.ncbi.nlm.nih.gov/geo/
Check the database before planning an experiment!
Next gen data database• http://www.ncbi.nlm.nih.gov/Traces/sra• http://www.ebi.ac.uk/ena• http
://www.ddbj.nig.ac.jp/sub/trace_sra-e.html
GENOME BROWSERS
Human reference sequences
• Celera• Huref• GRCh37
Three reference genomes. Keep this
in mind when browsing databases!
Useful Genome Browsers• Ensembl: http://www.ensembl.org/• NCBI Map Viewer:
http://www.ncbi.nlm.nih.gov/mapview/map_search.cgi?
• UCSC: http://genome.ucsc.edu/
Genome browser: Ensembl
EMBL Problems• Lots of redundancy• Wrong or old annotations• Vector contamination• Errors in sequences
Refseq• Better option, NCBI reference• Curated• Annotations are controlled• No redundancy
NCBI:Genbank vs RefSeqhttp://www.ncbi.nlm.nih.gov/RefSeq/
• Sequence records are created by scientists who submit sequence data to GenBank. As an archival database, GenBank may contain hundreds of records for the same gene. In addition, because there is no independent review system, the types of information may vary from record to record, and GenBank sequence data may contain errors and contaminant vector DNA.
• To address some of the problems associated with GenBank sequence records, NCBI developed its RefSeq database.
Refseq accession numbers• NM_ mRNA (provisional, predicted, reviewed)• NP_ protein (provisional, predicted, reviewed)• NR_ non-coding RNA (provisional, reviewed)• NG_ human genes (provisional, reviewed)• NC_ chromosomes, complete genomes
(provisional, reviewed)
Refseq accession numbers (2)• XM_ predicted mRNA (model)• XP_ predicted protein (model)• XR_ predicted non-coding RNA (model)• NT_ human and mouse genomic contiqs
(model)• NW_ mouse supercontiqs (model)
Genome browser: NCBI
Genome browser: UCSC• Example: UCSC• Good tutorial:– http://
www.openhelix.com/downloads/ucsc/ucsc_home.shtml
SNPS AND DISEASE RESEARCH
SNPs and disease research• Association analysis, disease related (?),
mapping genome variation…• Reference = dbSNP database
Example NCBI SNP database, SNP rs33957964
Other useful SNPs databases• Genome variation center
http://gvs.gs.washington.edu/GVS/• HapMap (Ensembl) http://hapmap.org/• List of all: http://
www.hgvs.org/dblist/ccent.html
Clinical Bioinformatics
• Microarrays, omics data (genomics, proteomics, interactomics, metabolomics, …)
• Combination of bioinformatics and medical informatics
ALGORITHMS AND TOOLS
Algorithms• Fundaments for bioinformatic tools
– Implemented in ‘front end tools’ (website, Java applications)• Can be slow• Good for smaller analysis, quick mining
– Scripts, programs - use in command line (e.g.local BLAST)• Usually local install on server• faster• large queries, long analysis time required• Knowledge of linux/unix essential
Hall of Fame• Linux operating system, mySQL database• (Bio)Perl: programming language making your life easier!• Blast/Blat: comparing sequences• Phylip: Phylogenetic analysis, tree building• ClustalW: Multiple alignment• MEGA5: Multiple alignment and editing sequences• HMMER: comparative genomics• EMBOSS: combining several tools for sequence analysis
Open sourcce Free to use and develop
Tools? Good Reference• http://nar.oxfordjournals.org/ - annual edition
Analysing next gen sequencing data• Different tools for different formats– Roche– Applied Biosystems– Illumina
Next gen tools• FastQC: quality assesment of FASTQ files
Assembly tools next gen• A number of specialized tools exist:ABySS, gap4, Geneious, Mira, Newbler,SSAKE, SOAPdenovo, Velvet, …
Galaxy! http://galaxy.psu.edu/
• Galaxy provides a web-based application for the analysis of sequence data
• Includes many tools including NGS data• Makes your life easier, less linux knowledge
On the cloud
Structure Galaxy
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So this is why you need a bioinformatician in the lab!!