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What is Bioinformatics?

What is Bioinformatics?. Bioinformatics : collection and storage of biological information Computational biology : development of algorithms and statistical models to analyze biological data. Jobs for bioinformaticians. Databases make biological data available to scientists.

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What is Bioinformatics?

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  1. What is Bioinformatics? • Bioinformatics: collection and storage of biological information • Computational biology: development of algorithms and statistical models to analyze biological data

  2. Jobs for bioinformaticians

  3. Databases make biological data available to scientists • As biology has increasingly turned into a data-rich science, the need for storing and communicating large datasets has grown tremendously. • Nucleotide, protein sequences • Protein structure • Expression data • Gene/protein networks

  4. Nucleotide Databases • EMBL www.ebi.ac.uk/embl/ • The EMBL (European Molecular Biology Laboratory) nucleotide sequence database is maintained by the European Bioinformatics Institute (EBI) in Hinxton, Cambridge, UK.

  5. Nucleotide Databases cont. • GenBank: maintained by the National Center for Biotechnology Information (NCBI); contains Entrez for accession to nucleotides, proteins, annotations, etc. www.ncbi.nlm.nih.gov/Genbank/ • UniGene: a non-redundant set of gene-oriented clusterswww.ncbi.nlm.nih.gov/UniGene/

  6. Protein Databases • SWISS-PROT: SWISS-PROT is a protein sequence database to provide a high level of annotations (such as the description of the function of a protein, its domains structure, post-translational modifications, variants, etc.), a minimal level of redundancy and high level of integration with other databases.www.expasy.ch/sprot/

  7. Protein Databases • PIR http://pir.georgetown.edu/ -The Protein Information Resource (PIR) is a division of the National Biomedical Research Foundation (NBRF) in the US. It is involved in a collaboration with the Munich Information Center for Protein Sequences (MIPS) and the Japanese International Protein Sequence Database (JIPID). Release 67.00 (31 Dec 2000) contains 198,801 entries.

  8. Sequence Motif Databases • Pfam www.sanger.ac.uk/Software/Pfam/ • Pfam is a database of protein families defined as domains (contiguous segments of entire protein sequences). For each domain, it contains a multiple alignment of a set of defining sequences (the seeds) and the other sequences in SWISS-PROT that can be matched to that alignment.

  9. 3D-Structure Databases • PDB www.rcsb.org/pdb/ -The PDB is the main primary database for 3D structures of biological macromolecules determined by X-ray crystallography and NMR. Structural biologists usually deposit their structures in the PDB on publication, and some scientific journals require this before accepting a paper. It also accepts the experimental data used to determine the structures.

  10. How to get sequences? • Entrez Database provides nucleotide and protein sequences in different formats. • One of the formats is FASTA

  11. FASTA FORMAT • Each sequence begins with a description line ‘>’

  12. A protein in FASTA format >HBA_ALLMI VLSMEDKSNVKAIWGKASGHLEEYGAEALEMFCAYPQTKIYFPHFDMSHNSAQIRAHGKKVFSALHEAVNHIDDLPGALCRLSELHAHSLRVDPVNFKFLAHCVLVVFAIHHPSALSPEIHASLDKFLCAVSAVLTSKYR • The first line is the description line, starts with a character '>' shows that the description line of a sequence follows the string following the '>' and ending at the first space (' ') is the sequence id (HBA_ALLMI).

  13. A DNA sequence in Fasta >X sequence ATGAATAGCACAGAGAGACCAAGAGAGAGAGAGAGACCCAGATATATCAGATAGAGA

  14. Why align sequences? • Find evolutionary relationship between species and/or genes. • Identify novel genes and define similar genes in other species. • Study genomes and how they change.

  15. Sequence Alignment • Homology means that two (or more) sequences have a common ancestor. • An example to sequence alignment Sequence 1 Sequence 2

  16. CLUSTALW: A software for aligning sequences http://www.ebi.ac.uk/clustalw/

  17. Genome Databases • www.ensembl.org

  18. Genome Databases: Gene Prediction • Define the location of genes (coding sequences, regulatory regions) • Gene prediction using software based on rules and patterns. Find Open Reading Frames (ORFs), with additional criteria for good start sequence for a gene. • Gene identification through alignment with known proteins and EST sequences (Expressed Sequence Tags; mRNA sequences). • Gene prediction through similarity with proteins or ESTs in other organisms. • Gene prediction through comparison with other genomes; conserved regions are probably coding or regulatory regions.

  19. Genome Databases: Annotation • Annotation of the genes: Compare with genes/proteins of known function in other organisms. • Functional classification. Broad groups of functional characterization, such as 'ribosomal proteins', 'nucleotide metabolism', 'signal transduction'.

  20. Genome Databases: Evolution • Evolutionary history • Genome duplications • Gene loss

  21. Transcription Databases • Microarrays can analyze 1000s of transcripts simultaneously. • Allow analysis of genes that are high or low in expression between normal and disease, for example. • Microarray Databases contain expression data (large amounts). • Stanford Microarray Database:

  22. Signaling & Metabolic Pathways • Analyze how genes/proteins interact and learn about function of genes • KEGG: Kyoto Encyclopedia of Genes and Genomes • http://www.genome.ad.jp/kegg/

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