Download to read offline
BIOINFORMATICS.ppt
- 1. Bioinformatics • What isbioinformatics? • Why bioinformatics? • The major molecular biology facts • Brief history of bioinformatics • Typical problems of bioinformatics: collection and retrieval of data alignment and similarity search prediction and classification • Expectations and the level of requirements Lecture 1
- 2. What is Bioinformatics? Mathematics andStatistics Biology Computer Science
- 3. A working definitionis that of House of Representatives Standing Committee on Primary Industries and Regional Services Inquiry :- "All aspects of gathering, storing, handling, analyzing, interpreting and spreading vast amounts of biological information in databases. The information involved includes gene sequences, biological activity/function, pharmacological activity, biological structure, molecular structure, protein- protein interactions, and gene expression. Bioinformatics uses powerful computers and statistical techniques to accomplish research objectives, for example, to discover a new pharmaceutical or herbicide." What is bioinformatics?
- 4. • Molecular biologyand genetics • Phylogenetic and evolutionary sciences • Different aspects of biotechnology including pharmaceutical and microbiological industries • Medicine • Agriculture •Eco-management Areas of current and future development of bioinformatics
- 5. • Exponential growthof investments • Constant deficit of trained professionals • Diversification of bioinformatics applications • Need in different types of bioinformaticians Why bioinformatics?
- 6. Central Dogma ofMolecular Biology GENOTYPE (i.e. Aa) PHENOTYPE (pink) GENE (DNA) MESSENGER (RNA) PROTEIN TRAIT ATGCAAGTCCACTGTATTCCA UACGUUCAGGUGACAUAAGGG transcription reverse tr translation replication
- 7. DNA Symbol Meaning Explanation GG Guanine A A Adenine T T Thymine C C Cytosine R A or G puRine Y C or T pYrimidine N A, C, G or T Any base Double helix 5’ 3’ 3’ 5’ A C G T C A T G T G C A G T A C RNA 5’ 3’ A C G U C A U G template U U Uracil
- 8. Genetic Code 1. Aminoacids are coded by codons – triplets of nucleotides, e.g. |ACG|TAT|…. 2. There are 43 = 64 codons for ~20 amino acids, the code is degenerate 3. Codons do not overlap 4. Deletions or insertions of one or few nucleotides (not equal to 3 x N) usually destroy a message by shifting a reading frame 5. Three specific codons (stop codons) do not code any amino acid and are always located at the very end of the protein coding part of a gene
- 9.
- 10. The 20 aminoacids common in living organisms
- 11. PROTEINS Green Fluorecent Protein(GFP) 1 mcgkkfelki dnvrfvghpt llqpphtiqa sktdpspkre lptmilfsvv falranadas 61 viscmhnlsr riaialqhee rrcqyltrea klmlamqdev ttiidsdgsp qspfrqilpk 121 cklardlkea ydslcttgvv rlhinnwlev sfclphkihr vggkhiplea lerslkairp
- 12. Genomic Hierarchy inEukaryotes Genome nuclear (1) Chromosomes (23x2) DNA molecules (23x2) Genes (~30,000); only a small fraction of genome Nucleotides (~3x109)
- 13. Eukaryotic genes arecomplex Promoter Exon 1 Exon 2 Exon 3 Exon 4 Start codon Intron 1 Intron 2 Intron 3 Stop codon Protein coding regions
- 14. • The firstbiological database - Protein Identification Resource was established in 1972 by Margaret Dayhoff • Dayhoff and co-workers organized the proteins into families and superfamilies based on degree of sequence similarity • Idea of sequence alignment was introduced as well as special tables that reflected the frequency of changes observed in the sequences of a group of closely related proteins • Currently there are several huge Protein Banks : SwissProt, PIR International, etc. • The first DNA database was established in 1979. Currently there are several powerful databases: GenBank, EMBL, DDBJ, etc. Brief history of bioinformatics: Databases
- 15. Brief history ofbioinformatics: evolutionary reconsructions
- 16. Brief history ofbioinformatics: other important steps • Development of sequence retrieval methods (1970-80s) • Development of principles of sequence alignment (1980s) • Prediction of RNA secondary structure (1980s) • Prediction of protein secondary structure and 3D (1980-90s) • The FASTA and BLAST methods for DB search (1980-90s) • Prediction of genes (1990s) • Studies of complete genome sequences (late 1990s –2000s)
- 17. Collection and retrievalof data. Alignment methods. • Sequencing (DNA, proteins) • Submission of sequences to the databases • Computer storage of sequences • Development of sequence formats • Conversion of one sequence format to another • Development of retrieval and alignment methods
- 18. Prediction, reconstruction and classification •Prediction of secondary and 3D structure of RNA and proteins • Gene prediction in prokaryotes and eukaryotes • Prediction of promoters and other functional sites • Reconstruction of phylogeny • Genome analysis • Classification of proteins and genes
- 19. Prediction of RNAsecondary structure: an example A. Single stranded RNA 5’ 3’ 5’ 3’ B. Stem and loop or hairpin loop
- 20. Expectations of students’performance • Basic understanding of general principles of molecular biology • Some mathematical and computer science background • Focus on using computational methods and understanding general ideas of analysis used in bioinformatics • Formal description of algorithms and complex methodology will not be the core elements of this unit • The core requirement is understanding of foundations of bioinformatics and “hands on” approach