Bioinformatics (Exam point of view)
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The document discusses bioinformatics, emphasizing its role as a bridge between biological observations and computational understanding, involving applications like genomics and drug design. It explores the organization and classification of biological databases, detailing primary and secondary databases for managing biological data. Additionally, it highlights the significance of sequence analysis methods and their applications in various fields such as genomics, proteomics, and drug discovery.
Bioinformatics (Exam point of view)
- 1. Dept. of Computational Biology & Bioinformatics 1 Test Slide
- 2. Dept. of Computational Biology & Bioinformatics 2
- 3. 3 Bioinformatics Dept. of Computational Biology & Bioinformatics
- 4. Bioinformatics - play with sequences & structures Dept. of Computational Biology & Bioinformatics 4
- 5. ORGANIZATION OF LIFE 5 ROLE OF BIOINFORMATICS Dept. of Computational Biology & Bioinformatics
- 6. 6 WHAT IS BIOINFORMATICS? Computational Biology/Bioinformatics is the application of computer sciences and allied technologies to answer the questions of Biologists, about the mysteries of life. It has evolved to serve as the bridge between: Observations (data) in diverse biologically-related disciplines and The derivations of understanding (information) APPLICATIONS OF BIOINFORMATICS Computer Aided Drug Design Microarray Bioinformatics Proteomics Genomics Biological Databases Phylogenetics Systems Biology Dept. of Computational Biology & Bioinformatics
- 7. 7 WHAT IS A BIO-SEQUENCE? WHAT IS SEQUENCE ALIGNMENT? Arranging DNA/protein sequences side by side to study the extent of their similarity AGTCTTGATTCTTCTAGTTCTGC GTCCTGATAAGTCAGTGTCTCC TGAGTCTAGCTTCTGTCCATGCT GATCATGTCCATGTTCTAGTCAT GATAGTTGATTCTAGTGTCCTG ATTAGCCTTGAATCTTCTAGTTC TGTCCATTATCCATCTGATGGA GTAGTTATGCGATCTCATG GT CCGATACTATCCTGATATAGCTT AATCTTCTAGTTCTGTCCATTAT CCATCTGTC ARNDCQEGHILKMFPUSTWYZEGNDTWRDC FPUQEGHILDCLKSTMFEWCUWESTHCFPW RDTCEDUSTTWEGHILDNDTEGHTWUWWE SPUSTPPUQWRDCCLKSWCUWMFCQEDT WRWESPWYZWEGHILDDFPTCTWRDSTTFP UEEDCCDTWCUWGHISTDTKKSUNENDCFE GWCRGHPPHHLDTWQESRNDCQEGHILKM FPUSTWYZEGNDTWRDCFPUQEGHILDCLK STMFEWCUWESTHCFPWRDTCEDUSTTWE GHILDNDTEGHTWUWWESPUSTPPUQWRD CCLKSWCUWMFCQEDTWRWESPWYZWEG HILDDFPTCTWRDSTTFPUEEDCCDTWCUW DNA, RNA or protein information represented as a series of bases (or amino acids) that appear in bio-molecules. The method by which a bio- sequence is obtained is called Bio-sequencing. DNA/ RNA SEQUENCE PROTEIN SEQUENCE Dept. of Computational Biology & Bioinformatics
- 8. 8 CRISIS AFTER DATA EXPLOSION!! sequencing Dept. of Computational Biology & Bioinformatics
- 9. DATA EXPLOSION TREND 9 BIOLOGICAL DATABASESSOLUTION?? Dept. of Computational Biology & Bioinformatics
- 10. 10 BIOLOGICAL DATABASES Dept. of Computational Biology & Bioinformatics
- 11. 11 A structured set of data held in a computer, esp. one that is accessible in various ways. WHAT IS A DATABASE? Dept. of Computational Biology & Bioinformatics
- 12. 12 POPULAR DATABASE WEBSITES Dept. of Computational Biology & Bioinformatics
- 13. BIOLOGICAL DATABASES 13Dept. of Computational Biology & Bioinformatics
- 14. 14 CLASSIFICATION OF BIOLOGICAL DATABASES Based on data source Based on data type Dept. of Computational Biology & Bioinformatics
- 15. 15 BASED ON DATA SOURCE Dept. of Computational Biology & Bioinformatics
- 16. 16 BIOLOGICAL DATABASES PRIMARY DATABASES SECONDARY DATABASES • First-hand information of experimental data from scientists and researchers • Data not edited or validated • Raw and original submission of data • Made available to public for annotation • Derived from information gathered in primary database • Data is manually curated and annotated • Data of highest quality as it is double checked Dept. of Computational Biology & Bioinformatics
- 17. Database Website 1. NCBI (National Centre for Biotechnology Information) www.ncbi.nlm.nih.gov 2. DDBJ (DNA Data Bank of Japan) www.ddbj.nig.ac.jp 3. EMBL(European Molecular Biology Laboratory) www.ebi.ac.uk/embl 4. PIR (Protein Information Resource) www.pir.georgetown.edu 5. PDB (Protein Data Bank) www.rcsb.org/pdb 6. NDB( Nucleotide Data Bank) www.ndbserver.rutgers.edu 7. SwissProt (Protein- only sequence database) www.expasy.ch PRIMARY DATABASES
- 18. SECONDARY DATABASES Database Website 1. PROSITE (Protein domains, families, functional sites) www.expasy.org/prosite 2. Pfam (Protein families) www.sanger.ac.uk/pfam 3. SCOP (Structural Classification Of Proteins) www.scop.mrc-lmb.cam.ac.uk/scop 4. CATH (Class, Architecture, Topology, Homologous Super Family of Proteins) www.cathdb.info 5. OMIM (Online Mendelian Inheritance in Man) www.ncbi.nlm.nih/omim 6. KEGG (Kyoto Encyclopedia of Genes and Genome) www.genome.jp/kegg/pathway.html 7. MetaCyc (Enzyme Metabolic Pathways) www.metacyc.org 18Dept. of Computational Biology & Bioinformatics
- 19. Based on type of data 19Dept. of Computational Biology & Bioinformatics
- 20. 20 BIOLOGICAL DATABASES NUCLEOTIDE SEQUENCE DATABASE PROTEIN SEQUENCE DATABASE GENOME DATABASE GENE EXPRESSION DATABASE ENZYME DATABASE STRUCTURE DATABASE PROTEIN INTERACTION DATABASE PATHWAY DATABASE LITERATURE DATABASE BASED ON THE TYPE OF DATA Dept. of Computational Biology & Bioinformatics
- 21. 21 NUCLEOTIDE SEQUENCE DATABASES Dept. of Computational Biology & Bioinformatics
- 22. 22 NCBI- National Centre for Biotechnology Information Dept. of Computational Biology & Bioinformatics
- 23. 23 EMBL – European Molecular Biology Lab Dept. of Computational Biology & Bioinformatics
- 24. 24 DDBJ- DNA DATA BANK OF JAPAN Dept. of Computational Biology & Bioinformatics
- 25. 25 PROTEIN SEQUENCE DATABASE Dept. of Computational Biology & Bioinformatics
- 26. Dept. of Computational Biology & Bioinformatics 26
- 27. 27 PDB- PROTEIN DATA BANK Dept. of Computational Biology & Bioinformatics
- 28. 28 PATHWAY DATABASES Dept. of Computational Biology & Bioinformatics
- 29. 29 KEGG- KYOTO ENCYCLOPEDIA OF GENES AND GENOMES Dept. of Computational Biology & Bioinformatics
- 30. 30 GENOME DATABASE Dept. of Computational Biology & Bioinformatics
- 31. 31 WORMBASE : has the entire genome of C. elegans and other nematodes Dept. of Computational Biology & Bioinformatics
- 32. 32 GENE EXPRESSION DATABASE Dept. of Computational Biology & Bioinformatics
- 33. 33Dept. of Computational Biology & Bioinformatics
- 34. Microarrays provide a means to measure gene expression Dept. of Computational Biology & Bioinformatics 34
- 35. Yeast genome on a chip
- 36. 36 ENZYME DATABASE Dept. of Computational Biology & Bioinformatics
- 37. 37 ENZYME DATABASE OF ExPaSy server Dept. of Computational Biology & Bioinformatics
- 38. 38 STRUCTURE DATABASE Dept. of Computational Biology & Bioinformatics
- 39. 39Dept. of Computational Biology & Bioinformatics
- 40. 40 LITERATURE DATABASE Dept. of Computational Biology & Bioinformatics
- 41. 41Dept. of Computational Biology & Bioinformatics
- 42. Use of Databases in Biology- Sequence Analysis Dept. of Computational Biology & Bioinformatics 42
- 43. Where do we get these sequences from? Through genome sequencing projects Dept. of Computational Biology & Bioinformatics 43
- 44. • Submit sequences to biological databases • Biological databases helps in efficient manipulation of large data sets • Provides improved search sensitivity, search efficiency • Joining of multiple data sets • Databases allows the users to analyse the biological data sets DNA RNA Proteins Dept. of Computational Biology & Bioinformatics 44
- 45. Analysis of Nucleic acids & Protein Sequences • Sequence Analysis Process of subjecting a DNA, RNA or peptide sequence to any of a wide range of analytical methods To understand its features, function, structure, or evolution To assign function to genes & proteins by the studying the similarities between the compared sequences Methodologies include: Sequence alignment Searches against biological databases Dept. of Computational Biology & Bioinformatics 45
- 46. • Sequence analysis in molecular biology includes a very wide range of relevant topics: The comparison of sequences in order to find similarity, infer if they are related (homologous) Identification of active sites, gene structures, reading frames etc. Identification of sequence differences and variations – SNP, Point mutations, identify genetic markers Revealing the evolution and genetic diversity of sequences and organisms Identification of molecular structure from sequence alone Dept. of Computational Biology & Bioinformatics 46
- 47. Sequence Alignment Relationships between these sequences are usually discovered by aligning them together assigning a score to the alignments Two main types of sequence alignment: Pair-wise sequence alignment - compares only two sequences at a time Multiple sequence alignment- compares many sequences Two important algorithms for aligning pairs of sequences : Needleman-Wunsch algorithm Smith-Waterman algorithm Dept. of Computational Biology & Bioinformatics 47
- 48. • Popular tools for sequence alignment include: Pair-wise alignment - BLAST Multiple alignment - ClustalW, MUSCLE, MAFFT, T-Coffee etc. • Alignment methods: Local alignments - Needleman–Wunsch algorithm Global alignments - Smith-Waterman algorithm Dept. of Computational Biology & Bioinformatics 48
- 49. Pair-wise alignment • Used to find the best-matching piecewise (local or global) alignments of two query sequences • Can only be used between two sequences at a time Dept. of Computational Biology & Bioinformatics 49
- 50. Multiple Sequence Alignment • Is an extension of pairwise alignment to incorporate more than two sequences at a time • Align all of the sequences in a given query set • Often used in identifying conserved sequence regions across a group of sequences hypothesized to be evolutionarily related • Alignments helps to establish evolutionary relationships by constructing phylogenetic trees Dept. of Computational Biology & Bioinformatics 50
- 51. Sequence Analaysis Tools Pair-wise alignment - BLAST • Basic Local Alignment Search Tool (BLAST) • Developed by Research staff at NCBI/GenBank as a new way to perform seq. similarity search • Available as free service over internet • Very fast ,Accurate and sensitive database searching • Server-NCBI Dept. of Computational Biology & Bioinformatics 51
- 52. Types of BLAST Programs: Dept. of Computational Biology & Bioinformatics 52
- 53. Dept. of Computational Biology & Bioinformatics 53 NCBI -BLAST
- 54. Dept. of Computational Biology & Bioinformatics 54
- 55. Dept. of Computational Biology & Bioinformatics 55
- 56. FASTA Dept. of Computational Biology & Bioinformatics 56 • DNA & Protein sequence alignment software package • Fast A “Fast –ALL” • Works on any Alphabets - FAST P Protein - FAST N Nucleotide
- 57. Dept. of Computational Biology & Bioinformatics 57
- 58. Sequence Analaysis Tools Multiple alignment - ClustalW • Study the identities, Similarities & Differences • Study evolutionary relationship • Identification of conserved sequence regions • Useful in predicting – Function & structure of proteins Identifying new members of protein families Dept. of Computational Biology & Bioinformatics 58
- 59. Dept. of Computational Biology & Bioinformatics 59
- 60. Dept. of Computational Biology & Bioinformatics 60
- 61. Dept. of Computational Biology & Bioinformatics 61
- 62. Includes all methods, theoretical & computational, used to model or mimic the behaviour of molecules Helps to study molecular systems ranging from small chemical systems to large biological molecules The methods are used in the fields of : Computational chemistry Drug design Computational biology Materials science Dept. of Computational Biology & Bioinformatics 62
- 63. Structure Analysis of Proteins • Researchers predict the 3D structure using protein or molecular modeling • Experimentally determined protein structures (templates) are used • To predict the structure of another protein that has a similar amino acid sequence (target) Dept. of Computational Biology & Bioinformatics 63
- 64. Advantages in Protein Modeling • Examining a protein in 3D allows for : greater understanding of protein functions providing a visual understanding that cannot always be conveyed through still photographs or descriptions Dept. of Computational Biology & Bioinformatics 64
- 65. Example of 3D-Protein Model Dept. of Computational Biology & Bioinformatics 65
- 66. Impact of Bioinformatics in Biology/Biotechnology Dept. of Computational Biology & Bioinformatics 66
- 67. • Biological research is the most fundamental research to understand complete mechanism of living system • The advancements in technologies helps in providing regular updates and contribution to make human life better and better. Reduced the time consuming experimental procedure Software development – Bioinformatians & Computational Biologists Submitting biological sequences to databases Dept. of Computational Biology & Bioinformatics 67
- 68. Role of Bioinformatics in Biotechnology Dept. of Computational Biology & Bioinformatics 68
- 69. • Genomics The study of genes and their expression Generates vast amount of data from gene sequences, their interrelations & functions Understand structural genomics, functional genomics and nutritional genomics • Proteomics Study of protein structure, function &interactions produced by a particular cell, tissue, or organism Deals with techniques of genetics, biochemistry and molecular biology Study protein-protein interactions, protein profiles, protein activity pattern and organelles compositions Dept. of Computational Biology & Bioinformatics 69
- 70. • Transcriptomics Study of sets of all messenger RNA molecules in the cell Also be called as Expression Profiling- DNA Micro array RNA sequencing –NGS Used to analyse the continuously changing cellular transcriptome • Cheminformatics Deals with focuses on storing, indexing, searching, retrieving, and applying information about chemical compounds involves organization of chemical data in a logical form - to facilitate the retrieval of chemical properties, structures & their relationships Helps to identify and structurally modify a natural product Dept. of Computational Biology & Bioinformatics 70
- 71. • Drug Discovery Increasingly important role in drug discovery, drug assessment & drug development Computer-aided drug design (CADD)- generate more & more drugs in a short period of time with low risk wide range of drug-related databases & softwares - for various purposes related to drug designing & development process • Evolutionary Studies Phylogenetics - evolutionary relationship among individuals or group of organisms phylogenetic trees are constructed based on the sequence alignment using various methods Dept. of Computational Biology & Bioinformatics 71
- 72. • Crop Improvement Innovations in omics based research improve the plant based research Understand molecular system of the plant which are used to improve the plant productivity comparative genomics helps in understanding the genes & their functions, biological properties of each species • Biodefense Biosecurity of organisms - subjected to biological threats or infectious diseases (Biowar) Bioinformatics- limited impact on forensic & intelligence operations Need of more algorithms in bioinformatics for biodefense • Bioenergy/Biofuels contributing to the growing global demand for alternative sources of renewable energy progress in algal genomics + ‘omics’ approach - Metabolic pathway & genes – genetically engineered micro algal strains Dept. of Computational Biology & Bioinformatics 72