Bioinformatics Final Presentation


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Bioinformatics Final Presentation

  1. 1. BIOINFORMATICS<br />Arushi<br />Dinesh<br />Kasi<br />Shruthi<br />1<br />
  2. 2. introduction<br /><ul><li>Bioinformatics has developed out of the need to understand the code of life, DNA.
  3. 3. Massive DNA sequencing projects have evolved and added in the growth of the science of bioinformatics.
  4. 4. The ultimate goal of bioinformatics is to uncover the wealth of biological information hidden in the mass of sequence, structure, literature and other biological data</li></ul>2<br />
  5. 5. introduction<br />3<br />
  6. 6. bioinformatics<br />4<br />
  7. 7. bioinformatics<br />5<br />
  8. 8. bioinformatics<br />6<br />
  9. 9. Components of Bioinformatics<br />7<br />
  10. 10. What is done in bioinformatics?<br />8<br />
  11. 11. Why use Bioinformatics?<br />9<br />
  12. 12. Applications of bioinformatics<br /><ul><li>Molecular medicine 
  13. 13. Personalized medicine 
  14. 14. Preventative medicine 
  15. 15. Gene therapy 
  16. 16. Drug development  
  17. 17. Microbial genome applications  
  18. 18. Waste cleanup  
  19. 19. Climate change Studies
  20. 20. Alternative energy sources
  21. 21. Biotechnology   </li></ul>10<br />
  22. 22. Applications of bioinformatics<br /><ul><li>Antibiotic resistance  
  23. 23. Forensic analysis of microbes  
  24. 24. Bio-weapon creation  
  25. 25. Evolutionary studies  
  26. 26. Crop improvement  
  27. 27. Insect resistance 
  28. 28. Improve nutritional quality   
  29. 29. Development of Drought resistance varieties  
  30. 30. Veterinary Science  </li></ul>11<br />
  31. 31. Software and tools<br />12<br /><ul><li>Software tools for bioinformatics range from simple command-line tools, to more complex graphical programs and standalone web-services available from various bioinformatics companies or public institutions.
  32. 32. The computational biology tool best-known among biologists is probably BLAST, an algorithm for determining the similarity of arbitrary sequences against other sequences, possibly from curated databases of protein or DNA sequences.
  33. 33. BLAST is one of a number of generally available programs for doing sequence alignment. The NCBI provides a popular web-based implementation that searches their databases. </li></li></ul><li>BLAST<br /><ul><li>Basic Local Alignment Search Tool.
  34. 34. It is an algorithm for comparing biological sequences information, such as amino acid sequence of different proteins or the nucleotides of DNA sequences.
  35. 35. BLAST is used to identify library sequences that resembles the query sequences.
  36. 36. The BLAST program was designed by Eugene Myers, StephenAltschul, Warren Gish, David J. Lipman and WebbMiller at the NIH and was published in J. Mol. Biol. in 1990.</li></ul>13<br />
  37. 37. BLAST<br /><ul><li> BLAST is a tool for alignment of sequences.</li></ul>Eg: To identify the unknown gene(query sequences) in the mouse,<br />the scientist will perform a BLAST search of the human genome (library sequences) to see whether the human carrying the similar gene or not.<br /><ul><li> BLAST was originally developed by NCBI( National Center for Biotechnology Information).
  38. 38. Link:</li></ul>14<br />
  39. 39. BLAST<br /><ul><li>The NCBI site provides binary files for the following operating </li></ul>systems and platforms.<br /><ul><li> UNIX
  40. 40. Linux
  41. 41. Mac
  42. 42. MS-Windows
  43. 43. IBM AIX 5.1</li></ul>15<br />
  44. 44. 16<br />
  45. 45. 17<br />
  46. 46. 18<br />
  47. 47. Kinds of BLAST<br /><ul><li>Nucleotide-nucleotide BLAST (blastn)</li></ul>This program, given a DNA query, returns the most similar DNA sequences from the DNA database that the user specifies.<br /><ul><li>Protein-protein BLAST (blastp)</li></ul>This program, given a protein query, returns the most similar protein sequences from the protein database that the user specifies.<br /><ul><li>Position-Specific Iterative BLAST (PSI-BLAST)</li></ul>This program is used to find distant relatives of a protein. <br />19<br />
  48. 48. Kinds of BLAST<br /><ul><li>Nucleotide 6-frame translation-protein (blastx)</li></ul>This program compares the six-frame conceptual translation products of a nucleotide query sequence (both strands) against a protein sequence database.<br /><ul><li>Nucleotide 6-frame translation-nucleotide 6-frame translation (tblastx)</li></ul>This program is the slowest of the BLAST family.The purpose of tblastx is to find very distant relationships between nucleotide sequences.<br /><ul><li>Protein-nucleotide 6-frame translation (tblastn)</li></ul>This program compares a protein query against the all six reading frames of a nucleotide sequence database.<br />20<br />
  49. 49. process<br /><ul><li>BLAST works through use of heuristic algorithm.
  50. 50. Heuristic algorithm ,is an algorithm that is able to produce an </li></ul>acceptable solution to a problem in many practical scenarios.<br /><ul><li>Heuristics are typically used when there is no known method to</li></ul> find an optimal solution ,under the given constraints.<br />21<br />
  51. 51. process<br /><ul><li> Using a heuristic method ,BLAST finds homologous sequences,</li></ul>not by comparing either sequences in its entirety, but rather by<br /> locating short matches between the two sequences.<br /><ul><li> This process of finding initial words is called seeding.
  52. 52. While attempting to find homology in sequences, sets of </li></ul>common letters, known as words.<br />22<br />
  53. 53. process<br /><ul><li> For example:
  54. 54. The sequences contain the following stretch of letters,GLKFA. If a</li></ul>BLASTp was being conducted under default conditions,theword<br /> size would be 3 letters.<br /><ul><li>In this case, using the given stretch of letters, the searched words would be GLK, LKF,KFA.
  55. 55. The heuristic algorithm of BLAST locates all common words </li></ul>between the sequences of interest (query) and the hit sequences<br />(sequences from database).<br />23<br />
  56. 56. USES OF BLAST<br />BLAST can be used for several purposes. These include:<br /><ul><li>Identifying Species:</li></ul>With the use of BLAST, you can possibly correctly identify a species and/or find homologous species. This can be useful, for example, when you are working with a DNA sequence from an unknown species.<br /><ul><li>Locating Domains:</li></ul>When working with a protein sequence you can input it into BLAST, to locate known domains within the sequence of interest.<br />24<br />
  57. 57. USES OF BLAST<br /><ul><li>Establishing Phylogeny:</li></ul>Using the results received through BLAST, you can create a phylogenetic tree using the BLAST web-page.<br /><ul><li>DNA Mapping:</li></ul>When working with a known species, and looking to sequence a gene at an unknown location, BLAST can compare the chromosomal position of the sequence of interest, to relevant sequences in the database(s).<br /><ul><li>Comparison:</li></ul>When working with genes, BLAST can locate common genes in two related species, and can be used to map annotations from one organism to another.<br />25<br />
  58. 58. SMITH-WATERMAN ALGORITHM<br /><ul><li>The Smith-Waterman algorithm is a well-known algorithm for performing local sequence alignment.
  59. 59. This method varies from the BLAST method in two areas, accuracy and speed. 
  60. 60. A better alternative in order to find the best possible results.
  61. 61. It is more time consuming.</li></ul>26<br />
  62. 62. FASTA<br /><ul><li>FASTA is a DNA and protein sequence alignment software package.
  63. 63. FASTA package contains programs for protein: protein, DNA:DNA, protein : translated DNA , and ordered or unordered peptide searches.
  64. 64.  A major focus of the package is the calculation of accurate similarity statistics, so that biologists can judge whether an alignment is likely to have occurred by chance.</li></ul>27<br />
  65. 65. Conclusion<br />28<br />