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BLAST(Basic Local Alignment Tool)
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BLAST(Basic Local Alignment Tool)

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The Basic Local Alignment Search Tool (BLAST) for comparing gene and protein sequences against others in public databases.

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  • 1. Any important work that does not begin with Bismillah is imperfect.
  • 2.
  • 3. (Basic local alignment search Tool) Fast similarity searching of the database
  • 4.
    • Definition & Description
    • Background
    • Algorithm
    • Types of BLAST program
    • BLAST search
    • BLAST Functions
  • 5.
  • 6.
    • The Basic Local Alignment Search Tool ( BLAST ) for comparing gene and protein sequences against others in public databases.
  • 7.
    • Fasta
    • Ssearch
    • BLAST
    • WU-BLAST
    ?? ?? ??
  • 8.
    • BLAST – B asic L ocal A lignment S earch T ool is a set of sequence comparison algorithms used to search databases for optimal local alignments to a query.
    • It breaks the query and database sequences into fragments and seeks matches between them.
  • 9.
    • When you have a nucleotide or protein sequence that you want to search against sequence databases
      • to determine what the sequence is
      • to find related sequences (homologs)
    For Better Understanding let’s take a look at alignment background
  • 10.
  • 11.
    • Beginning in the 1970s , scientists began to accumulate DNA and protein sequence data at an exponential rate; in fact, researchers currently have approximately 97 billion bases sequenced and over 93 million records.
    • Amazingly, this sequence data doubles every 18 months!
  • 12.
    • Today, one of the most commonly used tools to examine DNA and protein sequences is the Basic Local Alignment Search Tool, also known as BLAST (Altschul et al ., 1990).
    • BLAST is a computer algorithm that is available for use online at the (National Center for Biotechnology Information (NCBI) website and many other sites
  • 13.
    • Nucleic acid /Protein Alignments were time consuming.
    • Alignments were done by full alignment by using dynamic programming .
    • BLAST is 50 times faster then dynamic programming.
  • 14.
  • 15.
  • 16.
    • 1- The Smith -Waterman Algorithm
    • 2- BLAST
  • 17.
    • Assign penalties to mismatched pairs, insertions and deletions.
    • Rather than (global alignment), the SW examines all sub-sequences found within the query and potential match sequences, returning only the highest scoring alignment.
  • 18.
    • BLAST uses an algorithm very similar to the Smith-Waterman to query databases for best sequence similarity matches.
    • Heuristic algorithm
    • Advantage: Speed
    • Disadvantage: Deterministic algorithms only return one “best” alignment. There may be many alignments with high scores that won’t be found with this approach.
  • 19.
    • Main idea:
    • Construct a dictionary of all the words in the query
    • Initiate a local alignment for each word match between query and DB
    query DB
  • 20.
    • First step:
    • For each position p of the query, find the list or words of length w
    • scoring more than T when paired with the word starting at p:
    p-word List of all words of length w, scoring more than T with the p-word.
  • 21.
    • Extension of hits: requires a second hit on the same diagonal.
  • 22.
    • Gapped extension of High Scoring Pairs above a threshold.
  • 23.
    • Input and output conform to the
    • FASTA format
  • 24.
  • 25.
    • 1- Nucleotide-nucleotide BLAST (blastn)
    • 2- Protein-protein BLAST (blastp)
    • 3- Position-Specific Iterative BLAST (PSI-BLAST)
    • 4- Nucleotide 6-frame translation-protein (blastx)
    • 5- Nucleotide 6-frame translation-nucleotide 6-frame translation (tblastx)
    • 6- Protein-nucleotide 6-frame translation (tblastn)
    • 7- Large numbers of query sequences (megablast)
  • 26.
  • 27.
  • 28.  
  • 29.
  • 30.
  • 31.
    • Select a BLAST program
    • Selecting the BLAST Database
    • Entering your Sequence
      • FASTA format
      • Accession / GI number
    • Submitting your search
  • 32.
  • 33. Insert your sequence in FASTA format Submit your search
  • 34.
  • 35.  
  • 36.
    • Identifying Species
    • Locating Domains
    • Establishing Phylogeny
    • DNA Mapping
    • Comparison
  • 37.
  • 38.  
  • 39.