Difference between revisions of "BLAST"
From Bioinformatikpedia
(Created page with "==Basic Information== {| style="float: right; border: 1px solid #BBB; margin: .46em 0 0 .2em;" ! Author | Stephen Altschul, Warren Gish, David Lipman |- ! Year | 1990 |- ! Refer…") |
|||
(3 intermediate revisions by the same user not shown) | |||
Line 3: | Line 3: | ||
{| style="float: right; border: 1px solid #BBB; margin: .46em 0 0 .2em;" |
{| style="float: right; border: 1px solid #BBB; margin: .46em 0 0 .2em;" |
||
! Author |
! Author |
||
− | | Stephen Altschul, Warren Gish, David Lipman |
+ | | Eugene Myers, Stephen Altschul, Warren Gish, David Lipman |
|- |
|- |
||
! Year |
! Year |
||
Line 19: | Line 19: | ||
BLAST, Basic Local Alignment Search Tool, finds regions of local similarity between sequences. The program compares nucleotide or protein sequences to sequence databases and calculates the statistical significance of matches. BLAST is a heuristic to the calculation of optimal alignments calculated by dynamic programming. |
BLAST, Basic Local Alignment Search Tool, finds regions of local similarity between sequences. The program compares nucleotide or protein sequences to sequence databases and calculates the statistical significance of matches. BLAST is a heuristic to the calculation of optimal alignments calculated by dynamic programming. |
||
+ | |||
+ | |||
+ | |||
+ | |||
+ | |||
==Details== |
==Details== |
Latest revision as of 16:08, 17 August 2011
Basic Information
Author | Eugene Myers, Stephen Altschul, Warren Gish, David Lipman |
---|---|
Year | 1990 |
Reference | Basic local alignment search tool |
Short description | Alignment Heuristic |
Method | seed words |
BLAST, Basic Local Alignment Search Tool, finds regions of local similarity between sequences. The program compares nucleotide or protein sequences to sequence databases and calculates the statistical significance of matches. BLAST is a heuristic to the calculation of optimal alignments calculated by dynamic programming.
Details
In a first step BLAST locates short words, with significant scores and a certain length (e.g. 3) within a sequence, this is called seeding. These first matches are used for local alignments. High scoring words within a database can be pre-calculated. The challenge of BLAST was to calculate proper statistics for the searches.