The statistical analysis of alignment scores is much better understood for ________ than for _______(a) global alignments, local alignments(b) local alignments, global alignments(c) global alignments, any other alignment method(d) Needleman-Wunsch alignment, Smith-Waterman alignmentThis question was posed to me in examination.The above asked question is from Assessing the Significance of Sequence Alignments topic in section Sequence Alignment of Bioinformatics

The statistical analysis of alignment scores is much better understood

1.	The statistical analysis of alignment scores is much better understood for ________ than for _______(a) global alignments, local alignments(b) local alignments, global alignments(c) global alignments, any other alignment method(d) Needleman-Wunsch alignment, Smith-Waterman alignmentThis question was posed to me in examination.The above asked question is from Assessing the Significance of Sequence Alignments topic in section Sequence Alignment of Bioinformatics
Answer» The correct CHOICE is (b) local alignments, GLOBAL alignments Best explanation: Smith-Waterman alignment algorithm and the SCORING system USED to produce a local alignment are designed to reveal regions of closely matching sequence with a positive alignment score. In random or unrelated sequence alignments, these regions are rarely found. Hence, their presence in real sequence alignments is significant, and the PROBABILITY of their occurring by chance alignment of unrelated sequences can be readily calculated.

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