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Second normal form (2NF), in database normalization, is a normal form. A relation is in the second normal form if it fulfills the following two requirements: A relation is in the second normal form if it fulfills the following two requirements:
In bioinformatics, a sequence alignment is a way of arranging the sequences of DNA, RNA, or protein to identify regions of similarity that may be a consequence of functional, structural, or evolutionary relationships between the sequences. [1] Aligned sequences of nucleotide or amino acid residues are typically represented as rows within a matrix.
The objectives of normalization beyond 1NF (first normal form) were stated by Codd as: To free the collection of relations from undesirable insertion, update and deletion dependencies. To reduce the need for restructuring the collection of relations, as new types of data are introduced, and thus increase the life span of application programs.
Therefore, using a good gap penalty model will avoid low scores in alignments and improve the chances of finding a true alignment. [3] In genetic sequence alignments, gaps are represented as dashes(-) on a protein/DNA sequence alignment. [1] Unix diff function - computes the minimal difference between two files similarly to plagiarism detection.
The multiple sequence alignment problem is generally based on pairwise sequence alignment and currently, for a pairwise sequence alignment problem, biologists can use a dynamic programming approach to obtain its optimal solution. However, the multiple sequence alignment problem is still one of the more challenging problems in bioinformatics.
Recent development has focused on improving the time and space cost of the algorithm while maintaining quality. For example, in 2013, a Fast Optimal Global Sequence Alignment Algorithm (FOGSAA), [9] suggested alignment of nucleotide/protein sequences faster than other optimal global alignment methods, including the Needleman–Wunsch algorithm ...
They are a straightforward modification to the earliest heuristic-based alignment efforts that allow for minor differences between the sequences of interest. Spaced seeds have been used in homology search ., [ 1 ] alignment , [ 2 ] assembly , [ 3 ] and metagenomics . [ 4 ]
Sequence alignment can also reveal conserved domains and motifs. One motivation for local alignment is the difficulty of obtaining correct alignments in regions of low similarity between distantly related biological sequences, because mutations have added too much 'noise' over evolutionary time to allow for a meaningful comparison of those regions.