<p><span style="font-size:16px"><span style="font-family:times new roman,times,serif">If the target sequence, which is very short like 10~20 nucleotide long, is given, it could be aligned manually. But the information needed in real medical science is too lengthy to be analyzed by only human effort. In that sense, there are hundreds of softwares developed by many companies that can conduct sequence alignment of all DNA, RNA, and proteins in these days. As all those methods invented to compare the potential sequence alignments, each method has its own formulas to determine the values for each alignment. The formulas are known as objective functions which mean that the data range from simple to complex values. And those are generally divided into two categories, global and local alignments. Global alignments span based on the idea that the entire sequences are homologous, and the given sequences are to be aligned through whole region sites within it. But global methods have drawbacks that those are hard to apply on large and long sequences. In the case of long sequences, but the homologous sequences are just exist in a form of little motif. Thus, to resolve the problems, the local alignments select some similar region in lengthy stringsare developed. The Through local alignments , the sequences can be aligned separately without reference patterns and ignore the large portion of unaligned sites.</span></span></p> <p><span style="font-size:16px"><span style="font-family:times new roman,times,serif">In those two categories, there are better some representative alignments methods &ndash; Pairwise alignments, Multiple sequence alignments, Structural alignments.</span></span></p> <p>&nbsp;</p> <p><u><span style="font-size:16px"><span style="font-family:times new roman,times,serif"><strong>Multiple alignments</strong></span></span></u></p> <p><span style="font-size:16px"><span style="font-family:times new roman,times,serif">In general, most alignment methods conduct the determination of similarities or some other factors between two sequences. But the Multiple alignments, like its name, use sequences more than two for precise analysis but . In multiple rows of sequences, the consensus sequence is shown in the last row. Thus it is more difficult than global alignments due easy to find out what the selection conserved sequence is among hundreds of sequences. The information about conserved sequences can be used in analyzing active sites of enzymes or establishing evolutionary relationships.</span></span></p> <p><span style="font-size:16px"><span style="font-family:times new roman,times,serif">But this approach requires thousands of similar region within huge group data, it is indicated as a drawback that the inefficiency of biomoleculescomputational intractability. Thus many alternative approaches for this method suggested such as weighted averaging.</span></span></p>