 Dear students, in this module, we're going to continue exploring the pairwise sequence alignment. This is the second module in the series of three modules on pairwise sequence alignment. Let's take a look at what we already know. So pairwise sequence alignment essentially means that you're trying to compare two sequences. And the process that it involves is the inexact matching process. In the inexact matching process, we consider some differences between the sequences. And if there is an insertion or a dilation within the two sequences, then we can create a dot in the alignment and it's called a gap. So the process that you need to remember always is that the process starts with sliding the two sequences against each other. So once you do that, then you try to maximize the matches between these two sequences. And thirdly, during this maximization of the matches, if there is a situation where there is an extra amino acid or nucleotide in one sequence, then in the corresponding sequence you place a dot. This is called a gap. Let's talk about the gaps. Gaps are very important because in the evolutionary process, sometimes a nucleotide or an amino acid may be inserted into the sequence or deleted from the sequence. So in either case, if you arrive at a situation where you have to compare two sequences where one amino acid or nucleotide is missing versus another sequence in which that nucleotide or amino acid is present, then gaps are very useful and handy. So to introduce the gap, we must introduce a penalty as well because if two sequences are matching with each other but there is a gap in the middle, then we need to penalize that gap or we need to give a negative score to that match. If we do not give a negative score, then an exact match will obtain a score that is equal to an alignment where you have only one gap in the comparison of the two sequences. Therefore, gaps need to be given a negative score whenever you're aligning two sequences. Now let's take a look at the types of pairwise sequence alignments. There are two types in general. One is the global and the other is the local pairwise alignment. So in the global pairwise alignment, your aim is to maximize the sequence matches over the entire sequence by introducing gaps. So this is very, very important. I will repeat again. In the global pairwise sequence alignment, you try to maximize the sequence match over the entire sequence by introducing gaps. While in the local pairwise sequence alignment, you don't do that and you only go for the strongest similarity within the sequence. It does not have to be the entire sequence in this case. So you're only matching the local portions within the sequence. While in the global pairwise sequence alignment, you're trying to compare the full sequences against each other. So therefore, for the global sequence alignment, you determine the overall similarity. While in the local pairwise sequence alignment, you only find similar domains or actually portions such as motifs between motifs and domains between two sequences. So in this way, local alignment helps you identify portions within the sequences which are very similar while the global pairwise sequence alignment allows you to compare two sequences in their entirety. So as I just mentioned, the global alignment maximizes the number of matches between the query and the source. So these are the two sequences along the entire length of the sequences while the local alignment gives the score to the local match between the query and source sequence. There is a third category of sequence alignment as well which is actually not a formal category and that is the optimal alignment. So this kind of alignment exhibits the most correspondence between the query and the source. It is the alignment with the highest score. We'll discuss how to score these alignments later. So we will come back to the optimal alignment at that point. Important to note here is that such a highest scoring alignment may not be biologically meaningful. So in conclusion, the gaps are inserted to accommodate insertions and deletions of nucleotides or amino acids from sequences during the evolutionary process and that global and local alignments are used depending on our objective for aligning the two sequences. If we are trying to compare the entire sequence versus another sequence then we can use the global alignment or if we are trying to compare only portions of one sequence and another sequence we may go for local sequence alignment.