 The students in this module will be looking at the functional implementation or the working of the fast alignment algorithm. So just to warm you up, the fast alignment algorithm can help you search and compare sequences from the databases. More so, this exercise can help you to obtain comparison between organisms as well as the evolutionary history of a sequence. To start with the algorithm, let's put your sequence from database on one side and your sequence that is your query on the other side. So of course you will have multiple sequences that will be getting compared with the query one by one. So let's consider one sequence at a time and assume that there is some portion within the database sequence that matches very nicely with the query. So in this way you can create a dot plot and as you would remember that the dot plot helps you to find out all such diagonals between the database sequence and the query sequence. And here all such sequences have been plotted for you as an example. So in all there are six matches between the sequence from the database and the sequence that is given as a query. Now if you look at these number four and number five diagonals here and here. So they have different offset values while if you look at the diagonal number three it has a very identical offset value and it is a contiguous very long diagonal and these are small diagonals. So if you remember when we looked at the dot plots that the shorter the diagonals the higher the chance that that diagonal is a random match. So therefore you are hunting for the longer diagonals the longer the diagonals the better. So next you select the longer diagonals. So you select these three and you ignore these ones and then you want to extend these diagonals. So as you can see this portion is disconnected and this portion is disconnected. So you want to extend these diagonals such that they are joined. So how do we do that? By removing the shorter diagonals and setting a cutoff score. So in the end you only have a very clean set of diagonals and then you join them using the Smith-Waterman algorithm. Here and then you have a very nice alignment to finish the job. So in conclusion FASTA performs the preliminary alignments by using a dot matrix dot plot and then you extend the diagonals that are contiguous that is that are connected and are very long. And once you have all such diagonals you perform a threshold on the length of the diagonals and you only select the best diagonals. So these best diagonals the longest ones are then connected using the Smith-Waterman algorithm. And the result can be output in visual format as we just saw and you can analyze the statistical scores as well.