 Dear students, in this module, I'll continue on building the concept of Fast A or Fast Alignment Algorithm. You know that the classical global and local alignment algorithms such as Smith, Waterman and Neelman-Wunsch take a lot of time. They use dynamic programming approaches and to solve the dynamic programming matrix for once it's easy but to do it for many sequences and many databases takes a lot more time. Hence there is a need to have these faster, a little approximate algorithms which can help you to find the sequence alignment in a short span of time. So Fast A achieves this alignment by using short lengths of exact matches. So what I mean here by short length of exact matches is that exact match is a 100% similar sequence between the database and your query. So short sequences of such matches are collected and then an alignment procedure is performed on the resulting comparisons. So essentially Fast A relies on aligning these subsequences of a 100% similarity. This helps bias the algorithm towards these matches and therefore speed up the search. Now towards the input to Fast A and the outputs from the algorithm. So Fast A or Fast Alignment Algorithm and the EBI portal, the online website for performing Fast A accepts inputs by protein and gene IDs or simply sequences as well amongst many other input formats. And the results after you perform Fast Alignment are output in the form of a table wherein the score for each hit or the each result after the comparison is sorted by the highest score first. A statistical evaluation is also provided alongside so you can look at the quality of your result. If you click at the entries within the table you can look at the details and of course you can also see the IDs and the details of the scores alongside. Okay to help you visualize things so input to Fast A for instance if you want to do nucleotide similarity search can be the gene IDs. You just go to the web portal and you click on the nucleotide. So this portal is the EBI's Fast A. So once you select the nucleotide similarity search you can specify the database here the one which you want to compare your sequence with and here you can enter your sequence. If you look closely then you will see a drop down list box here which states DNA of course you can also put an RNA here. Okay so what if you want to do a protein sequence analysis so to compare protein sequences then you go to the protein similarity search on the same portal and you select your database here and you input your protein sequence here. So this can be a simple protein sequence or it can be a protein ID which you can find from Unifrot and other online protein databases. And if you press the search button then you will arrive at the results. So this is from a protein comparison that I input in the previous slide and you can see that's there is this list of proteins that has been found from the database which are very similar to my query that I input in the previous slide. In the Fast A if you bring your mouse here and you click on one of these entries then you can look at the details of each entry one by one. So in conclusion the purpose of Fast A is to perform sequence comparison in a short amount of time and you can employ it on large sets of sequences which you want to compare. So if you want to compare Fast A versus Smith Waterman then obviously Fast A will work quickly however Smith Waterman may sometimes give you more accurate results. So essentially it is a compromise between the speed of the algorithm and the accuracy of the algorithm. So the inputs and outputs can be similar to BLAST which we looked at and you can input the sequence or the IDs for both.