Conserved Sequence: Progressive Alignment and Binary Boolean Logic Algorithm

We provide a technique for identifying sequence sites expressed in conserved sequences, which are partial se-quences of known viral sequences, and we also propose that the conserved sequences are transformed at the protein level. In addition, we would like to support specialists in the pre-liminary identification of sequence fragments that can subsequently be investigated as potential vaccine candidates. The proposed approach generally focuses on analyzing mutations in sequences, which are then represented using the Kimura model, based on the genetic distance between sequences. Next, we select the best alignment technique to support the proposed algorithm. We choose progressive alignment for the alignment method and neighbor connection technique for the guide tree depending on the type. Finally, we developed an algorithm by combining progressive alignment and Boolean logic, which we call the binary Boolean logic algorithm. Next, we can obtain sustainable sequences for further analysis, which can then be used to determine vaccine candidates for specific viruses. The proposed method was evaluated using SARS-CoV-2 sequence data. Experimental results show that the proposed algorithm is proven to be able to determine proteins used for the analysis of vaccine candidates by displaying the sequence position in BLAST.