Antiviral software systems (AVSs) have problems in identifying polymorphic variants of viruses without explicit signatures for such variants. Alignment-based techniques from bioinformatics may provide a novel way to g...Antiviral software systems (AVSs) have problems in identifying polymorphic variants of viruses without explicit signatures for such variants. Alignment-based techniques from bioinformatics may provide a novel way to generate signatures from consensuses found in polymorphic variant code. We demonstrate how multiple sequence alignment supplemented with gap penalties leads to viral code signatures that generalize successfully to previously known polymorphic variants of JS. Cassandra virus and previously unknown polymorphic variants of W32.CTX/W32.Cholera and W32.Kitti viruses. The implications are that future smart AVSs may be able to generate effective signatures automatically from actual viral code by varying gap penalties to cover for both known and unknown polymorphic variants.展开更多
Biological sequence alignment is one of the most important problems in computational biology. The objective of the alignment process is to maximize the alignment score between two given sequences of varying or equal l...Biological sequence alignment is one of the most important problems in computational biology. The objective of the alignment process is to maximize the alignment score between two given sequences of varying or equal length. The alignment score of two sequences is calculated based on matches, mismatches and gaps in the alignment. We have proposed a new genetic approach for finding optimized match between two DNA or protein sequences. The process is compared with two well known relevant sequence alignment techniques.展开更多
Multiple sequence alignment （MSA） is the alignment among more than two molecular biological sequences, which is a fundamental method to analyze evolutionary events such as mutations, insertions, deletions, and re-ar...Multiple sequence alignment （MSA） is the alignment among more than two molecular biological sequences, which is a fundamental method to analyze evolutionary events such as mutations, insertions, deletions, and re-arrangements. In theory, a dynamic programming algorithm can be employed to produce the optimal MSA. However, this leads to an explosive increase in computing time and memory consumption as the number of sequences increases （Taylor, 1990）. So far, MSA is still regarded as one of the most challenging problems in bioinformatics and computational biology （Chatzou et al., 2016）.展开更多
文摘Antiviral software systems (AVSs) have problems in identifying polymorphic variants of viruses without explicit signatures for such variants. Alignment-based techniques from bioinformatics may provide a novel way to generate signatures from consensuses found in polymorphic variant code. We demonstrate how multiple sequence alignment supplemented with gap penalties leads to viral code signatures that generalize successfully to previously known polymorphic variants of JS. Cassandra virus and previously unknown polymorphic variants of W32.CTX/W32.Cholera and W32.Kitti viruses. The implications are that future smart AVSs may be able to generate effective signatures automatically from actual viral code by varying gap penalties to cover for both known and unknown polymorphic variants.
文摘Biological sequence alignment is one of the most important problems in computational biology. The objective of the alignment process is to maximize the alignment score between two given sequences of varying or equal length. The alignment score of two sequences is calculated based on matches, mismatches and gaps in the alignment. We have proposed a new genetic approach for finding optimized match between two DNA or protein sequences. The process is compared with two well known relevant sequence alignment techniques.
基金supported by the National Key R&D Program of China (Nos. 2017YFB0202600, 2016YFC1302500, 2016YFB0200400 and 2017YFB0202104)the National Natural Science Foundation of China (Nos. 61772543, U1435222, 61625202, 61272056 and 61771331)Guangdong Provincial Department of Science and Technology (No. 2016B090918122)
文摘Multiple sequence alignment （MSA） is the alignment among more than two molecular biological sequences, which is a fundamental method to analyze evolutionary events such as mutations, insertions, deletions, and re-arrangements. In theory, a dynamic programming algorithm can be employed to produce the optimal MSA. However, this leads to an explosive increase in computing time and memory consumption as the number of sequences increases （Taylor, 1990）. So far, MSA is still regarded as one of the most challenging problems in bioinformatics and computational biology （Chatzou et al., 2016）.
