In this paper, we report a multiple sequence alignment result on the basis of 10 amino acid sequences of the M protein, which come from different coronaviruses (4 SARS associated and 6 others known). The alignment mo...In this paper, we report a multiple sequence alignment result on the basis of 10 amino acid sequences of the M protein, which come from different coronaviruses (4 SARS associated and 6 others known). The alignment model was based on the profile HMM (Hidden Markov Model), and the model training was implemented through the SAHMM (Self Adapting Hidden Markov Model) software developed by the authors.展开更多
In this letter, we briefly describe a program of self adapting hidden Markov model (SA HMM) and its application in multiple sequences alignment. Program consists of two stage optimisation algorithm.
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
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
Creating a multi-gene alignment matrix for phylogenetic analysis using organelle genomes involves aligning single-gene datasets manually,a process that can be time-consuming and prone to errors.The HomBlocks pipeline ...Creating a multi-gene alignment matrix for phylogenetic analysis using organelle genomes involves aligning single-gene datasets manually,a process that can be time-consuming and prone to errors.The HomBlocks pipeline has been created to eliminate the inaccuracies arising from manual operations.The processing of a large number of sequences,however,remains a time-consuming task.To conquer this challenge,we develop a speedy and efficient method called Organelle Genomes for Phylogenetic Analysis(ORPA).ORPA can quickly generate multiple sequence alignments for whole-genome comparisons by parsing the result files of NCBI BLAST,completing the task just in 1 min.With increasing data volume,the efficiency of ORPA is even more pronounced,over 300 times faster than HomBlocks in aligning 60 high-plant chloroplast genomes.The phylogenetic tree outputs from ORPA are equivalent to HomBlocks,indicating its outstanding efficiency.Due to its speed and accuracy,ORPA can identify species-level evolutionary conflicts,providing valuable insights into evolutionary cognition.展开更多
The alignment operation between many protein sequences or DNAsequences related to the scientific bioinformatics application is very complex.There is a trade-off in the objectives in the existing techniques of Multiple...The alignment operation between many protein sequences or DNAsequences related to the scientific bioinformatics application is very complex.There is a trade-off in the objectives in the existing techniques of MultipleSequence Alignment (MSA). The techniques that concern with speed ignoreaccuracy, whereas techniques that concern with accuracy ignore speed. Theterm alignment means to get the similarity in different sequences with highaccuracy. The more growing number of sequences leads to a very complexand complicated problem. Because of the emergence;rapid development;anddependence on gene sequencing, sequence alignment has become importantin every biological relationship analysis process. Calculating the numberof similar amino acids is the primary method for proving that there is arelationship between two sequences. The time is a main issue in any alignmenttechnique. In this paper, a more effective MSA method for handling themassive multiple protein sequences alignment maintaining the highest accuracy with less time consumption is proposed. The proposed method dependson Artificial Fish Swarm (AFS) algorithm that can break down the mostchallenges of MSA problems. The AFS is exploited to obtain high accuracyin adequate time. ASF has been increasing popularly in various applicationssuch as artificial intelligence, computer vision, machine learning, and dataintensive application. It basically mimics the behavior of fish trying to getthe food in nature. The proposed mechanisms of AFS that is like preying,swarming, following, moving, and leaping help in increasing the accuracy andconcerning the speed by decreasing execution time. The sense organs that aidthe artificial fishes to collect information and vision from the environmenthelp in concerning the accuracy. These features of the proposed AFS make thealignment operation more efficient and are suitable especially for large-scaledata. The implementation and experimental results put the proposed AFS as afirst choice in the queue of alignment compared to the well-known algorithmsin multiple sequence alignment.展开更多
Soybean mosaic virus （SMV）, a member of the genus Potyvirus, is a major pathogen of soybean plants in China, and 16 SMV strains have been identified nationwide based on a former detailed SMV classification system. A...Soybean mosaic virus （SMV）, a member of the genus Potyvirus, is a major pathogen of soybean plants in China, and 16 SMV strains have been identified nationwide based on a former detailed SMV classification system. As the P3 gene is thought to be involved in viral replication, systemic infection, pathogenicity, and overcoming resistance, knowledge of the P3 gene sequences of SMV and other potyviruses would be useful in efforts to know the genetic relationships among them and control the disease. P3 gene sequences were obtained from representative isolates of the above-mentioned 16 SMV strains and were compared with other SMV strains and 16 Potyvirus species from the National Center for Biotechnology GenBank database. The P3 genes from the 16 SMV isolates are composed of 1041 nucleotides, encoding 347 amino acids, and share 90.7-100% nucleotide （NT） sequence identities and 95.1-100% amino acid （AA） sequence identities. The P3 coding regions of the 16 SMV isolates share high identities （92.4-98.9% NT and 96.0-100% AA） with the reported Korean isolates, followed by the USA isolates （88.5-97.9% NT and 91.4-98.6% AA）, and share low identities （80.5-85.2% NT and 82.1-84.7% AA） with the reported HZ 1 and P isolates from Pinellia ternata. The sequence identities of the P3 genes between SMV and the 16 potyviruses varied from 44.4 to 81.9% in the NT sequences and from 21.4 to 85.3% in the AA sequences, respectively. Among them, SMV was closely related to Watermelon mosaic virus （WMV）, with 76.0-81.9% NT and 77.5-85.3% AA identities. In addition, the SMV isolates and potyvirus species were clustered into six distinct groups. All the SMV strains isolated from soybean were clustered in Group I, and the remaining species were clustered in other groups. A multiple sequence alignment analysis of the C-terminal regions indicated that the P3 genes within a species were highly conserved, whereas those among species were relatively variable.展开更多
Multiple sequence alignments are successfully applied in many studies for understanding the structural and functional relations among single nucleic acids and protein sequences as well as whole families. Because of th...Multiple sequence alignments are successfully applied in many studies for understanding the structural and functional relations among single nucleic acids and protein sequences as well as whole families. Because of the rapid growth of sequence databases, multiple sequence alignments can often be very large and difficult to visualize and analyze. We offer a new service aimed to visualize and analyze the multiple alignments obtained with different external algorithms, with new features useful for the comparison of the aligned sequences as well as for the creation of a final image of the alignment. The service is named FASMA and is available at http： / /bioinformatica.isa.cnr.it /FASMA /.展开更多
There are many web-based multiple sequence alignment services accessible around the world. However, many researchers working on biological sequence analysis still struggle with inefficient, unfriendly user interface, ...There are many web-based multiple sequence alignment services accessible around the world. However, many researchers working on biological sequence analysis still struggle with inefficient, unfriendly user interface, and limited capability multiple sequence alignment software. In this study, we provide a comprehensive survey of regional and continental facilities that provide web-based alignment services. We also analyze and identify much needed services that are not available through these existing service providers. We then implement a web-based model to address these needs. From that perspective, our web-based multiple sequence alignment server, SeqAna, provides a unique set of services that none of these studied facilities have. For example, SeqAna provides a multiple sequence alignment scoring and ranking service. This service, the only of its kind, allows SeqAna＇s users to perform multiple sequence alignment with several alignment tools and rank the results of these alignments in the order of quality. With this service, SeqAna＇s users will be able to identify which alignment tools are more appropriate for their specific set of sequences. In addition, SeqAna＇s users can customize a small alignment sample as a reference for SeqAna to automatically identify the best tool to align their large set of sequences.展开更多
Although high quality multiple sequence alignment is an essential task in bioinforma- tics, it becomes a big dilemma nowadays due to the gigantic explosion in the amount of molecular data. The most consuming time and ...Although high quality multiple sequence alignment is an essential task in bioinforma- tics, it becomes a big dilemma nowadays due to the gigantic explosion in the amount of molecular data. The most consuming time and space phase is the distance matrix computation. This paper addresses this issue by proposing a vectorized parallel method that accomplishes the huge number of similarity comparisons faster in less space. Per- formance tests on real biological datasets using core-iT show superior results in terms of time and space.展开更多
文摘In this paper, we report a multiple sequence alignment result on the basis of 10 amino acid sequences of the M protein, which come from different coronaviruses (4 SARS associated and 6 others known). The alignment model was based on the profile HMM (Hidden Markov Model), and the model training was implemented through the SAHMM (Self Adapting Hidden Markov Model) software developed by the authors.
文摘In this letter, we briefly describe a program of self adapting hidden Markov model (SA HMM) and its application in multiple sequences alignment. Program consists of two stage optimisation algorithm.
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）.
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.
基金supported by the National Key R&D Program of China(2018YFA0903200)Science Technology and Innovation Commission of Shenzhen Municipality of China(ZDSYS 20200811142605017)It was also supported by Innovation Program of Chinese Academy of Agricultural Sciences and the Elite Young Scientists Program of CAAS.
文摘Creating a multi-gene alignment matrix for phylogenetic analysis using organelle genomes involves aligning single-gene datasets manually,a process that can be time-consuming and prone to errors.The HomBlocks pipeline has been created to eliminate the inaccuracies arising from manual operations.The processing of a large number of sequences,however,remains a time-consuming task.To conquer this challenge,we develop a speedy and efficient method called Organelle Genomes for Phylogenetic Analysis(ORPA).ORPA can quickly generate multiple sequence alignments for whole-genome comparisons by parsing the result files of NCBI BLAST,completing the task just in 1 min.With increasing data volume,the efficiency of ORPA is even more pronounced,over 300 times faster than HomBlocks in aligning 60 high-plant chloroplast genomes.The phylogenetic tree outputs from ORPA are equivalent to HomBlocks,indicating its outstanding efficiency.Due to its speed and accuracy,ORPA can identify species-level evolutionary conflicts,providing valuable insights into evolutionary cognition.
基金The authors extend their appreciation to the Deanship of Scientific Research at Jouf University for funding this work through research Grant No(DSR2020–01–414).
文摘The alignment operation between many protein sequences or DNAsequences related to the scientific bioinformatics application is very complex.There is a trade-off in the objectives in the existing techniques of MultipleSequence Alignment (MSA). The techniques that concern with speed ignoreaccuracy, whereas techniques that concern with accuracy ignore speed. Theterm alignment means to get the similarity in different sequences with highaccuracy. The more growing number of sequences leads to a very complexand complicated problem. Because of the emergence;rapid development;anddependence on gene sequencing, sequence alignment has become importantin every biological relationship analysis process. Calculating the numberof similar amino acids is the primary method for proving that there is arelationship between two sequences. The time is a main issue in any alignmenttechnique. In this paper, a more effective MSA method for handling themassive multiple protein sequences alignment maintaining the highest accuracy with less time consumption is proposed. The proposed method dependson Artificial Fish Swarm (AFS) algorithm that can break down the mostchallenges of MSA problems. The AFS is exploited to obtain high accuracyin adequate time. ASF has been increasing popularly in various applicationssuch as artificial intelligence, computer vision, machine learning, and dataintensive application. It basically mimics the behavior of fish trying to getthe food in nature. The proposed mechanisms of AFS that is like preying,swarming, following, moving, and leaping help in increasing the accuracy andconcerning the speed by decreasing execution time. The sense organs that aidthe artificial fishes to collect information and vision from the environmenthelp in concerning the accuracy. These features of the proposed AFS make thealignment operation more efficient and are suitable especially for large-scaledata. The implementation and experimental results put the proposed AFS as afirst choice in the queue of alignment compared to the well-known algorithmsin multiple sequence alignment.
基金supported by the National Natural Science Foundation of China(30671266,31101164)the National Basic Research Program of China(2006CB101708,2009CB118404)+2 种基金the National 863 Program of China(2006AA100104)the 111 Project from Ministry of Education of China(B08025)the Youth Science and Technology Innovation Foundation of Nanjing Agriculture University,China(KJ2010002)
文摘Soybean mosaic virus （SMV）, a member of the genus Potyvirus, is a major pathogen of soybean plants in China, and 16 SMV strains have been identified nationwide based on a former detailed SMV classification system. As the P3 gene is thought to be involved in viral replication, systemic infection, pathogenicity, and overcoming resistance, knowledge of the P3 gene sequences of SMV and other potyviruses would be useful in efforts to know the genetic relationships among them and control the disease. P3 gene sequences were obtained from representative isolates of the above-mentioned 16 SMV strains and were compared with other SMV strains and 16 Potyvirus species from the National Center for Biotechnology GenBank database. The P3 genes from the 16 SMV isolates are composed of 1041 nucleotides, encoding 347 amino acids, and share 90.7-100% nucleotide （NT） sequence identities and 95.1-100% amino acid （AA） sequence identities. The P3 coding regions of the 16 SMV isolates share high identities （92.4-98.9% NT and 96.0-100% AA） with the reported Korean isolates, followed by the USA isolates （88.5-97.9% NT and 91.4-98.6% AA）, and share low identities （80.5-85.2% NT and 82.1-84.7% AA） with the reported HZ 1 and P isolates from Pinellia ternata. The sequence identities of the P3 genes between SMV and the 16 potyviruses varied from 44.4 to 81.9% in the NT sequences and from 21.4 to 85.3% in the AA sequences, respectively. Among them, SMV was closely related to Watermelon mosaic virus （WMV）, with 76.0-81.9% NT and 77.5-85.3% AA identities. In addition, the SMV isolates and potyvirus species were clustered into six distinct groups. All the SMV strains isolated from soybean were clustered in Group I, and the remaining species were clustered in other groups. A multiple sequence alignment analysis of the C-terminal regions indicated that the P3 genes within a species were highly conserved, whereas those among species were relatively variable.
文摘Multiple sequence alignments are successfully applied in many studies for understanding the structural and functional relations among single nucleic acids and protein sequences as well as whole families. Because of the rapid growth of sequence databases, multiple sequence alignments can often be very large and difficult to visualize and analyze. We offer a new service aimed to visualize and analyze the multiple alignments obtained with different external algorithms, with new features useful for the comparison of the aligned sequences as well as for the creation of a final image of the alignment. The service is named FASMA and is available at http： / /bioinformatica.isa.cnr.it /FASMA /.
文摘There are many web-based multiple sequence alignment services accessible around the world. However, many researchers working on biological sequence analysis still struggle with inefficient, unfriendly user interface, and limited capability multiple sequence alignment software. In this study, we provide a comprehensive survey of regional and continental facilities that provide web-based alignment services. We also analyze and identify much needed services that are not available through these existing service providers. We then implement a web-based model to address these needs. From that perspective, our web-based multiple sequence alignment server, SeqAna, provides a unique set of services that none of these studied facilities have. For example, SeqAna provides a multiple sequence alignment scoring and ranking service. This service, the only of its kind, allows SeqAna＇s users to perform multiple sequence alignment with several alignment tools and rank the results of these alignments in the order of quality. With this service, SeqAna＇s users will be able to identify which alignment tools are more appropriate for their specific set of sequences. In addition, SeqAna＇s users can customize a small alignment sample as a reference for SeqAna to automatically identify the best tool to align their large set of sequences.
文摘Although high quality multiple sequence alignment is an essential task in bioinforma- tics, it becomes a big dilemma nowadays due to the gigantic explosion in the amount of molecular data. The most consuming time and space phase is the distance matrix computation. This paper addresses this issue by proposing a vectorized parallel method that accomplishes the huge number of similarity comparisons faster in less space. Per- formance tests on real biological datasets using core-iT show superior results in terms of time and space.
