Faculty Opinions recommendation of Generalized bootstrap supports for phylogenetic analyses of protein sequences incorporating alignment uncertainty.

To gain insight into the possible origins of the 2009 outbreak of new influenza A(H1N1), we performed two independent analyses of genetic evolution of the new influenza A(H1N1) virus. Firstly, protein homology analyses of more than 400 sequences revealed that this virus most likely evolved from recent swine viruses. Secondly, phylogenetic analyses of 5,214 protein sequences of influenza A(H1N1) viruses (avian, swine and human) circulating in North America for the last two decades (from 1989 to 2009) indicated that the new influenza A(H1N1) virus possesses a distinctive evolutionary trait (genetic distinctness). This appears to be a particular characteristic in pig-human interspecies transmission of influenza A. Thus these analyses contribute to the evidence of the role of pig populations as “mixing vessels” for influenza A(H1N1) viruses.

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SequenceBouncer: A method to remove outlier entries from a multiple sequence alignment

10.1101/2020.11.24.395459 ◽

2020 ◽

Author(s):

Cory D. Dunn

Keyword(s):

Nucleic Acid ◽

Sequence Alignment ◽

Multiple Sequence Alignment ◽

Phylogenetic Analyses ◽

Protein Sequences ◽

Mitochondrial Genomes ◽

Dna Barcodes ◽

Sequence Alignments ◽

Multiple Sequence ◽

Multiple Sequence Alignments

AbstractPhylogenetic analyses can take advantage of multiple sequence alignments as input. These alignments typically consist of homologous nucleic acid or protein sequences, and the inclusion of outlier or aberrant sequences can compromise downstream analyses. Here, I describe a program, SequenceBouncer, that uses the Shannon entropy values of alignment columns to identify outlier alignment sequences in a manner responsive to overall alignment context. I demonstrate the utility of this software using alignments of available mammalian mitochondrial genomes, bird cytochrome c oxidase-derived DNA barcodes, and COVID-19 sequences.

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A Bayesian Framework for Improving Clustering Accuracy of Protein Sequences Based on Association Rules

Advanced Data Mining Technologies in Bioinformatics ◽

10.4018/978-1-59140-863-5.ch012 ◽

2011 ◽

pp. 231-247

Author(s):

Peng-Yeng yin ◽

Shyong-Jian Shyu ◽

Guan-Shieng Huang ◽

Shuang-Te Liao

Keyword(s):

Data Mining ◽

Association Rules ◽

Phylogenetic Analyses ◽

Clustering Algorithms ◽

Protein Sequences ◽

Bayesian Framework ◽

Biological Data ◽

Data Mining Techniques ◽

Analysis Task ◽

Using Data

With the advent of new sequencing technology for biological data, the number of sequenced proteins stored in public databases has become an explosion. The structural, functional, and phylogenetic analyses of proteins would benefit from exploring databases by using data mining techniques. Clustering algorithms can assign proteins into clusters such that proteins in the same cluster are more similar in homology than those in different clusters. This procedure not only simplifies the analysis task but also enhances the accuracy of the results. Most of the existing protein-clustering algorithms compute the similarity between proteins based on one-to-one pairwise sequence

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A Bayesian Framework for Improving Clustering Accuracy of Protein Sequences Based on Association Rules

Intelligent Information Technologies ◽

10.4018/978-1-59904-941-0.ch025 ◽

2011 ◽

pp. 430-444

Author(s):

Peng-Yeng yin ◽

Shyong-Jian Shyu ◽

Guan-Shieng Huang ◽

Shuang-Te Liao

Keyword(s):

Data Mining ◽

Association Rules ◽

Phylogenetic Analyses ◽

Clustering Algorithms ◽

Protein Sequences ◽

Bayesian Framework ◽

Biological Data ◽

Data Mining Techniques ◽

Analysis Task ◽

Using Data

With the advent of new sequencing technology for biological data, the number of sequenced proteins stored in public databases has become an explosion. The structural, functional, and phylogenetic analyses of proteins would benefit from exploring databases by using data mining techniques. Clustering algorithms can assign proteins into clusters such that proteins in the same cluster are more similar in homology than those in different clusters. This procedure not only simplifies the analysis task but also enhances the accuracy of the results. Most of the existing protein-clustering algorithms compute the similarity between proteins based on one-to-one pairwise sequence

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A Bayesian Framework for Improving Clustering Accuracy of Protein Sequences Based on Association Rules

Medical Informatics ◽

10.4018/978-1-60566-050-9.ch171 ◽

2011 ◽

pp. 2259-2273

Author(s):

Peng-Yeng Yin ◽

Shyong-Jian Shyu ◽

Guan-Shieng Huang ◽

Shuang-Te Liao

Keyword(s):

Association Rules ◽

Ad Hoc ◽

Phylogenetic Analyses ◽

Clustering Algorithms ◽

Protein Sequences ◽

Bayesian Framework ◽

Clustering Methods ◽

Pairwise Sequence Alignment ◽

Local Optima ◽

Using Data

With the advent of new sequencing technology for biological data, the number of sequenced proteins stored in public databases has become an explosion. The structural, functional, and phylogenetic analyses of proteins would benefit from exploring databases by using data mining techniques. Clustering algorithms can assign proteins into clusters such that proteins in the same cluster are more similar in homology than those in different clusters. This procedure not only simplifies the analysis task but also enhances the accuracy of the results. Most of the existing protein-clustering algorithms compute the similarity between proteins based on one-to-one pairwise sequence alignment instead of multiple sequences alignment; the latter is prohibited due to expensive computation. Hence the accuracy of the clustering result is deteriorated. Further, the traditional clustering methods are ad-hoc and the resulting clustering often converges to local optima. This chapter presents a Bayesian framework for improving clustering accuracy of protein sequences based on association rules. The experimental results manifest that the proposed framework can significantly improve the performance of traditional clustering methods.

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A Bayesian Framework for Improving Clustering Accuracy of Protein Sequences Based on Association Rules

Data Warehousing and Mining ◽

10.4018/978-1-59904-951-9.ch062 ◽

2008 ◽

pp. 1091-1102

Author(s):

Peng-Yeng Yin ◽

Shyong-Jian Shyu ◽

Guan-Shieng Huang ◽

Shuang-Te Liao

Keyword(s):

Data Mining ◽

Association Rules ◽

Phylogenetic Analyses ◽

Clustering Algorithms ◽

Protein Sequences ◽

Bayesian Framework ◽

Biological Data ◽

Data Mining Techniques ◽

Analysis Task ◽

Using Data

With the advent of new sequencing technology for biological data, the number of sequenced proteins stored in public databases has become an explosion. The structural, functional, and phylogenetic analyses of proteins would benefit from exploring databases by using data mining techniques. Clustering algorithms can assign proteins into clusters such that proteins in the same cluster are more similar in homology than those in different clusters. This procedure not only simplifies the analysis task but also enhances the accuracy of the results. Most of the existing protein-clustering algorithms compute the similarity between proteins based on one-to-one pairwise sequence

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Comparative and phylogenetic analysis of RuBisCO large subunit (rbcL) proteins in some Sideritis L. (Lamiaceae) species: A bioinformatic approach

Genetika ◽

10.2298/gensr1901069s ◽

2019 ◽

Vol 51 (1) ◽

pp. 69-80

Author(s):

Emre Sevindik

Keyword(s):

Amino Acid ◽

Phylogenetic Analyses ◽

Large Subunit ◽

Protein Structures ◽

Three Dimensional ◽

Protein Sequences ◽

Stilbene Synthase ◽

Acid Number ◽

Pairwise Distance ◽

Bisphosphate Carboxylase

The large subunits of ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) protein, which plays an important role in the photosynthesis reaction, are encoded by the chloroplast genome. Sideritis L., a medical and aromatic plant group, belongs to Lamiaceae family. In this study, we performed sequence, physicochemical, phylogenetic and three-dimensional (3D) bioinformatic analyses of RuBisCO large subunit (rbcL) proteins in the Sideritis ssp. using various bioinformatics tools. Physicochemical analyzes were performed by ExPASy - ProtParam. The putative phosphorylation sites of the rbcL proteins were determined by NetPhos 2.0 and NetPhos 3.1. Phylogenetic analyses were performed with the MEGA 6.0 software. To estimate 3D protein structures, PyMol program was used. At the end of the study, it was found that the amino acid number of stilbene synthase proteins ranged between 171 and 456, molecular weight ranged between 19002.67 and 50420.44 Da, instability index ranged between 27.30 to 40.70 and GRAVY values ranged between -0.394 to -0.226. While the highest average amino acid rate in the rbcL proteins was Gly (10.00%), the lowest amino acid ratio (1.4%) was determined as Trp. In phylogenetic analyses performed using protein sequences, maximum likelihood (ML) tree consisted of 2 large clades. Pairwise distance analysis based on Sideritis species? rbcL protein sequences was performed using MEGA 6.0. The lowest pairwise distance was 0.000, while the highest pairwise distance was 0.024. When the estimated 3D structures of the proteins were examined, the Gly residue, which plays an important role in the structure and function of the proteins, was detected as the least in S. libanotica subsp. kurdica species while it was the most abundant residue in S. cretica subsp. spicata. The results of our study provide insights into fundamental characteristics of rbcL proteins in Sideritis taxa.

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Phylogenetic Analysis of Polyketide Synthase I Domains from Soil Metagenomic Libraries Allows Selection of Promising Clones

Applied and Environmental Microbiology ◽

10.1128/aem.70.9.5522-5527.2004 ◽

2004 ◽

Vol 70 (9) ◽

pp. 5522-5527 ◽

Cited By ~ 89

Author(s):

Aurélien Ginolhac ◽

Cyrille Jarrin ◽

Benjamin Gillet ◽

Patrick Robe ◽

Petar Pujic ◽

...

Keyword(s):

Polyketide Synthase ◽

Selection Process ◽

Phylogenetic Analyses ◽

Metagenomic Library ◽

Protein Sequences ◽

Direct Access ◽

Type I ◽

Ketosynthase Domain ◽

New Compounds ◽

Uncultivated Bacteria

ABSTRACT The metagenomic approach provides direct access to diverse unexplored genomes, especially from uncultivated bacteria in a given environment. This diversity can conceal many new biosynthetic pathways. Type I polyketide synthases (PKSI) are modular enzymes involved in the biosynthesis of many natural products of industrial interest. Among the PKSI domains, the ketosynthase domain (KS) was used to screen a large soil metagenomic library containing more than 100,000 clones to detect those containing PKS genes. Over 60,000 clones were screened, and 139 clones containing KS domains were detected. A 700-bp fragment of the KS domain was sequenced for 40 of 139 randomly chosen clones. None of the 40 protein sequences were identical to those found in public databases, and nucleic sequences were not redundant. Phylogenetic analyses were performed on the protein sequences of three metagenomic clones to select the clones which one can predict to produce new compounds. Two PKS-positive clones do not belong to any of the 23 published PKSI included in the analysis, encouraging further analyses on these two clones identified by the selection process.

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Ellipsomyxa ariusi sp. nov. (Myxosporea: Ceratomyxidae), a new myxosporean infecting the gallbladder of threadfin sea catfish Arius arius in India

Diseases of Aquatic Organisms ◽

10.3354/dao03529 ◽

2020 ◽

Vol 142 ◽

pp. 83-97

Author(s):

A Chandran ◽

PU Zacharia ◽

TV Sathianandan ◽

NK Sanil

Keyword(s):

Phylogenetic Analyses ◽

Type Specimen ◽

Ssu Rdna ◽

Fish Host ◽

Present Species ◽

Epithelial Layer ◽

Histopathological Changes ◽

Mucus Production ◽

High Bootstrap ◽

A New Species

The present study describes a new species of myxosporean, Ellipsomyxa ariusi sp. nov., infecting the gallbladder of the threadfin sea catfish Arius arius (Hamilton, 1822). E. ariusi sp. nov. is characterized by bivalvular, ellipsoid or elongate-oval myxospores with smooth spore valves and a straight suture, arranged at an angle to the longitudinal spore axis. Mature myxospores measured 10.1 ± 0.8 µm in length, 6.8 ± 0.5 µm in width and 7.7 ± 0.7 µm in thickness. Polar capsules are equal in size and oval to pyriform in shape. They are positioned at an angle to the longitudinal myxospore axis and open in opposite directions. Polar capsules measured 2.8 ± 0.3 µm in length and 2.5 ± 0.4 µm in width; polar filaments formed 4-5 coils, and extended to 32.2 ± 2.1 µm in length. Monosporic and disporic plasmodial stages attached to the wall of gallbladder. Molecular analysis of the type specimen generated a 1703 bp partial SSU rDNA sequence (MN892546), which was identical to the isolates from 3 other locations. In phylogenetic analyses, genus Ellipsomyxa appeared monophyletic and E. ariusi sp. nov. occupied an independent position in maximum likelihood and Bayesian inference trees with high bootstrap values. The overall prevalence of infection was 54.8% and multiway ANOVA revealed that it varied significantly with location, year, season, sex and size of the fish host. Histopathological changes associated with E. ariusi sp. nov. infection included swelling, vacuolation and detachment of epithelial layer, reduced mucus production and altered consistency and colour of bile. Based on the morphologic, morphometric and molecular differences with known species of Ellipsomyxa, and considering differences in host and geographic locations, the present species is treated as new and the name Ellipsomyxa ariusi sp. nov. is proposed.

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