This document summarizes the creation of a database of group I intron secondary structures derived from comparative sequence analysis. Over 200 publicly available group I intron sequences were analyzed to infer their secondary structures. The database aims to collect and refine group I intron structures as more sequences become available. It will make the secondary structure diagrams accessible online through file transfer protocol and the World Wide Web. The database currently contains 219 intron sequences classified into subgroups based on their phylogenetic diversity and cellular location.
This document summarizes a compilation of large subunit (23S and 23S-like) ribosomal RNA secondary structures from a diverse set of organisms, including archaea, bacteria, plastids, and mitochondria. It provides tables tracking the growth of sequenced large subunit rRNAs over time. It describes the process of determining secondary and higher-order structures through comparative analysis. The structures are made available both as hard copies and online via FTP. The document requests feedback to improve the accuracy and coverage of the compiled structures.
This document discusses constructing phylogenetic trees to analyze the evolutionary relationships between bacteria, archaea, and eukarya based on nuclear, membrane, and metabolic genes. 18 organisms were selected from each domain and their 16S rRNA, 18S rRNA, and gene sequences were obtained from databases. Multiple sequence alignments were performed and phylogenetic trees were constructed to compare the relationships depicted in the gene trees to the standard rRNA tree of life.
1. DNA contains the genetic code and is made up of nucleotides with a sugar, phosphate, and one of four nitrogen bases.
2. RNA is synthesized from DNA in a process called transcription and comes in three types - mRNA, tRNA, and rRNA.
3. Protein synthesis occurs on ribosomes using mRNA as a template to link amino acids specified by tRNA, forming a polypeptide chain.
This document provides information about killer whales in 3 or less sentences:
Killer whales, also known as orcas, are large black and white dolphins that feed on seals, fish, penguins and other whales. They live in Antarctic, Arctic and polar waters, and males can grow up to 23 feet and females up to 21 feet. The document contains additional facts about their diet, habitat, lifespan, social structure, intelligence and predatory role.
The document summarizes research on sequencing part of the ribosomal RNA coding region and determining the secondary structure of the 25S rRNA of Candida albicans. Key findings include:
- A rDNA cistron from C. albicans strain WO-1 was cloned and sequencing revealed the ITS1, ITS2, 5.8S rDNA and 25S rDNA coding regions.
- The C. albicans ITS regions are shorter than those of most other eukaryotes.
- The 5.8S and 25S rDNA sequences were used to model the secondary structure, which was compared to other species.
- Variable regions in the 25S r
Este documento fornece informações sobre o Fundo de Investimento em Direitos Creditórios Policard II, incluindo seu objetivo de proporcionar rendimento de longo prazo aos cotistas através de investimentos em direitos creditórios da Policard, seus detalhes de valor mínimo, prazo, rentabilidade, taxas e riscos envolvidos.
This document summarizes a collection of secondary structure diagrams of small subunit ribosomal RNAs (16S and 16S-like rRNAs) from Archaea, Bacteria, and Eukaryotic organelles. It provides the objectives of making the structures available online through a WWW server and FTP for viewing and downloading. Representative structures were selected to be phylogenetically and structurally diverse, including examples from Archaea, Bacteria, Eukaryotes, mitochondria and chloroplasts.
This document analyzes spliceosomal introns in ribosomal RNA genes of fungi. The key findings are:
1) Analysis of 49 intron insertion sites in fungal rRNA genes found that the conserved flanking sequence is G-intron-G, suggesting this is the proto-splice site where introns are inserted.
2) The exon sequences flanking the introns contain statistically significant information content, indicating the presence of potential regulatory elements.
3) Spliceosomal introns in fungal rRNA genes tend to occur in less conserved regions of the rRNA, whereas group I introns occur in more functionally important, conserved regions.
This document summarizes a compilation of large subunit (23S and 23S-like) ribosomal RNA secondary structures from a diverse set of organisms, including archaea, bacteria, plastids, and mitochondria. It provides tables tracking the growth of sequenced large subunit rRNAs over time. It describes the process of determining secondary and higher-order structures through comparative analysis. The structures are made available both as hard copies and online via FTP. The document requests feedback to improve the accuracy and coverage of the compiled structures.
This document discusses constructing phylogenetic trees to analyze the evolutionary relationships between bacteria, archaea, and eukarya based on nuclear, membrane, and metabolic genes. 18 organisms were selected from each domain and their 16S rRNA, 18S rRNA, and gene sequences were obtained from databases. Multiple sequence alignments were performed and phylogenetic trees were constructed to compare the relationships depicted in the gene trees to the standard rRNA tree of life.
1. DNA contains the genetic code and is made up of nucleotides with a sugar, phosphate, and one of four nitrogen bases.
2. RNA is synthesized from DNA in a process called transcription and comes in three types - mRNA, tRNA, and rRNA.
3. Protein synthesis occurs on ribosomes using mRNA as a template to link amino acids specified by tRNA, forming a polypeptide chain.
This document provides information about killer whales in 3 or less sentences:
Killer whales, also known as orcas, are large black and white dolphins that feed on seals, fish, penguins and other whales. They live in Antarctic, Arctic and polar waters, and males can grow up to 23 feet and females up to 21 feet. The document contains additional facts about their diet, habitat, lifespan, social structure, intelligence and predatory role.
The document summarizes research on sequencing part of the ribosomal RNA coding region and determining the secondary structure of the 25S rRNA of Candida albicans. Key findings include:
- A rDNA cistron from C. albicans strain WO-1 was cloned and sequencing revealed the ITS1, ITS2, 5.8S rDNA and 25S rDNA coding regions.
- The C. albicans ITS regions are shorter than those of most other eukaryotes.
- The 5.8S and 25S rDNA sequences were used to model the secondary structure, which was compared to other species.
- Variable regions in the 25S r
Este documento fornece informações sobre o Fundo de Investimento em Direitos Creditórios Policard II, incluindo seu objetivo de proporcionar rendimento de longo prazo aos cotistas através de investimentos em direitos creditórios da Policard, seus detalhes de valor mínimo, prazo, rentabilidade, taxas e riscos envolvidos.
This document summarizes a collection of secondary structure diagrams of small subunit ribosomal RNAs (16S and 16S-like rRNAs) from Archaea, Bacteria, and Eukaryotic organelles. It provides the objectives of making the structures available online through a WWW server and FTP for viewing and downloading. Representative structures were selected to be phylogenetically and structurally diverse, including examples from Archaea, Bacteria, Eukaryotes, mitochondria and chloroplasts.
This document analyzes spliceosomal introns in ribosomal RNA genes of fungi. The key findings are:
1) Analysis of 49 intron insertion sites in fungal rRNA genes found that the conserved flanking sequence is G-intron-G, suggesting this is the proto-splice site where introns are inserted.
2) The exon sequences flanking the introns contain statistically significant information content, indicating the presence of potential regulatory elements.
3) Spliceosomal introns in fungal rRNA genes tend to occur in less conserved regions of the rRNA, whereas group I introns occur in more functionally important, conserved regions.
This document provides secondary structure diagrams for large subunit ribosomal RNA sequences from a variety of organisms. It summarizes 40 complete rRNA sequences and 5 partial sequences published as of 1987. The diagrams are presented in a standardized format based on Escherichia coli rRNA secondary structure. Many regions of unknown structure are indicated. The structures were determined using comparative sequence analysis to identify compensating base changes maintaining Watson-Crick base pairing across evolutionary distances. Limitations of this approach include requiring sequences that contain the structural feature and sufficient sequence variation within those sequences to determine the structure.
This research article discusses the lateral transfer of group I introns between red and brown algae. The researchers found that a group I intron inserted at position 516 in the small subunit rRNA contained a unique helical insertion in the P5b helix in both bangiophyte red algae and the brown alga Aureoumbra lagunensis, though the host cells are evolutionarily distant. They analyzed the secondary structure and phylogeny of these introns to understand their origin. The highly conserved structure of the insertion suggests it is important functionally, though its specific role is unknown. Their analyses support the scenario that the intron was laterally transferred between red and brown algae after their divergence, rather than being present in
This document summarizes a compilation of large subunit (23S-like) ribosomal RNA sequences presented in a secondary structure format. It includes 71 rRNA sequences from archaebacteria, eubacteria, eukaryotic organelles (plastids and mitochondria), and eukaryotic cytoplasm. The compilation is intended to facilitate comparison of homologous structural features among different rRNA sequences by configuring them according to the E. coli 23S rRNA model structure. The sequences were grouped by phylogenetic domain and references for each sequence were provided. Access to the secondary structure figures was described as available either through hard copy or online files.
This document summarizes the 1993 compilation of large subunit (23S and 23S-like) ribosomal RNA structures. It provides an overview of the growth of the database, which saw the largest annual increase in sequences that year. It also describes models of higher-order structure for bacterial, yeast, and nematode mitochondrial rRNA. The accuracy of the data and availability of the structure figures are discussed.
This document summarizes the Comparative RNA Web (CRW) Site, an online database that provides comparative sequence and structure information for ribosomal RNAs, transfer RNA, and other RNAs. The CRW Site contains:
1) Current comparative structure models for rRNA and other RNAs derived from extensive sequence analysis and alignment.
2) Nucleotide frequency and conservation data mapped onto phylogenetic trees to show variation and conservation across organisms.
3) A collection of RNA sequences and secondary structure models from diverse organisms.
4) Tools for accessing and searching the database of RNA sequences, structures, and associated metadata.
This document discusses the collection and analysis of small subunit ribosomal RNA structures, specifically 16S and 16S-like rRNA. It provides background on how comparative methods have been used to infer the secondary and tertiary structures of rRNA molecules. It then summarizes the evolution of 16S rRNA secondary structure models, from early minimal structures to current models incorporating tertiary interactions. The objectives of the annual structure collection are outlined, including presenting updated E. coli 16S rRNA structure, additional tertiary interactions, and a sampling of structures from diverse phylogenetic domains. Examples of higher-order structure diagrams are provided for E. coli, yeast, and C. elegans rRNA.
1. Molecular phylogenetic analysis uses DNA, RNA, or protein sequences to reconstruct evolutionary relationships between organisms. The extent of differences between homologous sequences is used to measure divergence.
2. Key steps include deciding sequences to examine, determining sequences experimentally, aligning sequences to identify homologous residues, and comparing sequences to determine relationships and construct phylogenetic trees.
3. The 16S rRNA gene is often used because it is universally present and conserved enough to align while also containing rapidly and slowly evolving regions useful for relationships at different timescales.
Protein databases can contain either sequence or structure information. Some key protein sequence databases include PIR, Swiss-Prot, and TrEMBL. PIR classifies entries by annotation level, Swiss-Prot aims to provide high annotation levels and interlink information, and TrEMBL contains all coding sequences with some entries eventually incorporated into Swiss-Prot. Important structure databases are PDB, which contains 3D protein structures, and SCOP and CATH, which classify evolutionary and structural relationships between protein domains.
Austin Journal of Computational Biology and Bioinformatics is an open access, peer reviewed, scholarly journal dedicated to publish articles in all areas of research in Computational Biology and Bioinformatics.
The journal aims to promote research communications and provide a forum for researchers and other healthcare professionals to find most recent advances in the areas of Computational Biology and Bioinformatics.
Austin Journal of Computational Biology and Bioinformatics accepts original research articles, review articles, case reports and rapid communication on all the aspects of Computational Biology and Bioinformatics.
This document summarizes a seminal 1953 paper by James Watson and Francis Crick describing their discovery of the double helix structure of DNA. The paper proposes that DNA consists of two intertwined strands coiled around the same axis, with the bases on the inside of the helix paired together through hydrogen bonds in a specific way such that adenine pairs with thymine and guanine pairs with cytosine. This pairing allows each strand to act as a template for the other, providing a mechanism for copying genetic information.
Apollo is a web-based application that supports and enables collaborative genome curation in real time, allowing teams of curators to improve on existing automated gene models through an intuitive interface. Apollo allows researchers to break down large amounts of data into manageable portions to mobilize groups of researchers with shared interests.
This document summarizes evidence from comparative analysis of ribosomal RNA sequences that suggests two new higher order structural interactions in 16S ribosomal RNA:
1) A double helical structure involving positions 505-507 and 524-526, supported by examples of co-variation between these positions in various organisms. This represents a pseudoknot structure.
2) An interaction between the region around position 130 and the helix located between positions 180-195. In many bacteria, an insertion of a nucleotide near position 130 correlates with the helix in the 180-195 region being lengthened from 3 base pairs to around 10 base pairs.
The document provides detailed evidence for these proposed higher order structures from comparative analysis of rRNA
RNase contamination was preventing accurate measurement of RNA-protein binding between LARP6 and its RNA substrate. The researchers optimized native polyacrylamide gel electrophoresis with biotinylated RNA to visualize and quantify binding. They showed biotinylation worked without detecting RNase contamination. Continued gel condition optimization will improve resolution for determining the functional boundaries of the LARP6 La Module domain required for RNA binding.
Lee C.-Y., Lee J.C., and Gutell R.R. (2007).
Networks of interactions in the secondary and tertiary structure of ribosomal RNA.
Physica A, 386(1):564-572.
Amino acid interaction network prediction using multi objective optimizationcsandit
This summary provides an overview of the document in 3 sentences:
The document proposes a multi-objective evolutionary algorithm to predict amino acid interaction networks using genetic algorithms and ant colony optimization. It describes representing a protein as a network of amino acids and using multi-objective optimization to predict the secondary structure element interaction network, representing interactions as a graph. The algorithm then uses ant colony optimization to predict interactions between amino acids within and between predicted secondary structure networks.
Phylogeny-driven approaches to microbial & microbiome studies: talk by Jonath...Jonathan Eisen
This document summarizes an automated phylogenetic tree-based small subunit rRNA taxonomy and alignment pipeline (STAP) developed by the authors. STAP generates high-quality multiple sequence alignments and phylogenetic trees from rRNA gene sequences in a fully automated manner, allowing for phylogenetic analysis of large datasets. It combines existing tools like BLAST, CLUSTALW and PHYML with new programs for automated alignment, masking, and tree parsing. STAP yields results comparable to manual analysis but with increased speed and capacity needed to analyze the large volumes of rRNA data now being generated.
AMINO ACID INTERACTION NETWORK PREDICTION USING MULTI-OBJECTIVE OPTIMIZATIONcscpconf
The document describes a multi-objective optimization algorithm for predicting amino acid interaction networks. It uses genetic algorithms and ant colony optimization to first predict the network of interactions between amino acids in secondary structural elements, and then predict interactions between all amino acids. The genetic algorithm uses a multi-objective approach considering distance, torsion angles, and hydrophobicity to evolve an accurate interaction network. The ant colony algorithm then confirms the predicted interactions.
This document provides information about protein synthesis and the role of genes in controlling cellular activities. It discusses how DNA contains instructions in genes that are used to produce mRNA through transcription. The mRNA then directs protein synthesis through translation with the help of tRNA. Proteins fold into complex 3D structures determined by amino acid sequences that allow them to perform specific functions. Issues can arise if errors occur during protein production.
Secondary structure of rna and its predicting elementsVinaKhan1
This document discusses the secondary structure of RNA and methods for predicting its structure. It begins by describing the primary, secondary, and tertiary structures of RNA. The importance of predicting RNA secondary structure is that it allows structure prediction for sequences without experimental data. Common secondary structure elements include stem loops, bulge loops, interior loops, junctions, and pseudoknots. Prediction methods include base pair maximization and free energy minimization, with the most common being free energy minimization using software like MFOLD.
This document summarizes Carl Woese's contributions to science, particularly his discovery of the third domain of life (Archaea) through analysis of rRNA sequences. It describes how his work established the use of comparative analysis to determine rRNA secondary structure and identify structural motifs. It highlights that he envisioned comparative analysis providing details about RNA structure and energetics. The summary discusses Woese's seminal concepts regarding the need for a universal phylogenetic framework and how analysis of rRNA satisfied criteria to reconstruct evolutionary relationships across all life.
Gutell 123.app environ micro_2013_79_1803Robin Gutell
This document summarizes a study examining the host specificity of Lactobacillus bacteria associated with different hymenopteran (bee and ant) hosts. The researchers compiled nearly full-length 16S rRNA gene sequences of Lactobacillus from public databases and used these to construct phylogenetic trees. They also included shorter 16S sequences from surveys of bacteria associated with sweat bees, fungus-growing ants, and fire ants. The results showed that lactobacilli associated with honey bees and bumble bees are highly host specific, while sweat bees and ants associate with lactobacilli more closely related to those found in diverse environments or vertebrate hosts. The high host specificity seen in corbiculate bees (honey bees
This document provides secondary structure diagrams for large subunit ribosomal RNA sequences from a variety of organisms. It summarizes 40 complete rRNA sequences and 5 partial sequences published as of 1987. The diagrams are presented in a standardized format based on Escherichia coli rRNA secondary structure. Many regions of unknown structure are indicated. The structures were determined using comparative sequence analysis to identify compensating base changes maintaining Watson-Crick base pairing across evolutionary distances. Limitations of this approach include requiring sequences that contain the structural feature and sufficient sequence variation within those sequences to determine the structure.
This research article discusses the lateral transfer of group I introns between red and brown algae. The researchers found that a group I intron inserted at position 516 in the small subunit rRNA contained a unique helical insertion in the P5b helix in both bangiophyte red algae and the brown alga Aureoumbra lagunensis, though the host cells are evolutionarily distant. They analyzed the secondary structure and phylogeny of these introns to understand their origin. The highly conserved structure of the insertion suggests it is important functionally, though its specific role is unknown. Their analyses support the scenario that the intron was laterally transferred between red and brown algae after their divergence, rather than being present in
This document summarizes a compilation of large subunit (23S-like) ribosomal RNA sequences presented in a secondary structure format. It includes 71 rRNA sequences from archaebacteria, eubacteria, eukaryotic organelles (plastids and mitochondria), and eukaryotic cytoplasm. The compilation is intended to facilitate comparison of homologous structural features among different rRNA sequences by configuring them according to the E. coli 23S rRNA model structure. The sequences were grouped by phylogenetic domain and references for each sequence were provided. Access to the secondary structure figures was described as available either through hard copy or online files.
This document summarizes the 1993 compilation of large subunit (23S and 23S-like) ribosomal RNA structures. It provides an overview of the growth of the database, which saw the largest annual increase in sequences that year. It also describes models of higher-order structure for bacterial, yeast, and nematode mitochondrial rRNA. The accuracy of the data and availability of the structure figures are discussed.
This document summarizes the Comparative RNA Web (CRW) Site, an online database that provides comparative sequence and structure information for ribosomal RNAs, transfer RNA, and other RNAs. The CRW Site contains:
1) Current comparative structure models for rRNA and other RNAs derived from extensive sequence analysis and alignment.
2) Nucleotide frequency and conservation data mapped onto phylogenetic trees to show variation and conservation across organisms.
3) A collection of RNA sequences and secondary structure models from diverse organisms.
4) Tools for accessing and searching the database of RNA sequences, structures, and associated metadata.
This document discusses the collection and analysis of small subunit ribosomal RNA structures, specifically 16S and 16S-like rRNA. It provides background on how comparative methods have been used to infer the secondary and tertiary structures of rRNA molecules. It then summarizes the evolution of 16S rRNA secondary structure models, from early minimal structures to current models incorporating tertiary interactions. The objectives of the annual structure collection are outlined, including presenting updated E. coli 16S rRNA structure, additional tertiary interactions, and a sampling of structures from diverse phylogenetic domains. Examples of higher-order structure diagrams are provided for E. coli, yeast, and C. elegans rRNA.
1. Molecular phylogenetic analysis uses DNA, RNA, or protein sequences to reconstruct evolutionary relationships between organisms. The extent of differences between homologous sequences is used to measure divergence.
2. Key steps include deciding sequences to examine, determining sequences experimentally, aligning sequences to identify homologous residues, and comparing sequences to determine relationships and construct phylogenetic trees.
3. The 16S rRNA gene is often used because it is universally present and conserved enough to align while also containing rapidly and slowly evolving regions useful for relationships at different timescales.
Protein databases can contain either sequence or structure information. Some key protein sequence databases include PIR, Swiss-Prot, and TrEMBL. PIR classifies entries by annotation level, Swiss-Prot aims to provide high annotation levels and interlink information, and TrEMBL contains all coding sequences with some entries eventually incorporated into Swiss-Prot. Important structure databases are PDB, which contains 3D protein structures, and SCOP and CATH, which classify evolutionary and structural relationships between protein domains.
Austin Journal of Computational Biology and Bioinformatics is an open access, peer reviewed, scholarly journal dedicated to publish articles in all areas of research in Computational Biology and Bioinformatics.
The journal aims to promote research communications and provide a forum for researchers and other healthcare professionals to find most recent advances in the areas of Computational Biology and Bioinformatics.
Austin Journal of Computational Biology and Bioinformatics accepts original research articles, review articles, case reports and rapid communication on all the aspects of Computational Biology and Bioinformatics.
This document summarizes a seminal 1953 paper by James Watson and Francis Crick describing their discovery of the double helix structure of DNA. The paper proposes that DNA consists of two intertwined strands coiled around the same axis, with the bases on the inside of the helix paired together through hydrogen bonds in a specific way such that adenine pairs with thymine and guanine pairs with cytosine. This pairing allows each strand to act as a template for the other, providing a mechanism for copying genetic information.
Apollo is a web-based application that supports and enables collaborative genome curation in real time, allowing teams of curators to improve on existing automated gene models through an intuitive interface. Apollo allows researchers to break down large amounts of data into manageable portions to mobilize groups of researchers with shared interests.
This document summarizes evidence from comparative analysis of ribosomal RNA sequences that suggests two new higher order structural interactions in 16S ribosomal RNA:
1) A double helical structure involving positions 505-507 and 524-526, supported by examples of co-variation between these positions in various organisms. This represents a pseudoknot structure.
2) An interaction between the region around position 130 and the helix located between positions 180-195. In many bacteria, an insertion of a nucleotide near position 130 correlates with the helix in the 180-195 region being lengthened from 3 base pairs to around 10 base pairs.
The document provides detailed evidence for these proposed higher order structures from comparative analysis of rRNA
RNase contamination was preventing accurate measurement of RNA-protein binding between LARP6 and its RNA substrate. The researchers optimized native polyacrylamide gel electrophoresis with biotinylated RNA to visualize and quantify binding. They showed biotinylation worked without detecting RNase contamination. Continued gel condition optimization will improve resolution for determining the functional boundaries of the LARP6 La Module domain required for RNA binding.
Lee C.-Y., Lee J.C., and Gutell R.R. (2007).
Networks of interactions in the secondary and tertiary structure of ribosomal RNA.
Physica A, 386(1):564-572.
Amino acid interaction network prediction using multi objective optimizationcsandit
This summary provides an overview of the document in 3 sentences:
The document proposes a multi-objective evolutionary algorithm to predict amino acid interaction networks using genetic algorithms and ant colony optimization. It describes representing a protein as a network of amino acids and using multi-objective optimization to predict the secondary structure element interaction network, representing interactions as a graph. The algorithm then uses ant colony optimization to predict interactions between amino acids within and between predicted secondary structure networks.
Phylogeny-driven approaches to microbial & microbiome studies: talk by Jonath...Jonathan Eisen
This document summarizes an automated phylogenetic tree-based small subunit rRNA taxonomy and alignment pipeline (STAP) developed by the authors. STAP generates high-quality multiple sequence alignments and phylogenetic trees from rRNA gene sequences in a fully automated manner, allowing for phylogenetic analysis of large datasets. It combines existing tools like BLAST, CLUSTALW and PHYML with new programs for automated alignment, masking, and tree parsing. STAP yields results comparable to manual analysis but with increased speed and capacity needed to analyze the large volumes of rRNA data now being generated.
AMINO ACID INTERACTION NETWORK PREDICTION USING MULTI-OBJECTIVE OPTIMIZATIONcscpconf
The document describes a multi-objective optimization algorithm for predicting amino acid interaction networks. It uses genetic algorithms and ant colony optimization to first predict the network of interactions between amino acids in secondary structural elements, and then predict interactions between all amino acids. The genetic algorithm uses a multi-objective approach considering distance, torsion angles, and hydrophobicity to evolve an accurate interaction network. The ant colony algorithm then confirms the predicted interactions.
This document provides information about protein synthesis and the role of genes in controlling cellular activities. It discusses how DNA contains instructions in genes that are used to produce mRNA through transcription. The mRNA then directs protein synthesis through translation with the help of tRNA. Proteins fold into complex 3D structures determined by amino acid sequences that allow them to perform specific functions. Issues can arise if errors occur during protein production.
Secondary structure of rna and its predicting elementsVinaKhan1
This document discusses the secondary structure of RNA and methods for predicting its structure. It begins by describing the primary, secondary, and tertiary structures of RNA. The importance of predicting RNA secondary structure is that it allows structure prediction for sequences without experimental data. Common secondary structure elements include stem loops, bulge loops, interior loops, junctions, and pseudoknots. Prediction methods include base pair maximization and free energy minimization, with the most common being free energy minimization using software like MFOLD.
This document summarizes Carl Woese's contributions to science, particularly his discovery of the third domain of life (Archaea) through analysis of rRNA sequences. It describes how his work established the use of comparative analysis to determine rRNA secondary structure and identify structural motifs. It highlights that he envisioned comparative analysis providing details about RNA structure and energetics. The summary discusses Woese's seminal concepts regarding the need for a universal phylogenetic framework and how analysis of rRNA satisfied criteria to reconstruct evolutionary relationships across all life.
Gutell 123.app environ micro_2013_79_1803Robin Gutell
This document summarizes a study examining the host specificity of Lactobacillus bacteria associated with different hymenopteran (bee and ant) hosts. The researchers compiled nearly full-length 16S rRNA gene sequences of Lactobacillus from public databases and used these to construct phylogenetic trees. They also included shorter 16S sequences from surveys of bacteria associated with sweat bees, fungus-growing ants, and fire ants. The results showed that lactobacilli associated with honey bees and bumble bees are highly host specific, while sweat bees and ants associate with lactobacilli more closely related to those found in diverse environments or vertebrate hosts. The high host specificity seen in corbiculate bees (honey bees
Gutell R.R. (2013).
Comparative Analysis of the Higher-Order Structure of RNA.
in: Biophysics of RNA Folding. Volume editor: Rick Russell. Series title: Biophysics for the Life Sciences. Series editors: Norma Allewell, Ivan Rayment, Bertrand Garcia-Moreno, Jonathan Dinman, and Michael McCarthy. pp. 11-22. Publisher: Springer, New York, NY.
Gardner D.P., Xu W., Miranker D.P., Ozer S., Cannone J.J., and Gutell R.R. (2012).
An Accurate Scalable Template-based Alignment Algorithm.
Proceedings of 2012 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2012), Philadelphia, PA. October 4-7, 2012. IEEE Computer Society, Washington, DC, USA. pp. 237-243.
Lee J.C. and Gutell R.R. (2012).
A Comparison of the Crystal Structures of the Eukaryotic and Bacterial SSU Ribosomal RNAs Reveals Common Structural Features in the Hypervariable Regions.
PLoS ONE, 7(5):e38203.
Gardner D.P., Ren P., Ozer S., and Gutell R.R. (2011).
Statistical Potentials for Hairpin and Internal Loops Improve the Accuracy of the Predicted RNA Structure.
Journal of Molecular Biology, 413(2):473-483.2011. pp 15-22.
Ozer S., Doshi K.J., Xu W., and Gutell R.R. (2011).
rCAD: A Novel Database Schema for the Comparative Analysis of RNA.
7th IEEE International Conference on e-Science, Stockholm, Sweden. December 5-8, 2011. pp 15-22.
Jiang Y., Xu W., Thompson L.P., Gutell R., and Miranker D. (2011).
R-PASS: A Fast Structure-based RNA Sequence Alignment Algorithm.
Proceedings of 2011 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2011), Atlanta, GA. November 12-15, 2011. IEEE Computer Society, Washington, DC, USA. pp. 618-622.
Xu W., Wongsa A., Lee J., Shang L., Cannone J.J., and Gutell R.R. (2011).
RNA2DMap: A Visual Exploration Tool of the Information in RNA's Higher-Order Structure.
Proceedings of 2011 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2011), Atlanta, GA. November 12-15, 2011. IEEE Computer Society, Washington, DC, USA. pp. 613-617.
Muralidhara C., Gross A.M., Gutell R.R., and Alter O. (2011).
Tensor Decomposition Reveals Concurrent Evolutionary Convergences and Divergences and Correlations with Structural Motifs in Ribosomal RNA.
PLoS ONE, 6(4):e18768.
Xia Z., Gardner D.P., Gutell R.R., and Ren P. (2010).
Coarse-Grained Model for Simulation of RNA Three-Dimensional Structures.
The Journal of Physical Chemistry B, 114(42):13497-13506.
The document describes research on fragmentation of the large subunit ribosomal RNA (LSU rRNA) gene in oyster mitochondrial genomes. Key findings include:
1) The LSU rRNA gene is split into two fragments separated by thousands of nucleotides in three species of oysters.
2) RT-PCR and EST analysis showed the two fragments are transcribed separately in Crassostrea virginica and are not spliced together.
3) Secondary structure models of the fragmented LSU rRNA genes were predicted for C. virginica, C. gigas, and C. hongkongensis based on comparative sequence analysis. This fragmentation represents a novel phenomenon in bilateral metazoan mitochondrial genomes.
Mueller U.G., Ishak H., Lee J.C., Sen R., and Gutell R.R. (2010).
Placement of attine ant-associated Pseudonocardia in a global phylogeny (Pseudonocardiaceae, Actinomycetales): a test of two symbiont-association models.
Antonie van Leeuwenhoek International Journal of General and Molecular Microbiology, 98(2):195-212.
Theriot E.C., Cannone J.J., Gutell R.R., and Alverson A.J. (2009).
The limits of nuclear encoded SSU rDNA for resolving the diatom phylogeny.
European Journal of Phycology, 44(3):277-290.
Wu J.C., Gardner D.P., Ozer S., Gutell R.R. and Ren P. (2009).
Correlation of RNA Secondary Structure Statistics with Thermodynamic Stability and Applications to Folding.
Journal of Molecular Biology, 391(4):769-783.
Xu W., Ozer S., and Gutell R.R. (2009).
Covariant Evolutionary Event Analysis for Base Interaction Prediction Using a Relational Database Management System for RNA.
21st International Conference on Scientific and Statistical Database Management. June 2-4, 2009. Springer-Verlag. pp. 200-216.
Chen Y.P., Evans J.D., Murphy C., Gutell R., Zuker M., Gundersen-Rindal D., and Pettis J.S. (2009).
Morphological, Molecular, and Phylogenetic Characterization of Nosema cerenae, a Microsporidian Parasite Isolated from the European Honey Bee, Apis mellifera.
The Journal of Eukaryotic Microbiology, 56(2):142-147.
Maddison D.R., Moore W., Baker M.D., Ellis T.M., Ober K.A., Cannone J.J., and Gutell R.R. (2009).
Monophyly of terrestrial adephagan beetles as indicated by three nuclear genes (Coleoptera: Carabidae and Trachypachidae).
Zoologica Scripta, 38(1):43-62.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
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Gutell 042.nar.1994.22.03508
1. 3508-3510 Nucleic Acids Research, 1994, Vol. 22, No. 17
A comparative database of group I intron structures
Simon H.Damberger and Robin R.Gutell*
MCD Biology, Campus Box 347, University of Colorado, Boulder, CO 80309-0347, USA
ABSTRACT
We have created a database of comparatively derived
group I intron secondary structure diagrams. This
collection currently contains a broad sampling of
phylogenetically and structurally similar and diverse
structures from over 200 publicly available intron
sequences. As more group I introns are sequenced and
added to the database, we anticipate minor refinements
in these secondary structure diagrams. These diagrams
are directly accessible by computer as well as from the
authors.
INTRODUCTION
Group I introns are a family ofRNA molecules that catalyze their
own excision. Since it was discovered that group I introns self-
splice [1], much experimental and comparative research has been
devoted to determining their structure [2]. This work has, in turn,
helped us to understand their function during the splicing reaction.
As the number of group I intron sequences has increased,
comparative sequence analysis has established and refined the
group I intron secondary structure and is now revealing the
beginnirgs of a three dimensional model. [3,4,5,6] To further
refine the structural detail of group I introns, we will need
continued improvements ofour correlation analysis methods. We
will also need an even larger and more diverse collection ofgroup
I intron sequences.
Currently there are over 200 publicly available group I intron
sequences in GenBank [7]. These introns have been found within
two of the three primary phylogenetic domains and within the
Eucarya nucleus, chloroplast, and mitochondrion. With the
current number and expected increase ofgroup I intron sequence
availability, the need for a group I secondary structure database
has become great.
OBJECTIVES
Our current understanding of the patterns of sequence
conservation and variation for the group I intron family of RNA
molecules makes it possible to infer their secondary and tertiary
structure base pairings. The growing number of sequences
presents us with the opportunity to continue to evaluate and refine
these structures as additional comparative evidence becomes
available. These structures will be provided in a new common
format [8] that will allow a larger scientific audience to readily
compare similar and diverse introns. The group I secondary
structure database has several primary objectives:
1. To collect and structure group I intron sequences as they
become available. As more introns are sequenced, we expect
to refine the current structures using comparative analysis.
Although we expect the core structure of all group I introns
to largely remain the same, some minor changes in the
structure are possible. The variable regions, however, will
probably undergo more revision as sequences continue to
become available for comparison. Further comparative
analysis will also be called upon to identify new tertiary
interactions as comparative algorithms improve and the
database grows.
2. To present other information pertaining to group I introns such
as a list of all available group I intron sequences, reference
lists for intron sequences, cellular location ofintrons, and their
phylogenetic position.
3. To provide these structures to the general community via
anonymous ftp (file transfer protocol) and the World Wide
Web [9,10]. (Hard copies will also be available to those who
do not have access to the Internet.) Initially we will offer
representative structures from each of the major subgroups.
With time, we will generate more structures to round out the
phylogenetic diversity of the database. Within this
communication, we also present several examples of introns
including theAnkistrodesmus stipitatus LSU rRNA intron [11]
(fig. 1), Saccharomyces cerevisae mitochondrial LSU rRNA
intron [12] (fig. 2), and the second Podospora anserina
mitochondrial apocytochrome b intron [13] (fig. 3).
DESCRIPTION OF DATABASE
The database currently contains 219 intron sequences, the
majority ofwhich are available from GenBank. The total number
of introns in the different subgroups [as proposed in 6] are listed
in Table 1. These introns vary greatly in their phylogenetic
diversity and are found in two of the three major phylogenetic
domains, Eucarya and (eu)Bacteria [14,15] (this phylogenetic
nomenclature is presented in [16]). Within the Eucarya, introns
have been found in the nucleus and the two major organelles,
the mitochondrion and chloroplast. Group I introns have been
identified in 23 different genes (Table 1).
The secondary structures will be available in a new format that
more accurately represents the current knowledge of the group
I intron three dimensional structure [8]. The secondary structures
will be available through three channels; hard copies, anonymous
ftp, and through the WWW (World Wide Web). The computer
files will only be distributed in the PostScript format, therefore
*To whom correspondence should be addressed
.) 1994 Oxford University Press
2. Nucleic Acids Research, 1994, Vol. 22, No. 17 3509
AU- AA G-C- >C--
GU-A U-AC- A/ A-U
G-C C-GC- U A-U A* G
G *C G-C u
U U C v -AG
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AAU U A g CU
A A AL:CG-CAA AC-g CGAA I A C-U
AGUO- G CU GU
UAU-A-I G A -I
A-U~~~~~~~~G UU
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AC
(intron in capital letters) intron and flanking exon sequences (lower case letters).
The arrows point to the 5' and 3' splice sites. The thick lines show the continuity
of the strands with the arrowheads within the lines showing 5' to 3' sequence
direction. The boxed nucleotides connected by a thin line represent a base-pairing
interaction involved in the exon-ligation step (second step) of RNA splicing [4].
GenBank accession number is X56100.
a printer or viewer that can read PostScript is required to visualize
these diagrams. Those users with Internet access will be able to
retrieve copies of the structures through ftp or the WWW.
PostScript files of the secondary structure diagrams can be
obtained by anonymous ftp at the following site and directory:
ftp address: pundit. colorado. edu (128.138.212.53)
directory: /pub/RNA/GRPI/
The WWW is a system of software and protocols initiated by
CERN (European Laboratory for Particle Physics) to facilitate
the access of information via the Internet. It uses a hypertext and
multimedia presentation to simplify the accessibility of network
data. In order to use te WWW, one must first retrieve a program
that navigates the WWW like the NCSA (National Center for
Supercomputing Applications) Mosaic WWW browser.
NCSA Mosaic is a user-friendly WWW browser that is
available for Microsoft Windows, Macintoshes, and UNIX
workstations that use the X-Windows interface. NCSA Mosaic
can be retrieved by anonymous ftp from the ftp site
ftp.ncsa.uiuc.edu (141.142.20.50) in the /Mosaic directory.
To obtain PostScript files of the secondary structures through
the WWW, please use the following URL:
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Figure 2. Secondary structure diagram for the LSU rRNA Saccharomyces
cerevisiae mitochondrial intron. GenBank accession number is X00149.
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978 nucs
Figure 3. Secondary structre diagm for the second apocytochrome b Podospora
anserina mitochondrial intron. GenBank accession number is X55026.
3. 3510 Nucleic Acids Research, 1994, Vol. 22, No. 17
Table 1.
Subgroup Number Genes represented
IAl 28 ATP9; CYTB; LSU rRNA; ND1; OX2; psbA; psbB; psbC
IA2 6 g31; nrdB; nrdD; psbC; td
IA3 7 LSU rRNA; SSU rRNA
IB1 11 CYTB; LSU rRNA; OXI; SSU rRNA
IB2 17 ATP6; LSU rRNA; ND1; ND5; OXI
IB3 13 LSU rRNA; OXI; SSU rRNA
IB4 13 CYTB; LSU rRNA; ND5; OXI; psbA
ICi 46 LSU rRNA; ND1; ND4L; SSU rRNA
IC2 8 ATP6; ND1; ND3; ND4; ND5; OXI; SSU rRNA
IC3 33 LSU rRNA; OXI; tRNA arg; tRNA ile; tRNA leu
ID 13 CYTB; OXI; OX3; ND5
Unknown 24 CYTB; ND1; ND5; OXI; OX2; psbA; SSU rRNA;
Total 219
URL: http://pundit. colorado.edu:8080/RNA/GRPI/introns.html
The WWW database is formatted to make it easy for the user
to find the intron or introns of interest. There are two methods
ofaccessing the secondary structure diagrams. The first method
is through links set up by subgroup and phylogeny where the
user can click on the subgroup of interest and look for introns
through a list classified by phylogeny. For the second method,
the database allows boolean 'and' searches over all introns in
the database by organism name, intron site (gene and cellular
location), and subgroup (see WWW examples). These facilities
will be updated and enhanced as more introns are sequenced and
structured, and as our database expands. We welcome any
suggestions on how to improve the search facilities as well as
the database itself.
WWW examples
1. To find all subgroup IAl introns that occur in Podospora
anserina, enter the following into the search box (all searches
are case insensitive):
Podospora anserina IAl
2. To find all mitochondrial LSU rRNA introns, enter the
following:
LSUrRNA Mitochondrion
This publication should be quoted as a reference for any
secondary structure data obtained either through hard copies from
the authors or from the database. Requests for hard copy printouts
should be referred to RRG. Questions and comments about the
on-line resources should be directed to SHD.
ACKNOWLEDGEMENTS
We would like to thank Tom Cech for encouraging us to pursue
this project. We acknowledge Bryn Wiser and Tom Macke for
access to the programs that facilitate the generation of the
structures (XRNA) and alignments (AE2). We would also like
to thank the W. M. Keck Foundation for their generous support
of RNA science on the Boulder campus and Sun Microsystems
for the donation ofcomputer equipment. This work was supported
by grants from the NIH (GM48207) and the Colorado RNA
Center to R. R. G.
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ribosomal RNA precursor of Tetrahymena: involvement of a guanosine
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(1981).
2. Cech, T. R. Self-splicing ofgroup I introns. AnnualReviews ofBiochemistry
59, 543-568 (1990).
3. Michel, F., Jacquier, A., and Dujon, B. Comparison offungal mitochondrial
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splicing group I introns in cyanobacteria. Science 250, 1566-1570 (1990).
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shared by eubacteria and chloroplasts. Science 250, 1570-1572 (1990).
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