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2.  Stochastic Processes Are Key Determinants of Short-Term Evolution in Influenza A Virus 
PLoS Pathogens  2006;2(12):e125.
Understanding the evolutionary dynamics of influenza A virus is central to its surveillance and control. While immune-driven antigenic drift is a key determinant of viral evolution across epidemic seasons, the evolutionary processes shaping influenza virus diversity within seasons are less clear. Here we show with a phylogenetic analysis of 413 complete genomes of human H3N2 influenza A viruses collected between 1997 and 2005 from New York State, United States, that genetic diversity is both abundant and largely generated through the seasonal importation of multiple divergent clades of the same subtype. These clades cocirculated within New York State, allowing frequent reassortment and generating genome-wide diversity. However, relatively low levels of positive selection and genetic diversity were observed at amino acid sites considered important in antigenic drift. These results indicate that adaptive evolution occurs only sporadically in influenza A virus; rather, the stochastic processes of viral migration and clade reassortment play a vital role in shaping short-term evolutionary dynamics. Thus, predicting future patterns of influenza virus evolution for vaccine strain selection is inherently complex and requires intensive surveillance, whole-genome sequencing, and phenotypic analysis.
Synopsis
A comparative analysis of 413 complete genomes of the H3N2 subtype of human influenza A virus sampled from New York State, United States, the largest and first population-based study of its kind, reveals that viral evolution within epidemic seasons is dominated by the random importation of genetically different viral strains from other geographic areas, rather than by natural selection favoring local strains able to escape the human immune response. Multiple clades of genetically distinct viral strains cocirculate across the entire state within any season and occasionally exchange genes through reassortment. Both genetic diversity and geographic viral “traffic” are extensive within epidemics. Therefore, the evolution of influenza A virus is strongly shaped by random migration and reassortment and is far harder to predict than previously realized. Consequently, intensive sampling and whole-genome sequencing are essential for selecting viral strains for future vaccine production.
doi:10.1371/journal.ppat.0020125
PMCID: PMC1665651  PMID: 17140286
3.  Database resources of the National Center for Biotechnology Information 
Nucleic Acids Research  2013;42(Database issue):D7-D17.
In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI, http://www.ncbi.nlm.nih.gov) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI Web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central, PubReader, Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link, Primer-BLAST, COBALT, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, dbVar, Epigenomics, the Genetic Testing Registry, Genome and related tools, the Map Viewer, Trace Archive, Sequence Read Archive, BioProject, BioSample, ClinVar, MedGen, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus, Probe, Online Mendelian Inheritance in Animals, the Molecular Modeling Database, the Conserved Domain Database, the Conserved Domain Architecture Retrieval Tool, Biosystems, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All these resources can be accessed through the NCBI home page.
doi:10.1093/nar/gkt1146
PMCID: PMC3965057  PMID: 24259429
4.  GenBank 
Nucleic Acids Research  2013;42(Database issue):D32-D37.
GenBank® is a comprehensive database that contains publicly available nucleotide sequences for over 280 000 formally described species. These sequences are obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects, including whole-genome shotgun and environmental sampling projects. Most submissions are made using the web-based BankIt or standalone Sequin programs, and GenBank staff assign accession numbers upon data receipt. Daily data exchange with the European Nucleotide Archive and the DNA Data Bank of Japan ensures worldwide coverage. GenBank is accessible through the National Center for Biotechnology Information (NCBI) Entrez retrieval system, which integrates data from the major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and the biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available by FTP. To access GenBank and its related retrieval and analysis services, begin at the NCBI home page: www.ncbi.nlm.nih.gov.
doi:10.1093/nar/gkt1030
PMCID: PMC3965104  PMID: 24217914
5.  Sequential Seasonal H1N1 Influenza Virus Infections Protect Ferrets against Novel 2009 H1N1 Influenza Virus 
Journal of Virology  2013;87(3):1400-1410.
Individuals <60 years of age had the lowest incidence of infection, with ∼25% of these people having preexisting, cross-reactive antibodies to novel 2009 H1N1 influenza. Many people >60 years old also had preexisting antibodies to novel H1N1. These observations are puzzling because the seasonal H1N1 viruses circulating during the last 60 years were not antigenically similar to novel H1N1. We therefore hypothesized that a sequence of exposures to antigenically different seasonal H1N1 viruses can elicit an antibody response that protects against novel 2009 H1N1. Ferrets were preinfected with seasonal H1N1 viruses and assessed for cross-reactive antibodies to novel H1N1. Serum from infected ferrets was assayed for cross-reactivity to both seasonal and novel 2009 H1N1 strains. These results were compared to those of ferrets that were sequentially infected with H1N1 viruses isolated prior to 1957 or more-recently isolated viruses. Following seroconversion, ferrets were challenged with novel H1N1 influenza virus and assessed for viral titers in the nasal wash, morbidity, and mortality. There was no hemagglutination inhibition (HAI) cross-reactivity in ferrets infected with any single seasonal H1N1 influenza viruses, with limited protection to challenge. However, sequential H1N1 influenza infections reduced the incidence of disease and elicited cross-reactive antibodies to novel H1N1 isolates. The amount and duration of virus shedding and the frequency of transmission following novel H1N1 challenge were reduced. Exposure to multiple seasonal H1N1 influenza viruses, and not to any single H1N1 influenza virus, elicits a breadth of antibodies that neutralize novel H1N1 even though the host was never exposed to the novel H1N1 influenza viruses.
doi:10.1128/JVI.02257-12
PMCID: PMC3554183  PMID: 23115287
7.  Why Does a Protein’s Evolutionary Rate Vary over Time? 
Genome Biology and Evolution  2013;5(3):494-503.
The sequences of different proteins evolve at different rates. The relative evolutionary rate (ER) of a single protein also changes over evolutionary time. The cause of this ER fluctuation remains uncertain, and study of this phenomenon may shed light on protein evolution more broadly. We have characterized ER fluctuation in mammals and Drosophila. We found little correlation between the amount of rate variation observed for a protein and such factors as its expression level or phylogenetic distribution. Perhaps more surprisingly, we found little correlation between our measure of rate variation and ER itself. We also investigated the extent to which the ERs of different domains of a protein vary independently. We found that rates of different domains do tend to vary together. In fact, rates at positions in different domains are coupled just as strongly as rates at equally distant positions in the same domain. These findings provide clues to the protein evolutionary process.
doi:10.1093/gbe/evt024
PMCID: PMC3622301  PMID: 23436005
protein evolution; evolutionary rate; overdispersion; molecular clock
8.  GenBank 
Nucleic Acids Research  2012;41(Database issue):D36-D42.
GenBank® (http://www.ncbi.nlm.nih.gov) is a comprehensive database that contains publicly available nucleotide sequences for almost 260 000 formally described species. These sequences are obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects, including whole-genome shotgun (WGS) and environmental sampling projects. Most submissions are made using the web-based BankIt or standalone Sequin programs, and GenBank staff assigns accession numbers upon data receipt. Daily data exchange with the European Nucleotide Archive (ENA) and the DNA Data Bank of Japan (DDBJ) ensures worldwide coverage. GenBank is accessible through the NCBI Entrez retrieval system, which integrates data from the major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and the biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available by FTP. To access GenBank and its related retrieval and analysis services, begin at the NCBI home page: www.ncbi.nlm.nih.gov.
doi:10.1093/nar/gks1195
PMCID: PMC3531190  PMID: 23193287
9.  Complex Patterns of Human Antisera Reactivity to Novel 2009 H1N1 and Historical H1N1 Influenza Strains 
PLoS ONE  2012;7(7):e39435.
Background
During the 2009 influenza pandemic, individuals over the age of 60 had the lowest incidence of infection with approximately 25% of these people having pre-existing, cross-reactive antibodies to novel 2009 H1N1 influenza isolates. It was proposed that older people had pre-existing antibodies induced by previous 1918-like virus infection(s) that cross-reacted to novel H1N1 strains.
Methodology/Principal Findings
Using antisera collected from a cohort of individuals collected before the second wave of novel H1N1 infections, only a minority of individuals with 1918 influenza specific antibodies also demonstrated hemagglutination-inhibition activity against the novel H1N1 influenza. In this study, we examined human antisera collected from individuals that ranged between the ages of 1 month and 90 years to determine the profile of seropositive influenza immunity to viruses representing H1N1 antigenic eras over the past 100 years. Even though HAI titers to novel 2009 H1N1 and the 1918 H1N1 influenza viruses were positively associated, the association was far from perfect, particularly for the older and younger age groups.
Conclusions/Significance
Therefore, there may be a complex set of immune responses that are retained in people infected with seasonal H1N1 that can contribute to the reduced rates of H1N1 influenza infection in older populations.
doi:10.1371/journal.pone.0039435
PMCID: PMC3398940  PMID: 22815705
10.  Domain enhanced lookup time accelerated BLAST 
Biology Direct  2012;7:12.
Background
BLAST is a commonly-used software package for comparing a query sequence to a database of known sequences; in this study, we focus on protein sequences. Position-specific-iterated BLAST (PSI-BLAST) iteratively searches a protein sequence database, using the matches in round i to construct a position-specific score matrix (PSSM) for searching the database in round i + 1. Biegert and Söding developed Context-sensitive BLAST (CS-BLAST), which combines information from searching the sequence database with information derived from a library of short protein profiles to achieve better homology detection than PSI-BLAST, which builds its PSSMs from scratch.
Results
We describe a new method, called domain enhanced lookup time accelerated BLAST (DELTA-BLAST), which searches a database of pre-constructed PSSMs before searching a protein-sequence database, to yield better homology detection. For its PSSMs, DELTA-BLAST employs a subset of NCBI’s Conserved Domain Database (CDD). On a test set derived from ASTRAL, with one round of searching, DELTA-BLAST achieves a ROC5000 of 0.270 vs. 0.116 for CS-BLAST. The performance advantage diminishes in iterated searches, but DELTA-BLAST continues to achieve better ROC scores than CS-BLAST.
Conclusions
DELTA-BLAST is a useful program for the detection of remote protein homologs. It is available under the “Protein BLAST” link at http://blast.ncbi.nlm.nih.gov.
Reviewers
This article was reviewed by Arcady Mushegian, Nick V. Grishin, and Frank Eisenhaber.
doi:10.1186/1745-6150-7-12
PMCID: PMC3438057  PMID: 22510480
11.  GenBank 
Nucleic Acids Research  2011;40(Database issue):D48-D53.
GenBank® is a comprehensive database that contains publicly available nucleotide sequences for more than 250 000 formally described species. These sequences are obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects, including whole-genome shotgun (WGS) and environmental sampling projects. Most submissions are made using the web-based BankIt or standalone Sequin programs, and accession numbers are assigned by GenBank staff upon receipt. Daily data exchange with the European Nucleotide Archive (ENA) and the DNA Data Bank of Japan (DDBJ) ensures worldwide coverage. GenBank is accessible through the NCBI Entrez retrieval system, which integrates data from the major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and the biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available by FTP. To access GenBank and its related retrieval and analysis services, begin at the NCBI home page: www.ncbi.nlm.nih.gov.
doi:10.1093/nar/gkr1202
PMCID: PMC3245039  PMID: 22144687
12.  Database resources of the National Center for Biotechnology Information 
Nucleic Acids Research  2011;40(Database issue):D13-D25.
In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI Website. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central (PMC), Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Primer-BLAST, COBALT, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, dbVar, Epigenomics, Genome and related tools, the Map Viewer, Model Maker, Evidence Viewer, Trace Archive, Sequence Read Archive, BioProject, BioSample, Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus (GEO), Probe, Online Mendelian Inheritance in Animals (OMIA), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART), Biosystems, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.
doi:10.1093/nar/gkr1184
PMCID: PMC3245031  PMID: 22140104
13.  Projection of seasonal influenza severity from sequence and serological data 
PLoS Currents  2010;2:RRN1200.
Severity of seasonal influenza A epidemics is related to the antigenic novelty of the predominant viral strains circulating each year. Support for a strong correlation between epidemic severity and antigenic drift comes from infectious challenge experiments on vaccinated animals and human volunteers, field studies of vaccine efficacy, prospective studies of subjects with laboratory-confirmed prior infections, and analysis of the connection between drift and severity from surveillance data. We show that, given data on the antigenic and sequence novelty of the hemagglutinin protein of clinical isolates of H3N2 virus from a season along with the corresponding data from prior seasons, we can accurately predict the influenza severity for that season. This model therefore provides a framework for making projections of the severity of the upcoming season using assumptions based on viral isolates collected in the current season. Our results based on two independent data sets from the US and Hong Kong suggest that seasonal severity is largely determined by the novelty of the hemagglutinin protein although other factors, including mutations in other influenza genes, co-circulating pathogens and weather conditions, might also play a role. These results should be helpful for the control of seasonal influenza and have implications for improvement of influenza surveillance.
doi:10.1371/currents.RRN1200
PMCID: PMC2998708  PMID: 21152078
14.  Database resources of the National Center for Biotechnology Information 
Nucleic Acids Research  2010;39(Database issue):D38-D51.
In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI Web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central (PMC), Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Primer-BLAST, COBALT, Electronic PCR, OrfFinder, Splign, ProSplign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, dbVar, Epigenomics, Cancer Chromosomes, Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Trace Archive, Sequence Read Archive, Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus (GEO), Entrez Probe, GENSAT, Online Mendelian Inheritance in Man (OMIM), Online Mendelian Inheritance in Animals (OMIA), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART), IBIS, Biosystems, Peptidome, OMSSA, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.
doi:10.1093/nar/gkq1172
PMCID: PMC3013733  PMID: 21097890
15.  GenBank 
Nucleic Acids Research  2010;39(Database issue):D32-D37.
GenBank® is a comprehensive database that contains publicly available nucleotide sequences for more than 380 000 organisms named at the genus level or lower, obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects, including whole genome shotgun (WGS) and environmental sampling projects. Most submissions are made using the web-based BankIt or standalone Sequin programs, and accession numbers are assigned by GenBank staff upon receipt. Daily data exchange with the European Nucleotide Archive (ENA) and the DNA Data Bank of Japan (DDBJ) ensures worldwide coverage. GenBank is accessible through the NCBI Entrez retrieval system that integrates data from the major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and the biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available by FTP. To access GenBank and its related retrieval and analysis services, begin at the NCBI Homepage: www.ncbi.nlm.nih.gov.
doi:10.1093/nar/gkq1079
PMCID: PMC3013681  PMID: 21071399
16.  Relative Contributions of Intrinsic Structural–Functional Constraints and Translation Rate to the Evolution of Protein-Coding Genes 
A long-standing assumption in evolutionary biology is that the evolution rate of protein-coding genes depends, largely, on specific constraints that affect the function of the given protein. However, recent research in evolutionary systems biology revealed unexpected, significant correlations between evolution rate and characteristics of genes or proteins that are not directly related to specific protein functions, such as expression level and protein–protein interactions. The strongest connections were consistently detected between protein sequence evolution rate and the expression level of the respective gene. A recent genome-wide proteomic study revealed an extremely strong correlation between the abundances of orthologous proteins in distantly related animals, the nematode Caenorhabditis elegans and the fruit fly Drosophila melanogaster. We used the extensive protein abundance data from this study along with short-term evolutionary rates (ERs) of orthologous genes in nematodes and flies to estimate the relative contributions of structural–functional constraints and the translation rate to the evolution rate of protein-coding genes. Together the intrinsic constraints and translation rate account for approximately 50% of the variance of the ERs. The contribution of constraints is estimated to be 3- to 5-fold greater than the contribution of translation rate.
doi:10.1093/gbe/evq010
PMCID: PMC2940324  PMID: 20624725
protein evolution; structural–functional constraints; misfolding; protein abundance
17.  Database resources of the National Center for Biotechnology Information 
Nucleic Acids Research  2009;38(Database issue):D5-D16.
In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR, OrfFinder, Spidey, Splign, Reference Sequence, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Trace Archive, Sequence Read Archive, Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus, Entrez Probe, GENSAT, Online Mendelian Inheritance in Man, Online Mendelian Inheritance in Animals, the Molecular Modeling Database, the Conserved Domain Database, the Conserved Domain Architecture Retrieval Tool, Biosystems, Peptidome, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the web applications are custom implementations of the BLAST program optimized to search specialized data sets. All these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.
doi:10.1093/nar/gkp967
PMCID: PMC2808881  PMID: 19910364
18.  GenBank 
Nucleic Acids Research  2009;38(Database issue):D46-D51.
GenBank® is a comprehensive database that contains publicly available nucleotide sequences for more than 300 000 organisms named at the genus level or lower, obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects, including whole genome shotgun (WGS) and environmental sampling projects. Most submissions are made using the web-based BankIt or standalone Sequin programs, and accession numbers are assigned by GenBank staff upon receipt. Daily data exchange with the European Molecular Biology Laboratory Nucleotide Sequence Database in Europe and the DNA Data Bank of Japan ensures worldwide coverage. GenBank is accessible through the NCBI Entrez retrieval system, which integrates data from the major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and the biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bi-monthly releases and daily updates of the GenBank database are available by FTP. To access GenBank and its related retrieval and analysis services, begin at the NCBI homepage: www.ncbi.nlm.nih.gov.
doi:10.1093/nar/gkp1024
PMCID: PMC2808980  PMID: 19910366
19.  Selection for minimization of translational frameshifting errors as a factor in the evolution of codon usage 
Nucleic Acids Research  2009;37(20):6799-6810.
In a wide range of genomes, it was observed that the usage of synonymous codons is biased toward specific codons and codon patterns. Factors that are implicated in the selection for codon usage include facilitation of fast and accurate translation. There are two types of translational errors: missense errors and processivity errors. There is considerable evidence in support of the hypothesis that codon usage is optimized to minimize missense errors. In contrast, little is known about the relationship between codon usage and frameshifting errors, an important form of processivity errors, which appear to occur at frequencies comparable to the frequencies of missense errors. Based on the recently proposed pause-and-slip model of frameshifting, we developed Frameshifting Robustness Score (FRS). We used this measure to test if the pattern of codon usage indicates optimization against frameshifting errors. We found that the FRS values of protein-coding sequences from four analyzed genomes (the bacteria Bacillus subtilis and Escherichia coli, and the yeasts Saccharomyces cerevisiae and Schizosaccharomyce pombe) were typically higher than expected by chance. Other properties of FRS patterns observed in B. subtilis, S. cerevisiae and S. pombe, such as the tendency of FRS to increase from the 5′- to 3′-end of protein-coding sequences, were also consistent with the hypothesis of optimization against frameshifting errors in translation. For E. coli, the results of different tests were less consistent, suggestive of a much weaker optimization, if any. Collectively, the results fit the concept of selection against mistranslation-induced protein misfolding being one of the factors shaping the evolution of both coding and non-coding sequences.
doi:10.1093/nar/gkp712
PMCID: PMC2777431  PMID: 19745054
20.  Evolutionary Dynamics of N-Glycosylation Sites of Influenza Virus Hemagglutinin 
PLoS Currents  2009;1:RRN1001.
The hemagglutinin protein of influenza virus bears several sites of N-linked asparagine glycosylation. The number and location of these sites varies with strain and substrain. The human H3 hemagglutinin has gained several glycosylation sites on the antigenically important globular head since its introduction to humans, presumably due to selection. Although there is abundant evidence that glycosylation can affect antigenic and functional properties of the protein, direct evidence for selection is lacking. We have analyzed gain and loss of glycosylation sites on the side branches of a large phylogenetic tree of H3 HA1 sequences (branches off of the main, long-term line of descent). Side branches contrast with the main line of descent: losses of glycosylation sites are not uncommon, and they outnumber gains. Although other explanations are possible, this observation is consistent with weak selection for glycosylation sites or a more complicated pattern of selection. Furthermore, terminal and internal branches differ with respect to rates of gain and loss of glycosylation sites. This pattern would not be expected under selective neutrality, but is easily explained by weak selection or selection that changes with the immune state of the host population. Thus, it provides evidence that selection acts on the glycosylation state of hemagglutinin.
doi:10.1371/currents.RRN1001
PMCID: PMC2762648  PMID: 20025194
22.  Database resources of the National Center for Biotechnology Information 
Nucleic Acids Research  2008;37(Database issue):D5-D15.
In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR, OrfFinder, Spidey, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups (COGs), Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus (GEO), Entrez Probe, GENSAT, Online Mendelian Inheritance in Man (OMIM), Online Mendelian Inheritance in Animals (OMIA), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART) and the PubChem suite of small molecule databases. Augmenting many of the web applications is custom implementation of the BLAST program optimized to search specialized data sets. All of the resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.
doi:10.1093/nar/gkn741
PMCID: PMC2686545  PMID: 18940862
23.  GenBank 
Nucleic Acids Research  2008;37(Database issue):D26-D31.
GenBank® is a comprehensive database that contains publicly available nucleotide sequences for more than 300 000 organisms named at the genus level or lower, obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects. Most submissions are made using the web-based BankIt or standalone Sequin programs, and accession numbers are assigned by GenBank® staff upon receipt. Daily data exchange with the European Molecular Biology Laboratory Nucleotide Sequence Database in Europe and the DNA Data Bank of Japan ensures worldwide coverage. GenBank is accessible through the National Center for Biotechnology Information (NCBI) Entrez retrieval system, which integrates data from the major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and the biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available by FTP. To access GenBank and its related retrieval and analysis services, begin at the NCBI Homepage: www.ncbi.nlm.nih.gov.
doi:10.1093/nar/gkn723
PMCID: PMC2686462  PMID: 18940867
24.  Differences in evolutionary pressure acting within highly conserved ortholog groups 
Background
In highly conserved widely distributed ortholog groups, the main evolutionary force is assumed to be purifying selection that enforces sequence conservation, with most divergence occurring by accumulation of neutral substitutions. Using a set of ortholog groups from prokaryotes, with a single representative in each studied organism, we asked the question if this evolutionary pressure is acting similarly on different subgroups of orthologs defined as major lineages (e.g. Proteobacteria or Firmicutes).
Results
Using correlations in entropy measures as a proxy for evolutionary pressure, we observed two distinct behaviors within our ortholog collection. The first subset of ortholog groups, called here informational, consisted mostly of proteins associated with information processing (i.e. translation, transcription, DNA replication) and the second, the non-informational ortholog groups, mostly comprised of proteins involved in metabolic pathways. The evolutionary pressure acting on non-informational proteins is more uniform relative to their informational counterparts. The non-informational proteins show higher level of correlation between entropy profiles and more uniformity across subgroups.
Conclusion
The low correlation of entropy profiles in the informational ortholog groups suggest that the evolutionary pressure acting on the informational ortholog groups is not uniform across different clades considered this study. This might suggest "fine-tuning" of informational proteins in each lineage leading to lineage-specific differences in selection. This, in turn, could make these proteins less exchangeable between lineages. In contrast, the uniformity of the selective pressure acting on the non-informational groups might allow the exchange of the genetic material via lateral gene transfer.
doi:10.1186/1471-2148-8-208
PMCID: PMC2488352  PMID: 18637201
25.  GenBank 
Nucleic Acids Research  2007;36(Database issue):D25-D30.
GenBank (R) is a comprehensive database that contains publicly available nucleotide sequences for more than 260 000 named organisms, obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects. Most submissions are made using the web-based BankIt or standalone Sequin programs and accession numbers are assigned by GenBank staff upon receipt. Daily data exchange with the European Molecular Biology Laboratory Nucleotide Sequence Database in Europe and the DNA Data Bank of Japan ensures worldwide coverage. GenBank is accessible through NCBI's retrieval system, Entrez, which integrates data from the major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and the biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available by FTP. To access GenBank and its related retrieval and analysis services, begin at the NCBI Homepage: www.ncbi.nlm.nih.gov
doi:10.1093/nar/gkm929
PMCID: PMC2238942  PMID: 18073190

Results 1-25 (40)