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On Differential Variability of Expression Ratios: Improving . . .
- JOURNAL OF COMPUTATIONAL BIOLOGY
, 2001
"... We consider the problem of inferring fold changes in gene expression from cDNA microarray data. Standard procedures focus on the ratio of measured fluorescent intensities at each spot on the microarray, but to do so is to ignore the fact that the variation of such ratios is not constant. Estimates o ..."
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Cited by 261 (7 self)
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We consider the problem of inferring fold changes in gene expression from cDNA microarray data. Standard procedures focus on the ratio of measured fluorescent intensities at each spot on the microarray, but to do so is to ignore the fact that the variation of such ratios is not constant. Estimates of gene expression changes are derived within a simple hierarchical model that accounts for measurement error and fluctuations in absolute gene expression levels. Significant gene expression changes are identified by deriving the posterior odds of change within a similar model. The methods are tested via simulation and are applied to a panel of Escherichia coli microarrays.
Complete genome sequence of enterohemorrhagic Escherichia coli O157:H7 and genomic comparison with a laboratory strain K-12. DNA Res
, 2001
"... Escherichia coli O157:H7 is a major food-borne infectious pathogen that causes diarrhea, hemorrhagic colitis, and hemolytic uremic syndrome. Here we report the complete chromosome sequence of an O157:H7 strain isolated from the Sakai outbreak, and the results of genomic comparison with a benign labo ..."
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Cited by 248 (11 self)
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Escherichia coli O157:H7 is a major food-borne infectious pathogen that causes diarrhea, hemorrhagic colitis, and hemolytic uremic syndrome. Here we report the complete chromosome sequence of an O157:H7 strain isolated from the Sakai outbreak, and the results of genomic comparison with a benign laboratory
A combined transmembrane topology and signal peptide prediction method
- J. Mol. Biol
, 2004
"... Hidden Markov models (HMMs) have been successfully applied to the tasks of transmembrane protein topology prediction and signal peptide prediction. In this paper we expand upon this work by making use of the more powerful class of dynamic Bayesian networks (DBNs). Our model, Philius, is inspired by ..."
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Cited by 233 (10 self)
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Hidden Markov models (HMMs) have been successfully applied to the tasks of transmembrane protein topology prediction and signal peptide prediction. In this paper we expand upon this work by making use of the more powerful class of dynamic Bayesian networks (DBNs). Our model, Philius, is inspired by a previously published HMM, Phobius, and combines a signal peptide submodel with a transmembrane submodel. We introduce a two-stage DBN decoder that combines the power of posterior decoding with the grammar constraints of Viterbi-style decoding. Philius also provides protein type, segment, and topology confidence metrics to aid in the interpretation of the predictions. We report a relative improvement of 13 % over Phobius in full-topology prediction accuracy on transmembrane proteins, and a sensitivity and specificity of 0.96 in detecting signal peptides. We also show that our confidence metrics correlate well with the observed precision. In addition, we have made predictions on all 6.3 million proteins in the Yeast Resource Center (YRC) database. This large-scale study provides an overall picture of the relative numbers of proteins that include a signal-peptide and/or one or more transmembrane segments as well as a valuable resource for the scientific community. All DBNs are implemented using the Graphical Models Toolkit. Source code for the models described here is available at
EcoCyc: a comprehensive database resource for Escherichia coli
- Nucleic Acids Res
, 2005
"... The EcoCyc database ..."
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Recombination repair of DNA damage in Escherichia coli and bacteriophage
, 1999
"... Damage reversal and one-strand repair..........................................................................................................753 Two-strand repair........................................................................................................................................ ..."
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Cited by 178 (3 self)
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Damage reversal and one-strand repair..........................................................................................................753 Two-strand repair...............................................................................................................................................753 Homologous recombination versus recombinational repair.........................................................................754 The two mechanisms of two-strand damage...................................................................................................755 The two recombinational repair pathways of E. coli.....................................................................................755 Frequency of two-strand lesions.......................................................................................................................756 Recombinational repair capacity of E. coli cells............................................................................................756 SOS Response: Reaction of E. coli to DNA Damage.........................................................................................756 Repair instead of DNA damage checkpoints: the prokaryotic strategy......................................................756 Organization of the SOS regulon.....................................................................................................................757 Levels of SOS induction.....................................................................................................................................758
Molecular biology and pathogenicity of mycoplasmas
, 1998
"... This article cites 454 articles, 231 of which can be accessed ..."
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Cited by 174 (9 self)
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This article cites 454 articles, 231 of which can be accessed
Functional genomics: expression analysis of Escherichia coli growing on minimal and rich
, 1999
"... DNA arrays of the entire set of Escherichia coli genes were used to measure the genomic expression patterns of cells growing in late logarithmic phase on minimal glucose medium and on Luria broth containing glucose. Ratios of the transcript levels for all 4,290 E. coli protein-encoding genes (cds) w ..."
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Cited by 151 (11 self)
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DNA arrays of the entire set of Escherichia coli genes were used to measure the genomic expression patterns of cells growing in late logarithmic phase on minimal glucose medium and on Luria broth containing glucose. Ratios of the transcript levels for all 4,290 E. coli protein-encoding genes (cds) were obtained, and analysis of the expression ratio data indicated that the physiological state of the cells under the two growth conditions could be ascertained. The cells in the rich medium grew faster, and expression of the majority of the translation apparatus genes was significantly elevated under this growth condition, consistent with known patterns of growth rate-dependent regulation and increased rate of protein synthesis in rapidly growing cells. The cells grown on minimal medium showed significantly elevated expression of many genes involved in biosynthesis of building blocks, most notably the amino acid biosynthetic pathways. Nearly half of the known RpoS-dependent genes were expressed at significantly higher levels in minimal medium than in rich medium, and rpoS expression was similarly elevated. The role of RpoS regulation in these logarithmic phase cells was suggested by the functions of the RpoS dependent genes that were induced. The hallmark features of E. coli cells growing on glucose minimal medium appeared to be the formation and excretion of acetate, metabolism of the acetate, and protection of the cells from acid stress. A hypothesis invoking RpoS and UspA (universal stress protein, also significantly elevated in minimal glucose medium) as playing a role in coordinating these various aspects
Issues in cDNA microarray analysis: quality filtering, channel normalization, models of variations and assessment of gene effects
, 2001
"... We consider the problem of comparing the gene expression levels of cells grown under two different conditions using cDNA microarray data. We use a quality index, computed from duplicate spots on the same slide, to filter out outlying spots, poor quality genes and problematical slides. We also perfor ..."
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Cited by 146 (5 self)
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We consider the problem of comparing the gene expression levels of cells grown under two different conditions using cDNA microarray data. We use a quality index, computed from duplicate spots on the same slide, to filter out outlying spots, poor quality genes and problematical slides. We also perform calibration experiments to show that normalization between fluorescent labels is needed and that the normalization is slide dependent and non-linear. A rank invariant method is suggested to select nondifferentially expressed genes and to construct normalization curves in comparative experiments. After normalization the residuals from the calibration data are used to provide prior information on variance components in the analysis of comparative experiments. Based on a hierarchical model that incorporates several levels of variations, a method for assessing the significance of gene effects in comparative experiments is presented. The analysis is demonstrated via two groups of experiments with 125 and 4129 genes, respectively, in Escherichia coli grown in glucose and acetate.
A Comprehensive Library of DNA-binding Site Matrices for 55 Proteins Applied to the Complete Escherichia coli K-12 Genome
- J. Mol. Biol
, 1998
"... Introduction Sequence-specic DNA-binding proteins perform a multitude of roles in a living cell and regulate a variety of processes including transcription. Escherichia coli contains at least 240 proteins that are known or predicted to be DNA-binding proteins (Robison, 1997). Known binding sites fo ..."
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Cited by 145 (1 self)
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Introduction Sequence-specic DNA-binding proteins perform a multitude of roles in a living cell and regulate a variety of processes including transcription. Escherichia coli contains at least 240 proteins that are known or predicted to be DNA-binding proteins (Robison, 1997). Known binding sites for a DNA-binding protein can be used to identify additional sites for that protein, and thereby identify further genes regulated by that protein (Wasserman & Fickett, 1998; Tronche et al., 1997; Fondrat & Kalogeropoulos, 1996; Goodrich et al., 1990; Lewis et al., 1994; Ramseier et al., 1995; Stormo, 1990; Verbeek et al., 1990). A number of approaches have been used to search for additional sites, including searches using consensus sequences, and searches using position weight matrices. Fondrat & Kalogeropoulos (1996) used a precise set of rules and constraints together with a degenerate co
Regulation of translation via mRNA structure in prokaryotes and eukaryotes
- Gene
, 2005
"... The mechanism of initiation of translation differs between prokaryotes and eukaryotes, and the strategies used for regulation differ accordingly. Translation in prokaryotes is usually regulated by blocking access to the initiation site. This is accomplished via base-paired structures (within the mRN ..."
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Cited by 131 (1 self)
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The mechanism of initiation of translation differs between prokaryotes and eukaryotes, and the strategies used for regulation differ accordingly. Translation in prokaryotes is usually regulated by blocking access to the initiation site. This is accomplished via base-paired structures (within the mRNA itself, or between the mRNA and a small trans-acting RNA) or via mRNA-binding proteins. Classic examples of each mechanism are described. The polycistronic structure of mRNAs is an important aspect of translational control in prokaryotes, but polycistronic mRNAs are not usable (and usually not produced) in eukaryotes. Four structural elements in eukaryotic mRNAs are important for regulating translation: (i) the m7G cap; (ii) sequences flanking the AUG start codon; (iii) the position of the AUG codon relative to the 5 ′ end of the mRNA; and (iv) secondary structure within the mRNA leader sequence. The scanning model provides a framework for understanding these effects. The scanning mechanism also explains how small open reading frames near the 5 ′ end of the mRNA can down-regulate translation. This constraint is sometimes abrogated by changing the structure of the mRNA, sometimes with clinical consequences. Examples are described. Some mistaken ideas about regulation of translation that have found their way into textbooks are pointed out and corrected.
