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At least 253 records · Page 14Linked to original sources
PubMed2003

Statistical inference for well-ordered structures in nucleotide sequences.

Distinct, local structures are frequently correlated with functional RNA elements involved in post-transcriptional regulation of gene expression. Discovery of microRNAs (miRNAs) suggests that there are a large class of small non-coding RNAs in eukaryotic genomes. These miRNAs have the potential to form distinct fold-back stem-loop structures. The prediction of those well-ordered folding sequences (WFS) in genomic sequences is very helpful for our understanding of RNA-based gene regulation and the determination of local RNA elements with structure-dependent functions. In this study, we describe a novel method for discovering the local WFS in a nucleotide sequence by Monte Carlo simulation and RNA folding. In the approach the quality of a local WFS is assessed by the energy difference (E(diff)) between the optimal structure folded in the local segment and its corresponding optimal, restrained structure where all the previous base pairings formed in the optimal structure are prohibited. Distinct WFS can be discovered by scanning successive segments along a sequence for evaluating the difference between E(diff) of the natural sequence and those computed from randomly shuffled sequences. Our results indicate that the statistically significant WFS detected in the genomic sequences of Caenorhabditis elegans (C.elegans) F49E12, T07C5, T07D1, T10H9, Y56A3A and Y71G12B are coincident with known fold-back stem-loops found in miRNA precursors. The potential and implications of our method in searching for miRNAs in genomes is discussed.

Algorithms↗
PubMed1993

Techniques to identify clinical contexts during automated data analysis.

The interpretation of automatically collected data to produce intelligent alarms and identify particular conditions is nearly impossible without identifying the specific context in which the data are obtained. Shifts in clinical context occur because of changes in the patient's physiologic state, or due to the passage of time, or due to changes imposed by therapeutic intervention such as surgery. Techniques to identify such changes in clinical context are discussed with particular attention to the application of cluster analysis, discriminant analysis, and statistical predictors. An example of these analyses applied to EEG data is presented, showing an unexpected hysteresis of EEG behavior in response to an hypoxic challenge.

Cluster Analysis↗
PubMed1992

Poisson, compound Poisson and process approximations for testing statistical significance in sequence comparisons.

DNA and protein sequence comparisons are performed by a number of computational algorithms. Most of these algorithms search for the alignment of two sequences that optimizes some alignment score. It is an important problem to assess the statistical significance of a given score. In this paper we use newly developed methods for Poisson approximation to derive estimates of the statistical significance of k-word matches on a diagonal of a sequence comparison. We require at least q of the k letters of the words to match where 0 less than q less than or equal to k. The distribution of the number of matches on a diagonal is approximated as well as the distribution of the order statistics of the sizes of clumps of matches on the diagonal. These methods provide an easily computed approximation of the distribution of the longest exact matching word between sequences. The methods are validated using comparisons of vertebrate and E. coli protein sequences. In addition, we compare two HLA class II transplantation antigens by this method and contrast the results with a dynamic programming approach. Several open problems are outlined in the last section.

Algorithms↗
PubMed1992

Enrichment of oligonucleotide sets with transcription control signals. II: Mammalian DNA.

We studied the frequency distribution of oligonucleotides 10 bp long in a sample of 1.6 Mb of mammalian genes, containing 579 sequences from GenBank(R) 55.0, with the aim of detecting transcription control signals. 2216 decamers had a frequency higher than 10 times the mean and were subjected to further statistical analysis. For each of the 2216 decamers (parents), we counted the individual frequencies of the 30 decamers differing from the parent by one base mutation (progeny) and then calculated two variance/mean chi squares for the progeny, with and without the parent. We then studied the distribution of the ratio between the two chi squares. Out of 2216 decamers, 346 had a chi square ratio of 1.9 or larger. In this final set, which corresponds to less than 0.033 per cent of all possible decamers, 18 were found to contain 23 eukaryotic transcription control elements 5-10 bp of length, such as Sp1 and others. Furthermore, when compared to 210 random sets containing 346 decamers, this set contains a highly significant excess of the longer signals.

Algorithms↗
PubMed1991

Statistical issues arising from mouse micronucleus assay experiments of Ashby and co-workers.

Data from a series of mouse micronucleus assays have been reanalysed to illustrate various statistical issues raised by Ashby and co-workers during the development of the assay. Most of the statistical points discussed in these earlier papers can be explained by the stochastic nature of the data. Reanalysis shows that the type of data collected in mammalian micronucleus assays is amenable to analysis by standard biometric methods. It is concluded that statistical analysis has an important role in the exploration and interpretation of data from the micronucleus assay.

Analysis of Variance↗
PubMed2005

Statistical properties of information processing in neuronal networks.

Information processing and coding were analysed in dissociated hippocampal cultures, grown on multielectrode arrays. Multisite stimulation was used to activate different neurons and pathways of the network. The neural activity was binned into firing rates and the variability of the firing of individual neurons and of the whole population was analysed. In individual neurons, the timing of the first action potential (AP) was rather precise from trial to trial, whereas the timing of later APs was much more variable. Pooling APs in an ensemble of neurons reduced the variability of the response and allowed stimuli varying in intensity to be distinguished reliably in a single trial. A similar decrease of variability was observed pooling the first evoked APs in an ensemble of neurons. The size of the neuronal pool (approximately 50-100 neurons) and the time bin (approximately 20 ms) necessary to provide reproducible responses are remarkably similar to those obtained in in vivo preparations and in small nervous systems. Blockage of excitatory synaptic pathways mediated by NMDA receptors improved the mutual information between the evoked response and stimulus properties. When inhibitory GABAergic pathways were blocked by bicuculline the opposite effect was obtained. These results show how ensemble averages and an appropriate balance between inhibition and excitation allow neuronal networks to process information in a fast and reliable way.

Action Potentials↗
PubMed1994

Statistical tests of significance in transgenic mutation assays: considerations on the experimental unit.

When significant animal-to-animal variability is present in binary response data, the usual statistical tests applied to such data do not always operate correctly. In transgenic mouse mutation data, some evidence of significant animal-to-animal variability already exists, suggesting that conventional statistical methods may not be appropriate. Here, we describe an alternative statistical method that treats the animal as the experimental (or statistically independent) unit, and contrast results of its application with those from methods that take the transgene as the experimental unit. Using data from two publications that report experimental results for individual animals, the transgene-based and animal-based analyses can yield very different interpretations of the experimental data. The performance of animal-based statistical methods should be improved by conducting future experiments with enough animals to adequately address animal-to-animal variability.

Animals↗
PubMed2006

JProGO: a novel tool for the functional interpretation of prokaryotic microarray data using Gene Ontology information.

A novel program suite was implemented for the functional interpretation of high-throughput gene expression data based on the identification of Gene Ontology (GO) nodes. The focus of the analysis lies on the interpretation of microarray data from prokaryotes. The three well established statistical methods of the threshold value-based Fisher's exact test, as well as the threshold value-independent Kolmogorov-Smirnov and Student's t-test were employed in order to identify the groups of genes with a significantly altered expression profile. Furthermore, we provide the application of the rank-based unpaired Wilcoxon's test for a GO-based microarray data interpretation. Further features of the program include recognition of the alternative gene names and the correction for multiple testing. Obtained results are visualized interactively both as a table and as a GO subgraph including all significant nodes. Currently, JProGO enables the analysis of microarray data from more than 20 different prokaryotic species, including all important model organisms, and thus constitutes a useful web service for the microbial research community. JProGO is freely accessible via the web at the following address: http://www.jprogo.de.

Archaea↗
PubMed2004

Structural and spectroscopic study of 5,7-dihydroxy-flavone and its complex with aluminum.

The structure, stability and molar absorptivity of the complex formed between AlCl(3) and 5,7-dihydroxy-flavone in methanol were investigated using UV-Vis spectroscopy and the AM1 method. The molar ratio method and Job's method of continuous variation were applied to ascertain the stoichiometric composition of the complex in methanol at constant ionic strength. A 1:2 complex was indicated by both methods. The molar absorptivity and stability constant of the complex were determined using a simple and accurate procedure that requires solutions having the ligand and metal ion in the stoichiometric proportion. The high stability constant demonstrates that the complexation reaction is total. The structure of this complex, obtained by the quantum semi-empirical AM1 method, indicates that two classes of metal-ligand interactions are involved in the formation of the metal complex: (a) two simple covalent bonds between the aluminum atom and the oxygen atoms of o-hydroxyl groups of 5,7-dihydroxy-flavone; (b) two stronger Coulombic interactions between the aluminum atom and the carbonyl oxygen atoms of the ligand.

Aluminum↗
PubMedDate not supplied

Processing of serum proteins underlies the mass spectral fingerprinting of myocardial infarction.

The MALDI-TOF spectra of peptides from the sera of normal and myocardial infarction patients produced patterns that provided an accurate diagnostic of MI. In myocardial infarction, the spectral pattern originated from the cleavage of complement C3 alpha chain to release the C3f peptide and cleavage of fibrinogen to release peptide A. The fibrinogen peptide A and complement C3f peptide were in turn progressively truncated by aminopeptidases to produce two families of fragments that formed the characteristic spectral pattern of MI. Time course and inhibitor studies demonstrated that the peptide patterns in the serum reflect the balance of disease-specific-protease and aminopeptidase activity ex vivo.

Amino Acid Sequence↗
PubMed2001

Microarrays: lost in a storm of data?

Microarray expression profiling is instrumental to our understanding of the function of the genome. Resolution of functionally relevant expression patterns will require the analysis of large data sets compiled from multiple investigators. For this and other reasons, I argue that it is crucial for array data to be publicly shared in a format as close to the 'raw data' as possible. Issues such as protection of intellectual property, ensuring quality of the data, and the format and timing for sharing array data are also discussed.

Animals↗
PubMed1993

Recent advances in structure and function of food proteins: QSAR approach.

QSAR (quantitative structure-activity relationship), widely used in chemistry with hydrophobic, electronic, and steric parameters as structural factors, was found to be appropriate for use with food proteins, despite the difficulty, due to the complexity in macromolecular structure, in defining the steric terms. Emulsifying ability was closely related to hydrophobicity, and incorporation of solubility to hydrophobicity as factors improved the R2 of regression analysis. Foaming activity required both hydrophobicity and other factors pertaining to the adsorption of proteins at the interface in order to obtain adequate foam lamella strength. Hydrophobicity as well as other factors relating to the intermolecular interactions, for example, Ca and SH are involved in thermally induced gelation. For breadmaking, although no extensive QSAR work had been carried out, the important function of high molecular glutenin subunits was confirmed, and, notably, the critical function of hydrophobicity in breadmaking also was demonstrated. PLS (partial least-squares regression) and neural networks classify more correctly than other multivariate techniques, thereby yielding higher r2 values in modeling and prediction. However, multiple regression analysis and PCR (principal component regression) also were found to be effective for modeling because the information useful in elucidating the mechanism of protein function could be readily obtained. A characteristic property of unsupervised learning techniques, especially PCS (principal component similarity analysis), in identifying influential factors in the function mechanisms was demonstrated.

Bread↗
PubMed1993

PERFILS: a program for the quantitative treatment of footprinting data.

PERFILS, a computer program written in Borland TurboPascal, performs quantitative analysis of footprinting experiments using any IBM PC or compatible microcomputer. The program uses the height of the bands obtained from densitometric scanning of footprinting autoradiographs to calculate a differential cleavage plot. Such a plot displays, on a logarithmic scale, the difference of susceptibility of a DNA fragment to DNase I, or any other cleaving agent, in the presence of any ligand versus the sequence. PERFILS calculates the fractional cleavage values for control and ligand, giving a table of values for each internucleotidic bond and rendering the differential cleavage plot in only a few seconds.

Algorithms↗