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At least 937 records · Page 52Linked to original sources

PubMed2004

Accuracy improvement for identifying translation initiation sites in microbial genomes.

MOTIVATION: At present the computational gene identification methods in microbial genomes have a high prediction accuracy of verified translation termination site (3' end), but a much lower accuracy of the translation initiation site (TIS, 5' end). The latter is important to the analysis and the understanding of the putative protein of a gene and the regulatory machinery of the translation. Improving the accuracy of prediction of TIS is one of the remaining open problems. RESULTS: In this paper, we develop a four-component statistical model to describe the TIS of prokaryotic genes. The model incorporates several features with biological meanings, including the correlation between translation termination site and TIS of genes, the sequence content around the start codon; the sequence content of the consensus signal related to ribosomal binding sites (RBSs), and the correlation between TIS and the upstream consensus signal. An entirely non-supervised training system is constructed, which takes as input a set of annotated coding open reading frames (ORFs) by any gene finder, and gives as output a set of organism-specific parameters (without any prior knowledge or empirical constants and formulas). The novel algorithm is tested on a set of reliable datasets of genes from Escherichia coli and Bacillus subtillis. MED-Start may correctly predict 95.4% of the start sites of 195 experimentally confirmed E.coli genes, 96.6% of 58 reliable B.subtillis genes. Moreover, the test results indicate that the algorithm gives higher accuracy for more reliable datasets, and is robust to the variation of gene length. MED-Start may be used as a postprocessor for a gene finder. After processing by our program, the improvement of gene start prediction of gene finder system is remarkable, e.g. the accuracy of TIS predicted by MED 1.0 increases from 61.7 to 91.5% for 854 E.coli verified genes, while that by GLIMMER 2.02 increases from 63.2 to 92.0% for the same dataset. These results show that our algorithm is one of the most accurate methods to identify TIS of prokaryotic genomes. AVAILABILITY: The program MED-Start can be accessed through the website of CTB at Peking University: http://ctb.pku.edu.cn/main/SheGroup/MED_Start.htm.

Algorithms↗

PubMed2005

A systematic approach for comprehensive T-cell epitope discovery using peptide libraries.

MOTIVATION: T-cell response to peptides bound on MHC Class I or Class II molecules is essential for immune recognition of pathogens. T-cells are activated by specific peptide epitopes that are determined within the antigen processing pathways and presented on the surface of other cells bound to MHC molecules. To determine which part of allergenic or pathogenic proteins can stimulate T-cells is important for the treatment of diseases. We sought to take advantage of the falling cost of synthetic, screening grade peptides, and devise a comprehensive, non-hypothesis-driven screen for T-cell epitopes. We were interested in the study of celiac disease (CD) and used the ELISPOT technique to perform a large number of T-cell assays. We therefore needed to compensate for the lack of statistical data analysis methods for ELISPOT assays. RESULTS: We describe a method to comprehensively screen for T-cell epitopes within a family or a group of proteins. We have implemented an algorithm to generate a set of unique short peptide sequences that incorporate all possible epitopes within a group of proteins. T-cell assays were performed in 96-well plates using the ELISPOT assay to screen for responses in CD patients against any epitopes in glutens. We describe a statistical model to fit the data and an Expectation Maximization algorithm to estimate the parameters of interest and analyze the resulting data. AVAILABILITY: Implementations of our algorithms in R or Perl are available at http://bioinf.wehi.edu.au/folders/immunol.

Algorithms↗

PubMed2004

RAxML-III: a fast program for maximum likelihood-based inference of large phylogenetic trees.

MOTIVATION: The computation of large phylogenetic trees with statistical models such as maximum likelihood or bayesian inference is computationally extremely intensive. It has repeatedly been demonstrated that these models are able to recover the true tree or a tree which is topologically closer to the true tree more frequently than less elaborate methods such as parsimony or neighbor joining. Due to the combinatorial and computational complexity the size of trees which can be computed on a Biologist's PC workstation within reasonable time is limited to trees containing approximately 100 taxa. RESULTS: In this paper we present the latest release of our program RAxML-III for rapid maximum likelihood-based inference of large evolutionary trees which allows for computation of 1.000-taxon trees in less than 24 hours on a single PC processor. We compare RAxML-III to the currently fastest implementations for maximum likelihood and bayesian inference: PHYML and MrBayes. Whereas RAxML-III performs worse than PHYML and MrBayes on synthetic data it clearly outperforms both programs on all real data alignments used in terms of speed and final likelihood values. Availability SUPPLEMENTARY INFORMATION: RAxML-III including all alignments and final trees mentioned in this paper is freely available as open source code at http://wwwbode.cs.tum/~stamatak CONTACT: stamatak@cs.tum.edu.

Algorithms↗

PubMed2006

Maximum likelihood inference of imprinting and allele-specific expression from EST data.

MOTIVATION: In a diploid organism the proportion of transcripts that are produced from the two parental alleles can differ substantially due, for example to epigenetic modification that causes complete or partial silencing of one parental allele or to cis acting polymorphisms that affect transcriptional regulation. Counts of SNP alleles derived from EST sequences have been used to identify both novel candidates for genomic imprinting as well as examples of genes with allelic differences in expression. RESULTS: We have developed a set of statistical models in a maximum likelihood framework that can make highly efficient use of public transcript data to identify genes with unequal representation of alternative alleles in cDNA libraries. We modelled both imprinting and allele-specific expression and applied the models to a large dataset of SNPs mapped to EST sequences. Using simulations, matched closely to real data, we demonstrate significantly improved performance over existing methods that have been applied to the same data. We further validated the power of this approach to detect imprinting using a set of known imprinted genes and inferred a set of candidate imprinted genes, several of which are in close proximity to known imprinted genes. We report evidence that there are undiscovered imprinted genes in known imprinted regions. Overall, more than half of the genes for which the most data are available show some evidence of allele-specific expression. AVAILABILITY: Software is available from the authors on request.

Alleles↗

PubMed2007

SNPchip: R classes and methods for SNP array data.

UNLABELLED: High-density single nucleotide polymorphism microarrays (SNP chips) provide information on a subject's genome, such as copy number and genotype (heterozygosity/homozygosity) at a SNP. While fluorescence in situ hybridization and karyotyping reveal many abnormalities, SNP chips provide a higher resolution map of the human genome that can be used to detect, e.g., aneuploidies, microdeletions, microduplications and loss of heterozygosity (LOH). As a variety of diseases are linked to such chromosomal abnormalities, SNP chips promise new insights for these diseases by aiding in the discovery of such regions, and may suggest targets for intervention. The R package SNPchip contains classes and methods useful for storing, visualizing and analyzing high density SNP data. Originally developed from the SNPscan web-tool, SNPchip utilizes S4 classes and extends other open source R tools available at Bioconductor. This has numerous advantages, including the ability to build statistical models for SNP-level data that operate on instances of the class, and to communicate with other R packages that add additional functionality. AVAILABILITY: The package is available from the Bioconductor web page at www.bioconductor.org. SUPPLEMENTARY INFORMATION: The supplementary material as described in this article (case studies, installation guidelines and R code) is available from http://biostat.jhsph.edu/~iruczins/publications/sm/

Models, Statistical↗

PubMed2026

transfactor: transcription factor activity estimation via probabilistic gene expression deconvolution.

Gene expression is a primary modality being studied to differentiate between biological cells. Contemporary single-cell studies simultaneously measure genome-wide transcription levels for thousands of individual cells in a single experiment. While the characterization of cell population differences has often occurred through differential gene expression analysis, tiny effect sizes become statistically significant when thousands of cells are available for each population, compromising biological interpretation. Moreover, these large studies have spurred the development of methods to infer gene regulatory networks (GRNs) directly from the data, and GRN databases are becoming more comprehensive. In this work, we propose a statistical model for gene expression measures and an inference method that leverage GRNs to deconvolve transcription factor (TF) activity from gene expression, by probabilistically assigning mRNA molecules to TFs. This shifts the paradigm from investigating gene expression differences to regulatory differences at the level of TF activity, aiding interpretation and allowing prioritization of a limited number of TFs responsible for significant contributions to the observed gene expression differences. The inferred TF activities result in intuitive prioritization of TFs in terms of the (difference in) estimated number of molecules they produce, in contrast to other widely used methods relying on arbitrary enrichment scores. Our model allows the incorporation of prior information on the regulatory potential between each TF and target gene and is able to deal with both repressing and activating interactions. We compare our approach to other TF activity estimation methods using two simulation experiments and two case studies. Single-cell RNA-sequencing; TF activity; bioinformatics; GRN.

Transcription Factors↗

PubMed1990

Prediction of malignant hyperthermia susceptibility: statistical evaluation of clinical signs.

The anaesthetic records of 61 patients who had experienced adverse reactions thought to be malignant hyperthermia (MH) were reviewed retrospectively to evaluate the diagnostic importance of clinical symptoms. Using the in vitro contracture test, 38 (62%) patients were identified as MH susceptible (MHS), the remainder showing normal test results (MHN). Generalized rigidity, ventricular arrhythmias, cyanosis and postoperative myoglobinuria were observed significantly more often in MHS patients. Median values of body temperature and creatine kinase serum concentrations were significantly greater in the MHS group. Masseter spasm and sinus tachycardia were as common in MHS as in MHN individuals. Statistical models using generalized rigidity, ventricular arrhythmias, cyanosis and fever exceeding 38 degrees C for prediction of MH showed a maximum sensitivity and specificity of 78% and thus are not acceptable for clinical use. For definitive diagnosis of MH, the well established in vitro contracture test remains essential.

Adolescent↗

PubMed1999

An appraisal of the Peer Assessment Rating (PAR) Index and a suggested new weighting system.

The PAR Index was developed to measure treatment outcome in orthodontics. Validity was improved by weighting the scores of some components to reflect their relative importance. However, the index still has limitations, principally due to the high weight assigned to overjet. Difficulties also arise from the application of one weighting system to all malocclusions, since occlusal features vary in importance in different classes of malocclusion. The present study examined PAR Index validity using orthodontic consultant assessments as the 'Gold standard' and clinical ranking of occlusal features and statistical modelling to derive a new weighting system, separate for each malocclusion class. Discriminant and regression analyses were used to derive new criteria for measuring treatment outcome. As a result a new and more sensitive method of assessment is suggested which utilizes a combination of point and percentage reductions in PAR scores. This was found to have better correlations with the 'Gold standard' than the PAR nomogram.

Dental Occlusion↗

PubMed1994

Mapping and analysis of dairy cattle quantitative trait loci by maximum likelihood methodology using milk protein genes as genetic markers.

Maximum likelihood methodology was used to estimate effects of both a marker gene and a linked quantitative trait locus (QTL) on quantitative traits in a segregating population. Two alleles were assumed for the QTL. In addition to the effects of genotypes at both loci on the mean of the quantitative trait, recombination frequency between the loci, frequency of the QTL alleles and the residual standard deviation were also estimated. Thus six parameters were estimated in addition to the marker genotype means. The statistical model was tested on simulated data, and used to estimate direct and linked effects of the milk protein genes, beta-lactoglobulin, kappa-casein, and beta-casein, on milk, fat, and protein production and fat and protein percent in the Dutch dairy cattle population. beta-Lactoglobulin had significant direct effects on milk yield and fat percent. kappa-Casein had significant direct effects on milk yield, protein percent and fat yield. beta-Casein had significant direct effects on milk yield, fat and protein percent and fat and protein yield. Linked QTL with significant effects on fat percent were found for kappa-casein and beta-casein. Since the beta-casein and kappa-casein genes are closely linked, it is likely that the same QTL was detected for those two markers. Further, a QTL with a significant effect on fat yield was found to be linked to kappa-casein and a QTL with a significant effect on protein yield was linked to beta-lactoglobulin.

Alleles↗

PubMed2001

Bayesian mapping of quantitative trait loci under complicated mating designs.

Quantitative trait loci (QTL) are easily studied in a biallelic system. Such a system requires the cross of two inbred lines presumably fixed for alternative alleles of the QTL. However, development of inbred lines can be time consuming and cost ineffective for species with long generation intervals and severe inbreeding depression. In addition, restriction of the investigation to a biallelic system can sometimes be misleading because many potentially important allelic interactions do not have a chance to express and thus fail to be detected. A complicated mating design involving multiple alleles mimics the actual breeding system. However, it is difficult to develop the statistical model and algorithm using the classical maximum-likelihood method. In this study, we investigate the application of a Bayesian method implemented via the Markov chain Monte Carlo (MCMC) algorithm to QTL mapping under arbitrarily complicated mating designs. We develop the method under a mixed-model framework where the genetic values of founder alleles are treated as random and the nongenetic effects are treated as fixed. With the MCMC algorithm, we first draw the gene flows from the founders to the descendants for each QTL and then draw samples of the genetic parameters. Finally, we are able to simultaneously infer the posterior distribution of the number, the additive and dominance variances, and the chromosomal locations of all identified QTL.

Analysis of Variance↗

PubMed2001

Probabilistic prediction of unknown metabolic and signal-transduction networks.

Regulatory networks provide control over complex cell behavior in all kingdoms of life. Here we describe a statistical model, based on representing proteins as collections of domains or motifs, which predicts unknown molecular interactions within these biological networks. Using known protein-protein interactions of Saccharomyces cerevisiae as training data, we were able to predict the links within this network with only 7% false-negative and 10% false-positive error rates. We also use Markov chain Monte Carlo simulation for the prediction of networks with maximum probability under our model. This model can be applied across species, where interaction data from one (or several) species can be used to infer interactions in another. In addition, the model is extensible and can be analogously applied to other molecular data (e.g., DNA sequences).

Amino Acid Motifs↗

PubMed2006

Neighborhood effects on the self-rated health of elders: uncovering the relative importance of structural and service-related neighborhood environments.

OBJECTIVES: The purpose of this study was to investigate the independent relationship between neighborhood context (characterized through age structure, economic conditions, service provision, and residential stability) and self-reported health among elders in one U.S. city. METHODS: By using multilevel statistical models, we examined the cross-sectional relationships between markers of neighborhood environment (derived from the 1980 U.S. Census and the Yellow Pages of the 1985 New Haven, Connecticut, telephone book) and self-rated health among elders. We used survey data from the 1985 New Haven Established Populations for Epidemiologic Studies of the Elderly, which comprised 1,926 elders nested within 28 census tracts. RESULTS: When controlled for individual age, gender, race, marital status, education, and income, neighborhood measures of percent poverty were positively associated with poor self-rated health (odds ratio [OR] = 1.09; 95% confidence interval [CI] = 1.02-1.17), whereas residential stability (OR = 0.90; 95% CI = 0.84-0.96) and concentration of elders (OR = 0.82; 95% CI = 0.72-0.94) were inversely associated with poor self-rated health. Neighborhood service density was not associated with self-rated health. DISCUSSION: We found support for the role of neighborhood structural context (reflected through measures of poverty, residential stability, and age-based demographic concentration) in predicting the health of elders. Density of neighborhood services did not appear to have an independent effect on the self-rated health of elders.

Aged↗

PubMed1992

A longitudinal analysis of factors related to survival in old age.

Data from a longitudinal study of the elderly in rural North Wales are used in an exploratory study of the relationships between very broadly defined social circumstances and longevity. A statistical modeling approach is adopted and has some nonroutine features necessitated by missing data on dates of death. A variety of demographic, socioeconomic, social network, quality-of-life, dependence, and health variables are found, individually, to be related to survival. Multivariate analysis demonstrated that many of these relationships are spurious and, in particular, there is no prima facie evidence that survival is affected by social networks or quality-of-life factors. However, socioeconomic factors emerge as important for the old elderly.

Aged↗

PubMed2004

Clinical trials in late life: new science in old paradigms.

This article, based on a Lawton Award Lecture, addresses the subject of the need to enhance the evidence base in our field in order to influence processes of policy development. Four issues are identified as critical to this: theory-driven targets of public health significance, use of appropriate and sophisticated approaches to research design and statistical modeling, development of instruments and measures, and conclusions that make a difference. Incentives are discussed with particular attention to regulatory approaches. A broad view of research is taken, with examples from studies of Alzheimer's disease and depression in late life. I conclude that new approaches to methodology will enhance our capacity to translate exciting new findings from the basic sciences into the development of therapeutics and that this will, in turn, enhance our capacity to inform the development of public policy.

Aged↗

PubMed1993

Seasons, temperature and coronary disease.

Using data from a community-based register of heart disease (the WHO MONICA Project) associations between daily temperature, rainfall and other seasonal effects were investigated in relation to fatal coronary events and non-fatal definite myocardial infarctions in an Australian population. Coronary events, both fatal and non-fatal, were 20-40% more likely to occur in winter and spring than at other times of the year. Coronary deaths were more likely to occur on days of low temperature (and to a much lesser extent, on days of high temperature). No differences were found between patterns of sudden and non-sudden deaths (those occurring later after the onset of symptoms) associated with weather conditions. Statistical models allowing simultaneously for longer-term seasonal effects and daily temperature effects suggested that both exist. These results suggest that avoiding temperature stress could lead to reductions in the annual peaks in coronary events.

Aged↗

PubMed1993

Birthplace as a risk factor in motor neurone disease and Parkinson's disease.

A proportional mortality study was conducted to determine if state of birth is a risk factor associated with motor neurone disease (MND) and Parkinson's disease (PD) using US death certificate information for 1981. State of birth was used as a surrogate variable for location of early childhood environment. A gradient of risk by geographical area in the US was found for MND and PD. Cerebral vascular accident (CVA) deaths served as a comparison group. Multiple sclerosis (MS) deaths were analysed to validate the methods used. A geographical relationship between latitude proportional mortality ratios for MND, PD and MS by state of birth, and a geographical relationship between latitude and proportional mortality ratios for MND and MS by state of birth were found. Statistical modelling was used to compare the deaths from MND, PD, MS, CVA to all other deaths in the US by state of birth. The resulting models were evaluated to determine if any individual states were not well represented by the model for each disease. As predicted, no pattern was evident for CVA. The geographical gradient observed for MS was as predicted by other studies. The geographical pattern found for MND has a northwest to southeast gradient and the pattern found for PD has a west to east gradient.

Cause of Death↗

PubMed1992

Maternal depression, assessment methods, and physical symptoms affect estimates of depressive symptomatology among children with cancer.

Investigated the incidence of depressive symptoms and their covariates in a sample of 99 children undergoing treatment for cancer and their mothers. Although the prevalence of depressive symptoms falling within the clinical range was low (7 to 8%), classification of these children was highly dependent upon the informant and instrument used. Interrater reliabilities did not differ from chance levels. Separate multiple regression analyses of the mother's and nurse's ratings of the child's level of depression, the child's self-report on the Child Depression Inventory, and the mother's responses to the Child Behavior Checklist depression scales revealed different statistical models for each method of assessment. However, increased severity of the mother's self-report of depressive symptoms on the Beck Depression Inventory, which was predicted by low perceived social support and hospitalization of her child, was associated with higher levels of child depression on all child- and parent-report measures. Parental adjustment, sociodemographic, and medical factors as well as methods of assessment must be addressed by models explaining the etiology of depressive symptoms among pediatric oncology patients.

Adult↗

PubMed1990

Statistical analysis of nucleotide sequences.

In order to scan nucleic acid databases for potentially relevant but as yet unknown signals, we have developed an improved statistical model for pattern analysis of nucleic acid sequences by modifying previous methods based on Markov chains. We demonstrate the importance of selecting the appropriate parameters in order for the method to function at all. The model allows the simultaneous analysis of several short sequences with unequal base frequencies and Markov order k not equal to 0 as is usually the case in databases. As a test of these modifications, we show that in E. coli sequences there is a bias against palindromic hexamers which correspond to known restriction enzyme recognition sites.

Base Sequence↗