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Deleterious mutations in animal mitochondrial DNA.

A simple neutral model predicts that the ratio of non-synonymous to synonymous fixed differences between species will be the same as the ratio of non-synonymous to synonymous polymorphisms within species. This prediction is tested with existing mitochondrial datasets from 25 animal species. In slightly over half of the studies, the ratio of replacement to silent polymorphisms within species is significantly greater than the ratio of replacement to silent fixed differences between species. These observations are best explained by a substantial number of mildly deleterious amino acid mutations that contribute to heterozygosity but rarely become fixed.

Animals↗

Potential use of routine databases in health technology assessment.

OBJECTIVES: To develop criteria for classifying databases in relation to their potential use in health technology (HT) assessment and to apply them to a list of databases of relevance in the UK. To explore the extent to which prioritized databases could pick up those HTs being assessed by the National Coordinating Centre for Health Technology Assessment (NCCHTA) and the extent to which these databases have been used in HT assessment. To explore the validation of the databases and their cost. DATA SOURCES: Electronic databases. Key literature sources. Experienced users of routine databases. REVIEW METHODS: A 'first principles' examination of the data necessary for each type of HT assessment was carried out, supplemented by literature searches and a historical review. The principal investigators applied the criteria to the databases. Comments of the 'keepers' of the prioritized databases were incorporated. Details of 161 topics funded by the NHS R&D Health Technology Assessment (HTA) programme were reviewed iteratively by the principal investigators. Uses of databases in HTAs were identified by literature searches, which included the title of each prioritized database as a keyword. Annual reports of databases were examined and 'keepers' queried. The validity of each database was assessed using criteria based on a literature search and involvement by the authors in a national academic network. The costs of databases were established from annual reports, enquiries to 'keepers' of databases and 'guesstimates' based on cost per record. For assessing effectiveness, equity and diffusion, routine databases were classified into three broad groups: (1) group I databases, identifying both HTs and health states, (2) group II databases, identifying the HTs, but not a health state, and (3) group III databases, identifying health states, but not an HT. Group I datasets were disaggregated into clinical registries, clinical administrative databases and population-oriented databases. Group III were disaggregated into adverse event reporting, confidential enquiries, disease-only registers and health surveys. RESULTS: Databases in group I can be used not only to assess effectiveness but also to assess diffusion and equity. Databases in group II can only assess diffusion. Group III has restricted scope for assessing HTs, except for analysis of adverse events. For use in costing, databases need to include unit costs or prices. Some databases included unit cost as well as a specific HT. A list of around 270 databases was identified at the level of UK, England and Wales or England (over 1000 including Scotland, Wales and Northern Ireland). Allocation of these to the above groups identified around 60 databases with some potential for HT assessment, roughly half to group I. Eighteen clinical registers were identified as having the greatest potential although the clinical administrative datasets had potential mainly owing to their inclusion of a wide range of technologies. Only two databases were identified that could directly be used in costing. The review of the potential capture of HTs prioritized by the UK's NHS R&D HTA programme showed that only 10% would be captured in these databases, mainly drugs prescribed in primary care. The review of the use of routine databases in any form of HT assessment indicated that clinical registers were mainly used for national comparative audit. Some databases have only been used in annual reports, usually time trend analysis. A few peer-reviewed papers used a clinical register to assess the effectiveness of a technology. Accessibility is suggested as a barrier to using most databases. Clinical administrative databases (group Ib) have mainly been used to build population needs indices and performance indicators. A review of the validity of used databases showed that although internal consistency checks were common, relatively few had any form of external audit. Some comparative audit databases have data scrutinised by participating units. Issues around coverage and coding have, in general, received little attention. NHS funding of databases has been mainly for 'Central Returns' for management purposes, which excludes those databases with the greatest potential for HT assessment. Funding for databases was various, but some are unfunded, relying on goodwill. The estimated total cost of databases in group I plus selected databases from groups II and III has been estimated at pound 50 million or around 0.1% of annual NHS spend. A few databases with limited potential for HT assessment account for the bulk of spending. CONCLUSIONS: Suggestions for policy include clarification of responsibility for the strategic development of databases, improved resourcing, and issues around coding, confidentiality, ownership and access, maintenance of clinical support, optimal use of information technology, filling gaps and remedying deficiencies. Recommendations for researchers include closer policy links between routine data and R&D, and selective investment in the more promising databases. Recommended research topics include optimal capture and coding of the range of HTs, international comparisons of the role, funding and use of routine data in healthcare systems and use of routine database in trials and in modelling. Independent evaluations are recommended for information strategies (such as those around the National Service Frameworks and various collaborations) and for electronic patient and health records.

Biomedical Technology↗

Predicting membrane protein types using residue-pair models based on reduced similarity dataset.

An algorithm to predict the membrane protein types based on the multi-residue-pair effect in the Markov model is proposed. For a newly constructed dataset of 835 membrane proteins with very low sequence similarity, the overall prediction accuracy has been achieved as high as 81.1% and 71.7% in the resubstitution and jackknife test, respectively, for a prediction of type I single-pass, type II single-pass, multi-pass membrane proteins, lipid chain-anchored and GPI-anchored membrane proteins. The improvement of about 11% in the jackknife test can be achieved compared with the component-coupled algorithm merely based on the amino acid composition (AAC approach). The improvement is also confirmed on a high similarity dataset and the other extrapolating test. The result implies that designing more incisive analysis tools, one should develop algorithms based on the representative dataset with lower sequence similarity. The present algorithm is useful to expedite the determination of the types and functions of new membrane proteins and may be useful for the systematic analysis of functional genome data in a large scale. The computer program is available on request.

Algorithms↗

Extraction of correlated gene clusters from multiple genomic data by generalized kernel canonical correlation analysis.

MOTIVATION: A major issue in computational biology is the reconstruction of pathways from several genomic datasets, such as expression data, protein interaction data and phylogenetic profiles. As a first step toward this goal, it is important to investigate the amount of correlation which exists between these data. RESULTS: These methods are successfully tested on their ability to recognize operons in the Escherichia coli genome, from the comparison of three datasets corresponding to functional relationships between genes in metabolic pathways, geometrical relationships along the chromosome, and co-expression relationships as observed by gene expression data.

Algorithms↗

Empirical analysis of the STR profiles resulting from conceptual mixtures.

Samples containing DNA from two or more individuals can be difficult to interpret. Even ascertaining the number of contributors can be challenging and associated uncertainties can have dramatic effects on the interpretation of testing results. Using an FBI genotypes dataset, containing complete genotype information from the 13 Combined DNA Index System (CODIS) loci for 959 individuals, all possible mixtures of three individuals were exhaustively and empirically computed. Allele sharing between pairs of individuals in the original dataset, a randomized dataset and datasets of generated cousins and siblings was evaluated as were the number of loci that were necessary to reliably deduce the number of contributors present in simulated mixtures of four or less contributors. The relatively small number of alleles detectable at most CODIS loci and the fact that some alleles are likely to be shared between individuals within a population can make the maximum number of different alleles observed at any tested loci an unreliable indicator of the maximum number of contributors to a mixed DNA sample. This analysis does not use other data available from the electropherograms (such as peak height or peak area) to estimate the number of contributors to each mixture. As a result, the study represents a worst case analysis of mixture characterization. Within this dataset, approximately 3% of three-person mixtures would be mischaracterized as two-person mixtures and more than 70% of four-person mixtures would be mischaracterized as two- or three-person mixtures using only the maximum number of alleles observed at any tested locus.

Alleles↗

The application of new software tools to quantitative protein profiling via isotope-coded affinity tag (ICAT) and tandem mass spectrometry: II. Evaluation of tandem mass spectrometry methodologies for large-scale protein analysis, and the application of statistical tools for data analysis and interpretation.

Proteomic approaches to biological research that will prove the most useful and productive require robust, sensitive, and reproducible technologies for both the qualitative and quantitative analysis of complex protein mixtures. Here we applied the isotope-coded affinity tag (ICAT) approach to quantitative protein profiling, in this case proteins that copurified with lipid raft plasma membrane domains isolated from control and stimulated Jurkat human T cells. With the ICAT approach, cysteine residues of the two related protein isolates were covalently labeled with isotopically normal and heavy versions of the same reagent, respectively. Following proteolytic cleavage of combined labeled proteins, peptides were fractionated by multidimensional chromatography and subsequently analyzed via automated tandem mass spectrometry. Individual tandem mass spectrometry spectra were searched against a human sequence database, and a variety of recently developed, publicly available software applications were used to sort, filter, analyze, and compare the results of two repetitions of the same experiment. In particular, robust statistical modeling algorithms were used to assign measures of confidence to both peptide sequences and the proteins from which they were likely derived, identified via the database searches. We show that by applying such statistical tools to the identification of T cell lipid raft-associated proteins, we were able to estimate the accuracy of peptide and protein identifications made. These tools also allow for determination of the false positive rate as a function of user-defined data filtering parameters, thus giving the user significant control over and information about the final output of large-scale proteomic experiments. With the ability to assign probabilities to all identifications, the need for manual verification of results is substantially reduced, thus making the rapid evaluation of large proteomic datasets possible. Finally, by repeating the experiment, information relating to the general reproducibility and validity of this approach to large-scale proteomic analyses was also obtained.

Amino Acid Sequence↗

Determining the reliability of the Graf classification for hip dysplasia.

We sought to establish the levels of interrater reliability and intrarater reliability of the Graf classification among orthopaedic surgeons in their final training year and who learned the method by instructed teaching or self study. Using standard teaching material developed by Graf, two groups of senior orthopaedic residents at the same training level received structured teaching sessions (Group A, n = 2) or performed self study (Group B, n = 2). Interrater reliability and intrarater reliability were determined (Cohen's weighted kappa). Proportions of correctly rated sonograms were compared between groups, implications of misclassifications were analyzed, and sensitivity analyses were performed. Interrater reliability was 0.59 (95% CI = 0.32-0.85) for Group A, and 0.47 (95% CI = 0.14-0.79) for Group B. Intrarater reliability showed an overall kappa of 0.57 (95% CI = 0.35-0.78) in Group A, and 0.47 (95% CI = 0.19-0.75) in Group B. The proportion of correctly rated sonograms between groups was similar in the original dataset and in the sensitivity analysis. Misclassifications influencing treatment were infrequent; one patient would have received unwarranted treatment and three patients would not have received warranted treatment. The Graf classification showed moderate reliability. Using self study, it can be learned almost, but not quite as effectively as by a structured program.

Clinical Competence↗

Mining published lists of cancer related microarray experiments: identification of a gene expression signature having a critical role in cell-cycle control.

BACKGROUND: Routine application of gene expression microarray technology is rapidly producing large amounts of data that necessitate new approaches of analysis. The analysis of a specific microarray experiment profits enormously from cross-comparing to other experiments. This process is generally performed by numerical meta-analysis of published data where the researcher chooses the datasets to be analyzed based on assumptions about the biological relations of published datasets to his own data, thus severely limiting the possibility of finding surprising connections. Here we propose using a repository of published gene lists for the identification of interesting datasets to be subjected to more detailed numerical analysis. RESULTS: We have compiled lists of genes that have been reported as differentially regulated in cancer related microarray studies. We searched these gene lists for statistically significant overlaps with lists of genes regulated by the tumor suppressors p16 and pRB. We identified a highly significant overlap of p16 and pRB target genes with genes regulated by the EWS/FLI fusion protein. Detailed numerical analysis of these data identified two sets of genes with clearly distinct roles in the G1/S and the G2/M phases of the cell cycle, as measured by enrichment of Gene Ontology categories. CONCLUSION: We show that mining of published gene lists in the absence of numerical detail about gene expression levels constitutes a fast, easy to perform, widely applicable, and unbiased route towards the identification of biologically related gene expression microarray datasets.

Cell Cycle↗

Application of intraoperative 3D ultrasound during navigated tumor resection.

Intraoperative 3D ultrasound (3D-iUS) may enhance the quality of neuronavigation by adding information about brain shift and tumor remnants. The aim of our study was to prove the concept of 3D ultrasound on the basis of technical and human effects. A 3D-ultrasound navigation system consisting of a standard personal computer containing a video grabber card in combination with an optical tracking system (NDI Polaris) and a standard ultrasound device (Siemens Omnia) with a 7.5 MHz probe was used. 3D-iUS datasets were acquired after craniotomy, at different subsequent times of the procedure and overlaid with preoperative MRI. All patients underwent early postoperative 3D MRI including contrast agent within 24 hours after surgery. Acquisition of 3D iUS and the fusion with preoperative MRI was successful in 22/23 patients. The expenditure of time was at least 5 minutes for one intraoperative 3D US dataset. The technique was used three to seven times during surgery. The quality of the ultrasound images was superior in cases of metastasis, meningeoma and angioma over those in malignant glioma. Brain shifting ranged from 2-25 mm depending on localization and kind of tumor. A resection control was possible in 78%. All six neurosurgeons demonstrated a learning curve. The introduction of 3D ultrasound has increased the value of neuronavigation substantially, making it possible to update several times during surgery and minimize the problem of brain shift. Configuration of both the 3D iUS based on a standard ultrasound system and the MR navigation system is time- and especially cost-effective. Faster navigational datasets and more intuitive image-guided surgery enable novel and user-friendly display techniques.

Adult↗

Mixed effects models with bivariate and univariate association parameters for longitudinal bivariate binary response data.

When two binary responses are measured for each study subject across time, it may be of interest to model how the bivariate associations and marginal univariate risks involving the two responses change across time. To achieve such a goal, marginal models with bivariate log odds ratio and univariate logit components are extended to include random effects for all components. Specifically, separate normal random effects are specified on the log odds ratio scale for bivariate responses and on the logit scale for univariate responses. Assuming conditional independence given the random effects facilitates the modeling of bivariate associations across time with missing at random incomplete data. We fit the model to a dataset for which such structures are feasible: a longitudinal randomized trial of a cardiovascular educational program where the responses of interest are change in hypertension and hypercholestemia status. The proposed model is compared to a naive bivariate model that assumes independence between time points and univariate mixed effects logit models.

Biometry↗

Who tangos with GOA?-Use of Gene Ontology Annotation (GOA) for biological interpretation of '-omics' data and for validation of automatic annotation tools.

The number of large-scale experimental datasets generated from high-throughput technologies has grown rapidly. Biological knowledge resources such as the Gene Ontology Annotation (GOA) database, which provides high-quality functional annotation to proteins within the UniProt Knowledgebase, can play an important role in the analysis of such data. The integration of GOA with analytical tools has proved to aid the clustering, annotation and biological interpretation of such large expression datasets. GOA is also useful in the development and validation of automated annotation tools, in particular text-mining systems. The increasing interest in GOA highlights the great potential of this freely available resource to assist both the biological research and bioinformatics communities.

Animals↗

Using supervised fuzzy clustering to predict protein structural classes.

Prediction of protein classification is both an important and a tempting topic in protein science. This is because of not only that the knowledge thus obtained can provide useful information about the overall structure of a query protein, but also that the practice itself can technically stimulate the development of novel predictors that may be straightforwardly applied to many other relevant areas. In this paper, a novel approach, the so-called "supervised fuzzy clustering approach" is introduced that is featured by utilizing the class label information during the training process. Based on such an approach, a set of "if-then" fuzzy rules for predicting the protein structural classes are extracted from a training dataset. It has been demonstrated through two different working datasets that the overall success prediction rates obtained by the supervised fuzzy clustering approach are all higher than those by the unsupervised fuzzy c-means introduced by the previous investigators [C.T. Zhang, K.C. Chou, G.M. Maggiora. Protein Eng. (1995) 8, 425-435]. It is anticipated that the current predictor may play an important complementary role to other existing predictors in this area to further strengthen the power in predicting the structural classes of proteins and their other characteristic attributes.

Algorithms↗

Social relations or social capital? Individual and community health effects of bonding social capital.

Social capital has become one of the most popular topics in public health research in recent years. However, even after a decade of conceptual and empirical work on this subject, there is still considerable disagreement about whether bonding social capital is a collective resource that benefits communities or societies, or whether its health benefits are associated with people, their personal networks and support. Using data from the 2000 and 2002 Health Survey for England this study found that, in line with earlier research, personal levels of social support contribute to a better self-reported health status. The study also suggests that social capital is additionally important for people's health. In both datasets the aggregate social trust variable was significantly related to self-rated health before and after controlling for differences in socio-demographics and/or individual levels of social support. The results were corroborated in the second dataset with an alternative indicator of social capital. These results show that bonding social capital collectively contributes to people's self-rated health over and above the beneficial effects of personal social networks and support.

Adolescent↗

Relationship between mRNA stability and intron presence.

Introns were found to enhance almost every steps of gene expression except increasing mRNA stability. By analyzing the genome-wide data of mRNA stability published by someone previously, we found that human intron-containing genes have more stable mRNAs than intronless genes, and the Arabidopsis thaliana genes with the most unstable mRNAs have fewer introns than other genes in the genome. After controlling for mRNA length, we found mRNA stability is still positively correlated with intron number in human intron-containing genes. But in yeast Saccharomyces cerevisiae, two different datasets on mRNA half-life gave conflicting results. The components of messenger ribonucleoprotein particles recruited during intron splicing may be retained in cytoplasmic mRNPs and act as signals of mRNA stability or simply insulators to avoid mRNA degradation.

Arabidopsis↗

A control theoretic paradigm for cell signaling networks: a simple complexity for a sensitive robustness.

The fields of molecular biology and cell biology are being flooded with complex genomic and proteomic datasets of large dimensions. We now recognize that each molecule in the cell and tissue can no longer be viewed as an isolated entity. Instead, each molecule must be considered as one member of an interacting network. Consequently, there is an urgent need for mathematical models to understand the behavior of cell signaling networks in health and in disease.

Cell Physiological Phenomena↗

Streptomyces avermitilis sp. nov., nom. rev., a taxonomic home for the avermectin-producing streptomycetes.

The taxonomic status of 'Streptomyces avermitilis' strain MA-4680 was established using a polyphasic approach. Strain MA-4680 formed a distinct phyletic line in the 16S rDNA streptomycete tree, and it was evident from the almost complete 16S rDNA sequence data that it was most closely related to Streptomyces cinnabarinus, Streptomyces griseochromogenes, Streptomyces resistomycificus and Streptomyces viridochromogenes. However, strain MA-4680 was readily distinguished from the type strains of these species by using a range of phenotypic properties, notably morphological and pigmentation features. The combined genotypic and phenotypic datasets indicate that the organism forms a recognizable centre of variation within the genus Streptomyces. It is proposed that 'Streptomyces avermitilis' be formally recognized as a species of Streptomyces. The type strain is MA-4680(T) (ATCC 31267(T) = NCIMB 12804(T0 = NRRL 8165(T)).

Anthelmintics↗

SUMOsp: a web server for sumoylation site prediction.

Systematic dissection of the sumoylation proteome is emerging as an appealing but challenging research topic because of the significant roles sumoylation plays in cellular dynamics and plasticity. Although several proteome-scale analyzes have been performed to delineate potential sumoylatable proteins, the bona fide sumoylation sites still remain to be identified. Previously, we carried out a genome-wide analysis of the SUMO substrates in human nucleus using the putative motif psi-K-X-E and evolutionary conservation. However, a highly specific predictor for in silico prediction of sumoylation sites in any individual organism is still urgently needed to guide experimental design. In this work, we present a computational system SUMOsp--SUMOylation Sites Prediction, based on a manually curated dataset, integrating the results of two methods, GPS and MotifX, which were originally designed for phosphorylation site prediction. SUMOsp offers at least as good prediction performance as the only available method, SUMOplot, on a very large test set. We expect that the prediction results of SUMOsp combined with experimental verifications will propel our understanding of sumoylation mechanisms to a new level. SUMOsp has been implemented on a freely accessible web server at: http://bioinformatics.lcd-ustc.org/sumosp/.

Algorithms↗

State of the art techniques for preservation and reuse of hard copy electrocardiograms.

Baseline examinations and periodic reexaminations in longitudinal population studies, together with ongoing surveillance for morbidity and mortality, provide unique opportunities for seeking ways to enhance the value of electrocardiography (ECG) as an inexpensive and noninvasive tool for prognosis and diagnosis. We used newly developed optical ECG waveform recognition (OEWR) technique capable of extracting raw waveform data from legacy hard copy ECG recording. Hardcopy ECG recordings were scanned and processed by the OEWR algorithm. The extracted ECG datasets were formatted into a newly proposed, vendor-neutral, ECG XML data format. Oracle database was used as a repository for ECG records in XML format. The proposed technique for XML encapsulation of OEWR processed hard copy records resulted in an efficient method for inclusion of paper ECG records into research databases, thus providing their preservation, reuse and accession.

Algorithms↗