MITOP: database for mitochondria-related proteins, genes and diseases.

The MITOP database http://websvr.mips.biochem.mpg. de/proj/medgen/mitop/ consolidates information on both nuclear- and mitochondrial-encoded genes and their proteins. The five species files- Saccharomyces cerevisiae, Mus musculus, Caenorhabditis elegans, Neurospora crassa and Homo sapiens -include annotated data derived from a variety of online resources and the literature. A wide spectrum of search facilities is given in the interelated sections 'Gene catalogues', 'Protein catalogues', 'Homologies', 'Pathways and metabolism', and 'Human disease catalogue' including extensive references and hyperlinks for each entry. Precomputed FASTA searches using all the MITOP yeast protein entries and a list of the best EST hits with graphical cluster alignments related to the yeast reference sequence are presented. The MITOP orthologue tables with cross-listing to all the protein entries for each species in the database facilitate investigations into interspecies homology. A program (MITOPROT) is available to identify mitochondrial targeting sequences and graphical depictions of several important mitochondrial processes are included. The 'Human disease catalogue' lists a total of 101 disorders related to mitochondrial protein abnormalities, sorted by clinical criteria and age of onset.     

RNA secondary structure as a reusable interface to biological information resources

The dissemination of biological information has become critically dependent on the Internet and World Wide Web (WWW), which enable distributed access to information in a platform independent manner. The mode of interaction between biologists and on-line information resources, however, has been mostly limited to simple interface technologies such has hypertext links, tables and forms. The introduction of platform-independent runtime environments facilitates the development of more sophisticated WWW-based user interfaces. Until recently, most such interfaces have been tightly coupled to the underlying computation engines, and not separated as reusable components. We believe that many subdisciplines of biology have intuitive and familiar graphical representations of knowledge that can serve as multipurpose user interface elements. We call such graphical idioms “domain graphics”. In order to illustrate the power of such graphics, we have built a reusable interface based on the standard two dimensional (2D) layout of RNA secondary structure. The interface can be used to represent any pre-computed layout of RNA, and takes as a parameters the sets of actions to be performed as a user interacts with the interface. It can provide to any associated application program information about the base, helix, or subsequence selected by the user. We show the versatility of this interface by using it as a special purpose interface to BLAST, Medline and the RNA MFOLD search/compute engines. These demonstrations are available at: ir|url|http://www-smi.stanford.edu/projects/helix/pubs/ gene-combis-96/     

MITOP, the mitochondrial proteome database: 2000 update

MITOP (http://www.mips.biochem.mpg.de/proj/medgen/mitop/) is a comprehensive database for genetic and functional information on both nuclear- and mitochondrial-encoded proteins and their genes. The five species files--Saccharomyces cerevisiae, Mus musculus, Caenorhabditis elegans, Neurospora crassa and Homo sapiens--include annotated data derived from a variety of online resources and the literature. A wide spectrum of search facilities is given in the overlapping sections 'Gene catalogues', 'Protein catalogues', 'Homologies', 'Pathways and metabolism' and 'Human disease catalogue' including extensive references and hyperlinks to other databases. Central features are the results of various homology searches, which should facilitate the investigations into interspecies relationships. Precomputed FASTA searches using all the MITOP yeast protein entries and a list of the best human EST hits with graphical cluster alignments related to the yeast reference sequence are presented. The orthologue tables with cross-listings to all the protein entries for each species in MITOP have been expanded by adding the genomes of Rickettsia prowazeckii and Escherichia coli. To find new mitochondrial proteins the complete yeast genome has been analyzed using the MITOPROT program which identifies mitochondrial targeting sequences. The 'Human disease catalogue' contains tables with a total of 110 human diseases related to mitochondrial protein abnormalities, sorted by clinical criteria and age of onset. MITOP should contribute to the systematic genetic characterization of the mitochondrial proteome in relation to human disease.     

The arithmetic mean of ratio-normalized experiments overestimates the true E/C ratio

Biological assays often suffer from large systematic variation between sets of experiments. This variation is sometimes countered by normalizing the results of an "exposed" (E) experiment to that of a simultaneously performed "control" (C). We demonstrate that the arithmetic mean of such ratios overestimates the "true" E/C ratio. Fortunately, the overestimation may be calculated from experimentally accessible information, and it is generally possible to correct for this factor using formulas presented in this paper. We have studied the impact of this effect on a set of studies in the bioelectromagnetics literature and find that, although most results are weakened by the correction, few are significantly altered. Some of the papers used for our literature study are controversial; we believe that the present study may strengthen the quoted results by removing doubts about the statistical treatment of E/C ratios. Both false positives and negatives are possible if the proper correction is not made to the arithmetic mean of a set of E/C data. Realistic examples of erroneous statistical conclusions demonstrate that this is a real concern for E/C data which are marginal in both magnitude (mean < 2) and variance (standard deviation > 0.5).     

Goodness-of-fit methods for generalized linear mixed models

We develop graphical and numerical methods for checking the adequacy of generalized linear mixed models (GLMMs). These methods are based on the cumulative sums of residuals over covariates or predicted values of the response variable. Under the assumed model, the asymptotic distributions of these stochastic processes can be approximated by certain zero-mean Gaussian processes, whose realizations can be generated through Monte Carlo simulation. Each observed process can then be compared, both visually and analytically, to a number of realizations simulated from the null distribution. These comparisons enable one to assess objectively whether the observed residual patterns reflect model misspecification or random variation. The proposed methods are particularly useful for checking the functional form of a covariate or the link function. Extensive simulation studies show that the proposed goodness-of-fit tests have proper sizes and are sensitive to model misspecification. Applications to two medical studies lead to improved models.     

Detection of associations between diseases in animal carcinogenicity experiments

We present a statistical test for the hypothesis of independence of two disease processes in animal carcinogenicity experiments. It is assumed that the diseases are occult (detectable only at death via necropsy), and progressive, in that each passes (potentially) through three states in each animal: absent, nonlethally present, and lethally present. The test is based on the combination of statistics from a series of age-stratified 3 x 3 tables in which the animals that die in each age interval are cross-classified into one of these three states for each disease. This test utilizes all the data, whether obtained by sacrifice or by "natural death." It avoids the biases due to lethality noted by Breslow et al. (1974, Journal of the National Cancer Institute 52, 233-239) for the test based on age-stratified 2 x 2 tables, where the nonlethal and lethal occurrences are pooled. In a simulation experiment, we show that such biases (which usually conceal true positive associations and produce spurious negative associations) can be very severe indeed, whereas our test preserves the nominal significance level quite well. The power of the test appears to vary widely, depending on the incidence, time to onset, and rate of progression of each disease. As an example of the application of our method, we assess the association between liver tumors and reticulum cell sarcoma in a radiocarcinogenesis experiment involving approximately 1,000 C3H female mice.     

Data quality assessment of ungated flow cytometry data in high throughput experiments.

BACKGROUND: The recent development of semiautomated techniques for staining and analyzing flow cytometry samples has presented new challenges. Quality control and quality assessment are critical when developing new high throughput technologies and their associated information services. Our experience suggests that significant bottlenecks remain in the development of high throughput flow cytometry methods for data analysis and display. Especially, data quality control and quality assessment are crucial steps in processing and analyzing high throughput flow cytometry data. METHODS: We propose a variety of graphical exploratory data analytic tools for exploring ungated flow cytometry data. We have implemented a number of specialized functions and methods in the Bioconductor package rflowcyt. We demonstrate the use of these approaches by investigating two independent sets of high throughput flow cytometry data. RESULTS: We found that graphical representations can reveal substantial nonbiological differences in samples. Empirical Cumulative Distribution Function and summary scatterplots were especially useful in the rapid identification of problems not identified by manual review. CONCLUSIONS: Graphical exploratory data analytic tools are quick and useful means of assessing data quality. We propose that the described visualizations should be used as quality assessment tools and where possible, be used for quality control.     

Condor-COPASI: high-throughput computing for biochemical networks

ABSTRACT: BACKGROUND: Mathematical modelling has become a standard technique to improve our understanding of complex biological systems. As models become larger and more complex, simulations and analyses require increasing amounts of computational power. Clusters of computers in a high-throughput computing environment can help to provide the resources required for computationally expensive model analysis. However, exploiting such a system can be difficult for users without the necessary expertise. RESULTS: We present Condor-COPASI, a server-based software tool that integrates COPASI, a biological pathway simulation tool, with Condor, a high-throughput computing environment. Condor-COPASI provides a web-based interface, which makes it extremely easy for a user to run a number of model simulation and analysis tasks in parallel. Tasks are transparently split into smaller parts, and and submitted for execution on a Condor pool. Result output is presented to the user in a number of formats, including tables and interactive graphical displays. CONCLUSIONS: Condor-COPASI can effectively use a Condor high-throughput computing environment to provide significant gains in performance for a number of model simulation and analysis tasks. Condor-COPASI is free, open source software, released under the Artistic License 2.0, and is suitable for use by any institution with access to a Condor pool. Source code is freely available for download at http://code.google.com/p/condor-copasi/, along with full instructions on deployment and usage.     

LaTcOm: a web server for visualizing rare codon clusters in coding sequences

We present LaTcOm, a new web tool, which offers several alternative methods for 'rare codon cluster' (RCC) identification from a single and simple graphical user interface. In the current version, three RCC detection schemes are implemented: the recently described %MinMax algorithm and a simplified sliding window approach, along with a novel modification of a linear-time algorithm for the detection of maximally scoring subsequences tailored to the RCC detection problem. Among a number of user tunable parameters, several codon-based scales relevant for RCC detection are available, including tRNA abundance values from Escherichia coli and several codon usage tables from a selection of genomes. Furthermore, useful scale transformations may be performed upon user request (e.g. linear, sigmoid). Users may choose to visualize RCC positions within the submitted sequences either with graphical representations or in textual form for further processing. AVAILABILITY: LaTcOm is freely available online at the URL http://troodos.biol.ucy.ac.cy/latcom.html.     

A note on the Wilcoxon-Mann-Whitney test for 2 X kappa ordered tables

Biological and medical investigations often use ordered categorical data. When two groups are to be compared and the data for the groups fall in three or more ordered categories, the Wilcoxon-Mann-Whitney (WMW) test uses information in the ordering to give a test that is usually powerful against shift alternatives. However, such applications of WMW often involve distributions for which extensive ties play an important role. Newly available computer programs for performing exact tests give deeper insights into the characteristics of the exact WMW distributions and the suitability of normal approximations. We offer practical advice, based on experience with published biomedical data sets and on numerical studies of hypothetical ordered tables, for the use of WMW and its normal approximations.     

Graphical representation of a generalized linear model-based statistical test estimating the fit of the single-hit Poisson model to limiting dilution assays.

Standardized statistical and graphical methods for analysis of limiting dilution assays are highly desirable to enable investigators to compare and interpret results and conclusions with greater accuracy and precision. According to these requirements, we present in this work a powerful statistical slope test that estimates the fit of the single-hit Poisson model to limiting dilution experiments. This method is readily amenable to a graphical representation. This slope test is obtained by modeling limiting dilution data according to a linear log-log regression model, which is a generalized linear model specially designed for modeling binary data. The result of the statistical slope test can then be graphed to visualize whether the data are compatible or not with the single-hit Poisson model. We demonstrate this statistical test and its graphical representation by using two examples: a real limiting dilution experiment evaluating the growth frequency of IL-2-responsive tumor-infiltrating T cells in a malignant lymph node involved by a B cell non-Hodgkin's lymphoma, and a simulation of a limiting dilution assay corresponding to a theoretical non-single-hit Poisson model, suppressor two-target Poisson model.     

Effects of species evenness can be derived from species richness – ecosystem functioning relationships

Although species richness effects on ecosystem functioning have been studied thoroughly in countless experiments, the effects of the other side of diversity – species evenness – remain less identified, especially at high species richness. Due to the large number of different model ecosystems that need to be created, the explanatory power of the experimental approach for evenness is indeed limited. We show here that experimental studies on the influence of species richness on ecosystem functions contain hidden information on the influence of species evenness. Both the effects of maximum and minimum evenness, and of a key set of intermediate evenness levels, can be derived from species richness – ecosystem function curves, and that for every richness level, by using communities with low species richness as the equivalent of highly uneven communities with higher richness. We show that evenness effects on ecosystem functioning have the same direction as richness effects, however with increasing effect sizes at higher richness levels. We validated our technique for a wide range of ecosystem functions and applied it to the species richness – community biomass data from an existing biodiversity experiment. Our approach could provide a fast and easy alternative to resource‐intensive experiments in which evenness is experimentally varied, as we can build on the elaborate existing literature on species richness to assess its effects.     

Protein glycosylation analysis with capillary-based electromigrative separation techniques

An impressive complexity is associated with glycoproteins due to the microheterogeneity of glycosylation as posttranslational modification giving rise to a vast number of isoforms. The full characterization of glycoproteins is difficult to achieve, and a number of analytical methods have to be combined for a detailed understanding of glycosylation. In this review, we focus on capillary electromigrative separation techniques in the formats capillary electrophoresis, micellar electrokinetic chromatography, and capillary sieving electrophoresis. These separation techniques can be applied to all levels of glycosylation analysis including intact glycoproteins, glycopeptides, and released glycans. We here discuss the separation characteristics for each method and the information that they can provide for each level. Detection issues, especially laser-induced fluorescence detection and mass spectrometry are taken into account. In addition, tables provide an overview on the achievements made from the very beginning of glycosylation research by electromigrative separation techniques. From the literature presented here it is clear, that glycosylation analysis by electromigrative separation techniques is on the edge of transition of basic research and method development towards applications. First proof-of-principle studies for in-depth glycoprotein characterization and clinical diagnosis are described. However, this overview also shows that many basic aspects of separation have not yet been fully understood and more research is necessary to be able to fully use the capabilities of electromigrative separation techniques.     

AssociationDB: web-based exploration of genomic association

Genome-wide association studies use hundreds of thousands of markers making it challenging to present and finally interpret the results. We developed a graphical, web-based solution for an interactive exploration of the results of case-control studies, with a tight integration of related gene information and tissue-specific expression data. Association results are presented as physical position-based vertical bars with known genes included as horizontal bars at their respective physical positions. The interface allows the specification of filtering criteria for the association data and highlights potentially interesting genes with user-specified terms occurring in their reports or with relevant expression patterns. Pop-up windows and hyperlinks provide drill-down capabilities and quick access to relevant data AssociationDB can either be used as a stand-alone solution or as a front-end joining association results obtained by other software with genomic information.     

Establishing appropriate genome-wide significance levels for canine linkage analyses

A threshold of 3.3 for a genome-wide maximum LOD score (MAXLOD) has been demonstrated in human linkage studies as corresponding to a type I error rate of 5%. Generalization of this work to other species assumes the presence of an infinitely dense marker map. While this assumption is increasingly realistic for the human genome, it may be unrealistic for the dog genome. In this study we establish the analytic and empirical thresholds for MAXLOD in canine linkage studies corresponding to type I error rates of 5% and 1% for autosomal traits. Empirical thresholds are computed via simulation assuming a 10 cM map with no fine mapping performed. Pedigree structures for simulations were drawn from two canine disease studies. Five thousand replicates of genome-wide null genotype data were simulated and analyzed for each disease. We determined that MAXLOD thresholds of 3.2 and 2.7 correspond to analytic and empirical type I error rates of 5%, respectively. In all cases, the MAXLOD thresholds from simulations were always at least 0.5 LOD units below the corresponding analytic thresholds. We therefore recommend that a threshold of 3.2 be used for canine linkage studies when fine mapping is performed, and that researchers perform their own simulation studies to assess genome-wide empirical significance levels when no fine mapping is performed.     

The minimum information required for reporting a molecular interaction experiment (MIMIx)

A wealth of molecular interaction data is available in the literature, ranging from large-scale datasets to a single interaction confirmed by several different techniques. These data are all too often reported either as free text or in tables of variable format, and are often missing key pieces of information essential for a full understanding of the experiment. Here we propose MIMIx, the minimum information required for reporting a molecular interaction experiment. Adherence to these reporting guidelines will result in publications of increased clarity and usefulness to the scientific community and will support the rapid, systematic capture of molecular interaction data in public databases, thereby improving access to valuable interaction data.     

Separation of Respiratory Influences from the Tachogram: A Methodological Evaluation

The variability of the heart rate (HRV) is widely studied as it contains information about the activity of the autonomic nervous system (ANS). However, HRV is influenced by breathing, independently of ANS activity. It is therefore important to include respiratory information in HRV analyses in order to correctly interpret the results. In this paper, we propose to record respiratory activity and use this information to separate the tachogram in two components: one which is related to breathing and one which contains all heart rate variations that are unrelated to respiration. Several algorithms to achieve this have been suggested in the literature, but no comparison between the methods has been performed yet. In this paper, we conduct two studies to evaluate the methods'' performances to accurately decompose the tachogram in two components and to assess the robustness of the algorithms. The results show that orthogonal subspace projection and an ARMAX model yield the best performances over the two comparison studies. In addition, a real-life example of stress classification is presented to demonstrate that this approach to separate respiratory information in HRV studies can reveal changes in the heart rate variations that are otherwise masked by differing respiratory patterns.