bluuebunny/crossref_metadata_2025 huggingface dataset:
Locomotif: from graphical motif description to RNA motif search
Authors: Reeder Janina , Reeder Jens , Giegerich Robert
Published: July 2007

Motivation and Results: Motivated by the recent rise of interest in small regulatory RNAs, we present Locomotif—a new approach for locating RNA motifs that goes beyond the previous ones in three ways: (1) motif search is based on efficient dynamic programming algorithms, incorporating the established thermodynamic model of RNA secondary structure formation. (2) motifs are described graphically, using a Java-based editor, and search algorithms are derived from the graphics in a fully automatic way. The editor allows us to draw secondary structures, annotated with size and sequence information. They closely resemble the established, but informal way in which RNA motifs are communicated in the literature. Thus, the learning effort for Locomotif users is minimal. (3) Locomotif employs a client-server approach. Motifs are designed by the user locally. Search programs are generated and compiled on a bioinformatics server. They are made available both for execution on the server, and for download as C source code plus an appropriate makefile.

Availability: Locomotif is available at http://bibiserv.techfak.uni-bielefeld.de/locomotif

Contact: robert@techfak.uni-bielefeld.de
Nucleotide variation of regulatory motifs may lead to distinct expression patterns
Authors: Segal Liat , Lapidot Michal , Solan Zach , Ruppin Eytan , Pilpel Yitzhak , Horn David
Published: July 2007

Motivation: Current methodologies for the selection of putative transcription factor binding sites (TFBS) rely on various assumptions such as over-representation of motifs occurring on gene promoters, and the use of motif descriptions such as consensus or position-specific scoring matrices (PSSMs). In order to avoid bias introduced by such assumptions, we apply an unsupervised motif extraction (MEX) algorithm to sequences of promoters. The extracted motifs are assessed for their likely cis-regulatory function by calculating the expression coherence (EC) of the corresponding genes, across a set of biological conditions.

Results: Applying MEX to all Saccharomyces cerevisiae promoters, followed by EC analysis across 40 biological conditions, we obtained a high percentage of putative cis-regulatory motifs. We clustered motifs that obtained highly significant EC scores, based on both their sequence similarity and similarity in the biological conditions these motifs appear to regulate. We describe 20 clusters, some of which regroup known TFBS. The clusters display different mRNA expression profiles, correlated with typical changes in the nucleotide composition of their relevant motifs. In several cases, a variation of a single nucleotide is shown to lead to distinct differences in expression patterns. These results are confronted with additional information, such as binding of transcription factors to groups of genes. Detailed analysis is presented for clusters related to MCB/SCB, STRE and PAC. In the first two cases, we provide evidence for different binding mechanisms of different clusters of motifs. For PAC-related motifs we uncover a new cluster that has so far been overshadowed by the stronger effects of known PAC motifs.

Contact: horn@tau.ac.il

Supplementary information: Supplementary data are available at http://adios.tau.ac.il/regmotifs and at Bioinformatics online.
Negation of protein–protein interactions: analysis and extraction
Authors: Sanchez-Graillet Olivia , Poesio Massimo
Published: July 2007

Motivation: Negative information about protein–protein interactions—from uncertainty about the occurrence of an interaction to knowledge that it did not occur—is often of great use to biologists and could lead to important discoveries. Yet, to our knowledge, no proposals focusing on extracting such information have been proposed in the text mining literature.

Results: In this work, we present an analysis of the types of negative information that is reported, and a heuristic-based system using a full dependency parser to extract such information. We performed a preliminary evaluation study that shows encouraging results of our system. Finally, we have obtained an initial corpus of negative protein–protein interactions as basis for the construction of larger ones.

Availability: The corpus is available by request from the authors.

Contact: osanch@essex.ac.uk or poesio@essex.ac.uk
Probabilistic whole-genome alignments reveal high indel rates in the human and mouse genomes
Authors: Lunter Gerton
Published: July 2007

Motivation: The two mutation processes that have the largest impact on genome evolution at small scales are substitutions, and sequence insertions and deletions (indels). While the former have been studied extensively, indels have received less attention, and in particular, the problem of inferring indel rates between pairs of divergent sequence remains unsolved. Here, I describe a novel and accurate method for estimating neutral indel rates between divergent pairs of genomes.

Results: Simulations suggest that new method for estimating indel rates is accurate to within 2%, at divergences corresponding to that of human and mouse. Applying the method to these species, I show that indel rates are up to twice higher than is apparent from alignments, and depend strongly on the local G + C content. These results indicate that at these evolutionary distances, the contribution of indels to sequence divergence is much larger than hitherto appreciated. In particular, the ratio of substitution to indel rates between human and mouse appears to be around γ = 8, rather than the currently accepted value of about γ = 14.

Contact: Gerton.lunter@dpag.ox.ac.uk
Anisotropic fluctuations of amino acids in protein structures: insights from X-ray crystallography and elastic network models
Authors: Eyal Eran , Chennubhotla Chakra , Yang Lee-Wei , Bahar Ivet
Published: July 2007

Motivation: A common practice in X-ray crystallographic structure refinement has been to model atomic displacements or thermal fluctuations as isotropic motions. Recent high-resolution data reveal, however, significant departures from isotropy, described by anisotropic displacement parameters (ADPs) modeled for individual atoms. Yet, ADPs are currently reported for a limited set of structures, only.

Results: We present a comparative analysis of the experimentally reported ADPs and those theoretically predicted by the anisotropic network model (ANM) for a representative set of structures. The relative sizes of fluctuations along different directions are shown to agree well between experiments and theory, while the cross-correlations between the (x-, y- and z-) components of the fluctuations show considerable deviations. Secondary structure elements and protein cores exhibit more robust anisotropic characteristics compared to disordered or flexible regions. The deviations between experimental and theoretical data are comparable to those between sets of experimental ADPs reported for the same protein in different crystal forms. These results draw attention to the effects of crystal form and refinement procedure on experimental ADPs and highlight the potential utility of ANM calculations for consolidating experimental data or assessing ADPs in the absence of experimental data.

Availability: The ANM server at http://www.ccbb.pitt.edu/anm is upgraded to permit users to compute and visualize the theoretical ADPs for any PDB structure, thus providing insights into the anisotropic motions intrinsically preferred by equilibrium structures.

Contact: bahar@ccbb.pitt.edu

Supplementary information: Two Supplementary Material files can be accessed at the journal website. The first presents the tabulated results from computations (Pearson correlations and KL distances with respect to experimental ADPs) reported for each of the 93 proteins in Set I (the averages over all proteins are presented above in Table 3). The second file consists of three sections: (A) detailed derivation of Equation (7), (B) analysis of the effect of ANM parameters on computed ADPs and identification of parameters that achieve optimal correlation with experiments and (C) description of the method for computing the tangential and radial components of equilibrium fluctuations.
SNP mining porcine ESTs with MAVIANT, a novel tool for SNP evaluation and annotation
Authors: Panitz Frank , Stengaard Henrik , Hornshøj Henrik , Gorodkin Jan , Hedegaard Jakob , Cirera Susanna , Thomsen Bo , Madsen Lone B. , Høj Anette , Vingborg Rikke K. , Zahn Bujie , Wang Xuegang , Wang Xuefei , Wernersson Rasmus , Jørgensen Claus B. , Scheibye-Knudsen Karsten , Arvin Troels , Lumholdt Steen , Sawera Milena , Green Trine , Nielsen Bente J. , Havgaard Jakob H. , Brunak Søren , Fredholm Merete , Bendixen Christian
Published: July 2007

Motivation: Single nucleotide polymorphisms (SNPs) analysis is an important means to study genetic variation. A fast and cost-efficient approach to identify large numbers of novel candidates is the SNP mining of large scale sequencing projects. The increasing availability of sequence trace data in public repositories makes it feasible to evaluate SNP predictions on the DNA chromatogram level. MAVIANT, a platform-independent Multipurpose Alignment VIewing and Annotation Tool, provides DNA chromatogram and alignment views and facilitates evaluation of predictions. In addition, it supports direct manual annotation, which is immediately accessible and can be easily shared with external collaborators.

Results: Large-scale SNP mining of polymorphisms bases on porcine EST sequences yielded more than 7900 candidate SNPs in coding regions (cSNPs), which were annotated relative to the human genome. Non-synonymous SNPs were analyzed for their potential effect on the protein structure/function using the PolyPhen and SIFT prediction programs. Predicted SNPs and annotations are stored in a web-based database. Using MAVIANT SNPs can visually be verified based on the DNA sequencing traces. A subset of candidate SNPs was selected for experimental validation by resequencing and genotyping. This study provides a web-based DNA chromatogram and contig browser that facilitates the evaluation and selection of candidate SNPs, which can be applied as genetic markers for genome wide genetic studies.

Availability: The stand-alone version of MAVIANT program for local use is freely available under GPL license terms at http://snp.agrsci.dk/maviant.

Contact: christian.bendixen@agrsci.dk

Supplementary information: Supplementary data are available at Bioinformatics online.
Using dynamic programming to create isotopic distribution maps from mass spectra
Authors: McIlwain Sean , Page David , Huttlin Edward L. , Sussman Michael R.
Published: July 2007

Motivation: This article presents a method to identify the isotopic distributions within a mass spectrum using a probabilistic classifier supplemented with dynamic programming. Such a system is needed for a variety of purposes, including generating robust and meaningful features from mass spectra to be used in classification.

Results: The primary result of this article is that the dynamic programming approach significantly improves sensitivity, without harming specificity, of a probabilistic classifier for identifying the isotopic distributions. When annotating isotopic distributions where an expert has performed the initial ‘peak-picking’ (removal of noise peaks), the dynamic programming approach gives a true positive rate of 96% and a false positive rate of 0.0%, whereas the classifier alone has a true positive rate of only 47% when the false positive rate is 0.0%. When annotating isotopic distributions in machine peak-picked spectra, which may contain many noise peaks, the dynamic programming approach gives a true positive rate of only 22.0%, but it still keeps a low false positive rate of 1.0% and still outperforms the classifier alone. It is important to note that all these rates are when we require exact matches with the distributions in annotated spectra; in our evaluation a distribution is considered ‘entirely incorrect’ if it is missing even one peak or contains even one extraneous peak. We compared to the THRASH and AID-MS systems using a looser requirement: correctly identifying the distribution that contains the mono-isotopic mass. Under this measure, our dynamic programming approach achieves a true positive rate of 82% and a false positive rate of 1%, which again outperforms the classifier alone. The dynamic programming approach ends up being more conservative than THRASH and AID-MS, yielding both fewer true and false peaks, but the F-score of the dynamic programming approach is significantly better than those of THRASH and AID-MS. All results were obtained with 10-fold cross-validation of 99 sections of mass spectra with a total of 214 hand-annotated isotopic distributions.

Availability: Programs are available via http://www.cs.wisc.edu/~mcilwain/IDM

Contact: mcilwain@cs.wisc.edu
Functional annotation of regulatory pathways
Authors: Pandey Jayesh , Koyutürk Mehmet , Kim Yohan , Szpankowski Wojciech , Subramaniam Shankar , Grama Ananth
Published: July 2007

Motivation: Standardized annotations of biomolecules in interaction networks (e.g. Gene Ontology) provide comprehensive understanding of the function of individual molecules. Extending such annotations to pathways is a critical component of functional characterization of cellular signaling at the systems level.

Results: We propose a framework for projecting gene regulatory networks onto the space of functional attributes using multigraph models, with the objective of deriving statistically significant pathway annotations. We first demonstrate that annotations of pairwise interactions do not generalize to indirect relationships between processes. Motivated by this result, we formalize the problem of identifying statistically overrepresented pathways of functional attributes. We establish the hardness of this problem by demonstrating the non-monotonicity of common statistical significance measures. We propose a statistical model that emphasizes the modularity of a pathway, evaluating its significance based on the coupling of its building blocks. We complement the statistical model by an efficient algorithm and software, Narada, for computing significant pathways in large regulatory networks. Comprehensive results from our methods applied to the Escherichia coli transcription network demonstrate that our approach is effective in identifying known, as well as novel biological pathway annotations.

Availability: Narada is implemented in Java and is available at http://www.cs.purdue.edu/homes/jpandey/narada/

Contact: jpandey@cs.purdue.edu
GPDTI: A Genetic Programming Decision Tree Induction method to find epistatic effects in common complex diseases
Authors: Estrada-Gil Jesús K. , Fernández-López Juan C. , Hernández-Lemus Enrique , Silva-Zolezzi Irma , Hidalgo-Miranda Alfredo , Jiménez-Sánchez Gerardo , Vallejo-Clemente Edgar E.
Published: July 2007

Motivation: The identification of risk-associated genetic variants in common diseases remains a challenge to the biomedical research community. It has been suggested that common statistical approaches that exclusively measure main effects are often unable to detect interactions between some of these variants. Detecting and interpreting interactions is a challenging open problem from the statistical and computational perspectives. Methods in computing science may improve our understanding on the mechanisms of genetic disease by detecting interactions even in the presence of very low heritabilities.

Results: We have implemented a method using Genetic Programming that is able to induce a Decision Tree to detect interactions in genetic variants. This method has a cross-validation strategy for estimating classification and prediction errors and tests for consistencies in the results. To have better estimates, a new consistency measure that takes into account interactions and can be used in a genetic programming environment is proposed. This method detected five different interaction models with heritabilities as low as 0.008 and with prediction errors similar to the generated errors.

Availability: Information on the generated data sets and executable code is available upon request.

Contact: jestrada@inmegen.gob.mx
Multiway analysis of epilepsy tensors
Authors: Acar Evrim , Aykut-Bingol Canan , Bingol Haluk , Bro Rasmus , Yener Bülent
Published: July 2007

Motivation: The success or failure of an epilepsy surgery depends greatly on the localization of epileptic focus (origin of a seizure). We address the problem of identification of a seizure origin through an analysis of ictal electroencephalogram (EEG), which is proven to be an effective standard in epileptic focus localization.

Summary: With a goal of developing an automated and robust way of visual analysis of large amounts of EEG data, we propose a novel approach based on multiway models to study epilepsy seizure structure. Our contributions are 3-fold. First, we construct an Epilepsy Tensor with three modes, i.e. time samples, scales and electrodes, through wavelet analysis of multi-channel ictal EEG. Second, we demonstrate that multiway analysis techniques, in particular parallel factor analysis (PARAFAC), provide promising results in modeling the complex structure of an epilepsy seizure, localizing a seizure origin and extracting artifacts. Third, we introduce an approach for removing artifacts using multilinear subspace analysis and discuss its merits and drawbacks.

Results: Ictal EEG analysis of 10 seizures from 7 patients are included in this study. Our results for 8 seizures match with clinical observations in terms of seizure origin and extracted artifacts. On the other hand, for 2 of the seizures, seizure localization is not achieved using an initial trial of PARAFAC modeling. In these cases, first, we apply an artifact removal method and subsequently apply the PARAFAC model on the epilepsy tensor from which potential artifacts have been removed. This method successfully identifies the seizure origin in both cases.

Contact: acare@cs.rpi.edu
An ensemble framework for clustering protein–protein interaction networks
Authors: Asur Sitaram , Ucar Duygu , Parthasarathy Srinivasan
Published: July 2007

Motivation: Protein–Protein Interaction (PPI) networks are believed to be important sources of information related to biological processes and complex metabolic functions of the cell. The presence of biologically relevant functional modules in these networks has been theorized by many researchers. However, the application of traditional clustering algorithms for extracting these modules has not been successful, largely due to the presence of noisy false positive interactions as well as specific topological challenges in the network.

Results: In this article, we propose an ensemble clustering framework to address this problem. For base clustering, we introduce two topology-based distance metrics to counteract the effects of noise. We develop a PCA-based consensus clustering technique, designed to reduce the dimensionality of the consensus problem and yield informative clusters. We also develop a soft consensus clustering variant to assign multifaceted proteins to multiple functional groups. We conduct an empirical evaluation of different consensus techniques using topology-based, information theoretic and domain-specific validation metrics and show that our approaches can provide significant benefits over other state-of-the-art approaches. Our analysis of the consensus clusters obtained demonstrates that ensemble clustering can (a) produce improved biologically significant functional groupings; and (b) facilitate soft clustering by discovering multiple functional associations for proteins.

Contact: srini@cse.ohio-state.edu

Supplementary information: Supplementary data are available at Bioinformatics online.
Gene selection via the BAHSIC family of algorithms
Authors: Song Le , Bedo Justin , Borgwardt Karsten M. , Gretton Arthur , Smola Alex
Published: July 2007

Motivation: Identifying significant genes among thousands of sequences on a microarray is a central challenge for cancer research in bioinformatics. The ultimate goal is to detect the genes that are involved in disease outbreak and progression. A multitude of methods have been proposed for this task of feature selection, yet the selected gene lists differ greatly between different methods. To accomplish biologically meaningful gene selection from microarray data, we have to understand the theoretical connections and the differences between these methods. In this article, we define a kernel-based framework for feature selection based on the Hilbert–Schmidt independence criterion and backward elimination, called BAHSIC. We show that several well-known feature selectors are instances of BAHSIC, thereby clarifying their relationship. Furthermore, by choosing a different kernel, BAHSIC allows us to easily define novel feature selection algorithms. As a further advantage, feature selection via BAHSIC works directly on multiclass problems.

Results: In a broad experimental evaluation, the members of the BAHSIC family reach high levels of accuracy and robustness when compared to other feature selection techniques. Experiments show that features selected with a linear kernel provide the best classification performance in general, but if strong non-linearities are present in the data then non-linear kernels can be more suitable.

Availability: Accompanying homepage is http://www.dbs.ifi.lmu.de/~borgward/BAHSIC

Contact: kb@dbs.ifi.lmu.de

Supplementary information: Supplementary data are available at Bioinformatics online.
Reconstructing sibling relationships in wild populations
Authors: Berger-Wolf Tanya Y. , Sheikh Saad I. , DasGupta Bhaskar , Ashley Mary V. , Caballero Isabel C. , Chaovalitwongse Wanpracha , Putrevu S. Lahari
Published: July 2007

Reconstruction of sibling relationships from genetic data is an important component of many biological applications. In particular, the growing application of molecular markers (microsatellites) to study wild populations of plant and animals has created the need for new computational methods of establishing pedigree relationships, such as sibgroups, among individuals in these populations. Most current methods for sibship reconstruction from microsatellite data use statistical and heuristic techniques that rely on a priori knowledge about various parameter distributions. Moreover, these methods are designed for data with large number of sampled loci and small family groups, both of which typically do not hold for wild populations. We present a deterministic technique that parsimoniously reconstructs sibling groups using only Mendelian laws of inheritance. We validate our approach using both simulated and real biological data and compare it to other methods. Our method is highly accurate on real data and compares favorably with other methods on simulated data with few loci and large family groups. It is the only method that does not rely on a priori knowledge about the population under study. Thus, our method is particularly appropriate for reconstructing sibling groups in wild populations.

Contact: tanyabw@uic.edu
Inferring missing genotypes in large SNP panels using fast nearest-neighbor searches over sliding windows
Authors: Roberts Adam , McMillan Leonard , Wang Wei , Parker Joel , Rusyn Ivan , Threadgill David
Published: July 2007

Motivation: Typical high-throughput genotyping techniques produce numerous missing calls that confound subsequent analyses, such as disease association studies. Common remedies for this problem include removing affected markers and/or samples or, otherwise, imputing the missing data. On small marker sets imputation is frequently based on a vote of the K-nearest-neighbor (KNN) haplotypes, but this technique is neither practical nor justifiable for large datasets.

Results: We describe a data structure that supports efficient KNN queries over arbitrarily sized, sliding haplotype windows, and evaluate its use for genotype imputation. The performance of our method enables exhaustive exploration over all window sizes and known sites in large (150K, 8.3M) SNP panels. We also compare the accuracy and performance of our methods with competing imputation approaches.

Availability: A free open source software package, NPUTE, is available at http://compgen.unc.edu/software, for non-commercial uses.

Contact: mcmillan@cs.unc.edu
RankMotif++: a motif-search algorithm that accounts for relative ranks of K-mers in binding transcription factors
Authors: Chen Xiaoyu , Hughes Timothy R. , Morris Quaid
Published: July 2007

Motivation: The sequence specificity of DNA-binding proteins is typically represented as a position weight matrix in which each base position contributes independently to relative affinity. Assessment of the accuracy and broad applicability of this representation has been limited by the lack of extensive DNA-binding data. However, new microarray techniques, in which preferences for all possible K-mers are measured, enable a broad comparison of both motif representation and methods for motif discovery. Here, we consider the problem of accounting for all of the binding data in such experiments, rather than the highest affinity binding data. We introduce the RankMotif++, an algorithm designed for finding motifs whenever sequences are associated with a semi-quantitative measure of protein-DNA-binding affinity. RankMotif++ learns motif models by maximizing the likelihood of a set of binding preferences under a probabilistic model of how sequence binding affinity translates into binding preference observations. Because RankMotif++ makes few assumptions about the relationship between binding affinity and the semi-quantitative readout, it is applicable to a wide variety of experimental assays of DNA-binding preference.

Results: By several criteria, RankMotif++ predicts binding affinity better than two widely used motif finding algorithms (MDScan, MatrixREDUCE) or more recently developed algorithms (PREGO, Seed and Wobble), and its performance is comparable to a motif model that separately assigns affinities to 8-mers. Our results validate the PWM model and provide an approximation of the precision and recall that can be expected in a genomic scan.

Availability: RankMotif++ is available upon request.

Contact: quaid.morris@utoronto.ca

Supplementary information: Supplementary data are available at Bioinformatics online.
A graph-based approach to systematically reconstruct human transcriptional regulatory modules
Authors: Yan Xifeng , Mehan Michael R. , Huang Yu , Waterman Michael S. , Yu Philip S. , Zhou Xianghong Jasmine
Published: July 2007

Motivation: A major challenge in studying gene regulation is to systematically reconstruct transcription regulatory modules, which are defined as sets of genes that are regulated by a common set of transcription factors. A commonly used approach for transcription module reconstruction is to derive coexpression clusters from a microarray dataset. However, such results often contain false positives because genes from many transcription modules may be simultaneously perturbed upon a given type of conditions. In this study, we propose and validate that genes, which form a coexpression cluster in multiple microarray datasets across diverse conditions, are more likely to form a transcription module. However, identifying genes coexpressed in a subset of many microarray datasets is not a trivial computational problem.

Results: We propose a graph-based data-mining approach to efficiently and systematically identify frequent coexpression clusters. Given m microarray datasets, we model each microarray dataset as a coexpression graph, and search for vertex sets which are frequently densely connected across ⌈ θ m ⌉ datasets (0 ≤ θ ≤ 1). For this novel graph-mining problem, we designed two techniques to narrow down the search space: (1) partition the input graphs into (overlapping) groups sharing common properties; (2) summarize the vertex neighbor information from the partitioned datasets onto the ‘Neighbor Association Summary Graph's for effective mining. We applied our method to 105 human microarray datasets, and identified a large number of potential transcription modules, activated under different subsets of conditions. Validation by ChIP-chip data demonstrated that the likelihood of a coexpression cluster being a transcription module increases significantly with its recurrence. Our method opens a new way to exploit the vast amount of existing microarray data accumulation for gene regulation study. Furthermore, the algorithm is applicable to other biological networks for approximate network module mining.

Availability: http://zhoulab.usc.edu/NeMo/

Contact: xjzhou@usc.edu
Haplotype inference for present–absent genotype data using previously identified haplotypes and haplotype patterns
Authors: Yoo Yun Joo , Tang Jianming , Kaslow Richard A. , Zhang Kui
Published: July 2007

Motivation: Killer immunoglobulin-like receptor (KIR) genes vary considerably in their presence or absence on a specific regional haplotype. Because presence or absence of these genes is largely detected using locus-specific genotyping technology, the distinction between homozygosity and hemizygosity is often ambiguous. The performance of methods for haplotype inference (e.g. PL-EM, PHASE) for KIR genes may be compromised due to the large portion of ambiguous data. At the same time, many haplotypes or partial haplotype patterns have been previously identified and can be incorporated to facilitate haplotype inference for unphased genotype data. To accommodate the increased ambiguity of present–absent genotyping of KIR genes, we developed a hybrid approach combining a greedy algorithm with the Expectation-Maximization (EM) method for haplotype inference based on previously identified haplotypes and haplotype patterns.

Results: We implemented this algorithm in a software package named HAPLO-IHP (Haplotype inference using identified haplotype patterns) and compared its performance with that of HAPLORE and PHASE on simulated KIR genotypes. We compared five measures in order to evaluate the reliability of haplotype assignments and the accuracy in estimating haplotype frequency. Our method outperformed the two existing techniques by all five measures when either 60 % or 25 % of previously identified haplotypes were incorporated into the analyses.

Availability: The HAPLO-IHP is available at http://www.soph.uab.edu/Statgenetics/People/KZhang/HAPLO-IHP/index.html

Contact:  KZhang@ms.soph.uab.edu

Supplementary information: Supplementary data are available at Bioinformatics online.
miniTUBA: medical inference by network integration of temporal data using Bayesian analysis
Authors: Xiang Zuoshuang , Minter Rebecca M. , Bi Xiaoming , Woolf Peter J. , He Yongqun
Published: July 2007

Motivation: Many biomedical and clinical research problems involve discovering causal relationships between observations gathered from temporal events. Dynamic Bayesian networks are a powerful modeling approach to describe causal or apparently causal relationships, and support complex medical inference, such as future response prediction, automated learning, and rational decision making. Although many engines exist for creating Bayesian networks, most require a local installation and significant data manipulation to be practical for a general biologist or clinician. No software pipeline currently exists for interpretation and inference of dynamic Bayesian networks learned from biomedical and clinical data.

Results: miniTUBA is a web-based modeling system that allows clinical and biomedical researchers to perform complex medical/clinical inference and prediction using dynamic Bayesian network analysis with temporal datasets. The software allows users to choose different analysis parameters (e.g. Markov lags and prior topology), and continuously update their data and refine their results. miniTUBA can make temporal predictions to suggest interventions based on an automated learning process pipeline using all data provided. Preliminary tests using synthetic data and laboratory research data indicate that miniTUBA accurately identifies regulatory network structures from temporal data.

Availability: miniTUBA is available at http://www.minituba.org

Contact:  yongqunh@med.umich.edu
APID2NET: unified interactome graphic analyzer
Authors: Hernandez-Toro Juan , Prieto Carlos , De Las Rivas Javier
Published: July 2007

Motivation: Exploration and analysis of interactome networks at systems level requires unification of the biomolecular elements and annotations that come from many different high-throughput or small-scale proteomic experiments. Only such integration can provide a non-redundant and consistent identification of proteins and interactions. APID2NET is a new tool that works with Cytoscape to allow surfing unified interactome data by querying APID server (http://bioinfow.dep.usal.es/apid/) to provide interactive analysis of protein–protein interaction (PPI) networks. The program is designed to visualize, explore and analyze the proteins and interactions retrieved, including the annotations and attributes associated to them, such as: GO terms, InterPro domains, experimental methods that validate each interaction, PubMed IDs, UniProt IDs, etc. The tool provides interactive graphical representation of the networks with all Cytoscape capabilities, plus new automatic tools to find concurrent functional and structural attributes along all protein pairs in a network.

Availability:  http://bioinfow.dep.usal.es/apid/apid2net.html

Contact:  jrivas@usal.es

Supplementary information: Installation Guide and User's Guide are supplied at the Web site indicated above.
Underwater television as a fishery-independent method for stock assessment of Norway lobster (Nephrops norvegicus) in the central Adriatic Sea (Italy)
Authors: Morello Elisabetta B. , Froglia Carlo , Atkinson R. J. A.
Published: July 2007

Morello, E. B., Froglia, C., and Atkinson, R. J. A. 2007. Underwater television as a fishery-independent method for stock assessment of Norway lobster (Nephrops norvegicus) in the central Adriatic Sea (Italy). – ICES Journal of Marine Science, 64: 1116–1123. Norway lobster is of great commercial importance throughout the NE Atlantic and Mediterranean, where it lives in burrows in muddy sediments. The fact that the species is caught in commercial gear only when it emerges from its burrow and the absence of hard structures available for age determination complicate the application of normal fishery-dependent stock-assessment methodologies. This study provides more evidence of the usefulness of underwater television surveys as a fishery-independent technique to assess the Nephrops stocks of the Adriatic Sea. The results are compared with those of previous studies, and the advantages and disadvantages of using such methodology discussed in an Adriatic context.
Quantitative diet assessment of wobbegong sharks (genus Orectolobus) in New South Wales, Australia
Authors: Huveneers Charlie , Otway Nicholas M. , Gibbs Susan E. , Harcourt Robert G.
Published: July 2007

Huveneers, C., Otway, N. M., Gibbs, S. E., and Harcourt, R. G. 2007. Quantitative diet assessment of wobbegong sharks (genus Orectolobus) in New South Wales, Australia. – ICES Journal of Marine Science, 64: 1272–1281. The diets of three species of wobbegong (Orectolobus ornatus, O. maculatus, and O. halei) in New South Wales, Australia, were investigated using stomach contents from specimens caught by commercial fishers. Some 80% of wobbegongs caught by commercial setline, and 60% caught by trap or scuba diving, had empty stomachs, most likely due to regurgitation. Wobbegongs were frequently hooked in the stomach (80–90% of the catch), potentially contributing to the greater proportion of empty stomachs compared with other species of shark. The diet of all three species was primarily osteichthyans, but with some cephalopods and chondrichthyans. Interspecific differences in the diets were related to total length of the shark. Octopuses were more frequent in the diet of O. ornatus (dwarf ornate wobbegong) than other wobbegong species, possibly through the smaller adult size facilitating capture of octopuses in small holes/crevices. Orectolobus halei fed more frequently on pelagic species and chondrichthyans, possibly because of their greater mobility. Wobbegongs feed at a high trophic level, and their removal from their ecosystem may impact lower trophic levels.
Simulating Models of Issue Voting
Authors: Macdonald Stuart Elaine , Rabinowitz George , Listhaug Ola
Published: July 2007

How should one analyze data when the underlying models being tested are statistically intractable? In this article, we offer a simulation approach that involves creating sets of artificial data with fully known generating models that can be meaningfully compared to real data. The strategy depends on constructing simulations that are well matched to the data against which they will be compared. Our particular concern is to consider concurrently how voters place parties on issue scales and how they evaluate parties based on issues. We reconsider the Lewis and King (2000) analysis of issue voting in Norway. The simulation findings resolve the ambiguity that Lewis and King report, as voters appear to assimilate and contrast party placements and to evaluate parties directionally. The simulations also provide a strong caveat against the use of individually perceived party placements in analyses of issue voting.
Basic mechanisms of high‐risk human papillomavirus‐induced carcinogenesis: Roles of E6 and E7 proteins
Authors: Narisawa‐Saito Mako , Kiyono Tohru
Published: July 2007

Human papillomaviruses (HPV) are believed to be the primary causal agents for development of pre‐neoplastic and malignant lesions of the uterine cervix, and high‐risk types such as type 16 and 18 are associated with more than 90% of all cervical carcinomas. The E6 and E7 genes of HPV are thought to play causative roles, since E6 promotes the degradation of p53 through its interaction with E6AP, an E3 ubiquitin ligase, whereas E7 binds to the retinoblastoma protein (pRb) and disrupts its complex formation with E2F transcription factors. Although prophylactic vaccines have become available, it is still necessary to clarify the mechanisms of HPV‐induced carcinogenesis because of the widespread nature of HPV infection. Approximately 493 000 new cases of cervical cancer are diagnosed each year with approximately 274 000 mortalities due to invasive cervical cancer. In the present article, the mechanisms of HPV16 E6‐ and E7‐induced multistep carcinogenesis and recently identified functions of these onco‐proteins are reviewed. (Cancer Sci 2007; 98: 1505–1511)
The cost‐effectiveness of four treatments for marijuana dependence
Authors: Olmstead Todd A. , Sindelar Jody L. , Easton Caroline J. , Carroll Kathleen M.
Published: July 2007

Aim To analyze data from a randomized clinical trial to determine the cost‐effectiveness of using contingency management (CM) and motivational/skills building therapy (motivational enhancement therapy/cognitive‐behavioral therapy: MET/CBT) to treat young adults with marijuana dependence.

Participants, design and measurements A total of 136 marijuana‐dependent young adults, all referred by the criminal justice system, were randomized to one of four treatment conditions: MET/CBT with CM, MET/CBT without CM, drug counseling (DC) with CM and DC without CM. Patient outcome measures include the longest duration of confirmed marijuana abstinence (LDA) during treatment and the total number of marijuana‐free urine specimens provided during treatment. Costs were collected retrospectively from the provider and include the costs of therapy, patient drug testing, and those associated with the incentives component (value of vouchers, time to administer the voucher system).

Setting Out‐patient substance abuse clinic in New Haven, Connecticut, USA.

Findings Which treatment is the most cost‐effective depends on the threshold values of an additional week of LDA or an additional marijuana‐free urine specimen. For example, the most effective treatment, MET/CBT with CM, was also the most cost‐effective treatment at the highest threshold values, while the least effective treatment, DC, was the most cost‐effective at the lowest values. Because consensus threshold values for these patient outcomes do not exist, results are presented showing the ranges of values over which each treatment would be considered cost‐effective compared to the others. Acceptability curves are presented to show the decision uncertainty associated with these ranges. The results are shown to be robust to (i) sensitivity analyses on several key cost parameters and (ii) patient outcomes measured during the 6‐month follow‐up period.

Conclusions This study uses incremental cost‐effectiveness ratios and acceptability curves to shed light on the relative cost‐effectiveness of four interventions for treating young adults with marijuana dependence. Given the relatively small and specialized nature of our study sample, and the fact that we examined a CM procedure with a single reinforcement schedule, additional studies are warranted to determine the reliability and generalizability of our results both to alternative marijuana‐using populations and to CM procedures with alternative incentive parameters. Nevertheless, the relative durability of effects of MET/CBT compared to DC through the 6‐month follow‐up, and its cost‐effectiveness over a comparatively wide range of threshold values, underscores the promise of this approach.
The role of plant defence proteins in fungal pathogenesis
Authors: FERREIRA RICARDO B. , MONTEIRO SARA , FREITAS REGINA , SANTOS CLÁUDIA N. , CHEN ZHENJIA , BATISTA LUÍS M. , DUARTE JOÃO , BORGES ALEXANDRE , TEIXEIRA ARTUR R.
Published: July 2007

It is becoming increasingly evident that a plant–pathogen interaction may be compared to an open warfare, whose major weapons are proteins synthesized by both organisms. These weapons were gradually developed in what must have been a multimillion‐year evolutionary game of ping‐pong. The outcome of each battle results in the establishment of resistance or pathogenesis. The plethora of resistance mechanisms exhibited by plants may be grouped into constitutive and inducible, and range from morphological to structural and chemical defences. Most of these mechanisms are defensive, exhibiting a passive role, but some are highly active against pathogens, using as major targets the fungal cell wall, the plasma membrane or intracellular targets. A considerable overlap exists between pathogenesis‐related (PR) proteins and antifungal proteins. However, many of the now considered 17 families of PR proteins do not present any known role as antipathogen activity, whereas among the 13 classes of antifungal proteins, most are not PR proteins. Discovery of novel antifungal proteins and peptides continues at a rapid pace. In their long coevolution with plants, phytopathogens have evolved ways to avoid or circumvent the plant defence weaponry. These include protection of fungal structures from plant defence reactions, inhibition of elicitor‐induced plant defence responses and suppression of plant defences. A detailed understanding of the molecular events that take place during a plant–pathogen interaction is an essential goal for disease control in the future.
Wheeze and asthma prevalence and related health‐service use in white and south Asian pre‐schoolchildren in the United Kingdom
Authors: Kuehni C. E. , Strippoli M.‐P. F. , Low N. , Brooke A. M. , Silverman M.
Published: July 2007

Background
Epidemiological data for south Asian children in the United Kingdom are contradictory, showing a lower prevalence of wheeze, but a higher rate of medical consultations and admissions for asthma compared with white children. These studies have not distinguished different asthma phenotypes or controlled for varying environmental exposures.

Objective
To compare the prevalence of wheeze and related health‐service use in south Asian and white pre‐schoolchildren in the United Kingdom, taking into account wheeze phenotype (viral and multiple wheeze) and environmental exposures.

Methods
A postal questionnaire was completed by parents of a population‐based sample of 4366 white and 1714 south Asian children aged 1–4 years in Leicestershire, UK. Children were classified as having viral wheeze or multiple trigger wheeze.

Results
The prevalence of current wheeze was 35.6% in white and 25.5% in south Asian 1‐year‐olds (P<0.001), and 21.9% and 20.9%, respectively, in children aged 2–4 years. Odds ratios (ORs) (95% confidence interval) for multiple wheeze and for viral wheeze, comparing south Asian with white children, were 2.21 (1.19–4.09) and 1.43 (0.77–2.65) in 2–4‐year‐olds after controlling for socio‐economic conditions, environmental exposures and family history. In 1‐year‐olds, the respective ORs for multiple and viral wheeze were 0.66 (0.47–0.92) and 0.81 (0.64–1.03). Reported GP consultation rates for wheeze and hospital admissions were greater in south Asian children aged 2–4 years, even after adjustment for severity, but the use of inhaled corticosteroids was lower.

Conclusions
South Asian 2–4‐year‐olds are more likely than white children to have multiple wheeze (a condition with many features of chronic atopic asthma), after taking into account ethnic differences in exposure to some environmental agents. Undertreatment with inhaled corticosteroids might partly explain their greater use of health services.
Shaping ability of progressive versus constant taper instruments in curved root canals of extracted teeth
Authors: Yang G. B. , Zhou X. D. , Zheng Y. L. , Zhang H. , Shu Y. , Wu H. K.
Published: July 2007

Aim  To compare the shaping ability of progressive versus constant taper shaft instruments in curved root canals of extracted human teeth.

Methodology  A total of 40 root canals of mandibular molars with curvatures ranging between 20° and 40° were divided into two groups of 20 canals each and embedded in a muffle system. The root canals sectioned horizontally at three levels before preparation and then remounted into the mould. All root canals were prepared with ProTaper (progressive taper) or Hero Shaper (constant taper) instruments. Pre‐ and post‐instrumentation radiographs and cross‐sectional images were obtained. The parameters evaluated were: working safety (instrument failure, apical blockage and loss of working length) and shaping ability (straightening, cross‐sectional area, transportation and centring ability). The data were analysed statistically using Student’s t‐test.

Results  No instrument fractured during preparation. One Hero Shaper instrument permanently deformed. Both instrument systems maintained working length well. The canals prepared with Hero Shaper instruments were straightened to a lesser degree (P < 0.05). ProTaper instruments removed more dentine in the coronal and the middle sections of the canals. Canals prepared with Hero Shaper instruments had less transportation (P < 0.01) and better centring ability (P < 0.05) in the apical section.

Conclusions  Both instrument systems were safe to use and maintained working length well. The canals prepared with Hero Shaper had less transportation and were better centred in the apical region, possibly because their smaller taper reduced instrument stiffness.