Availability: AQUA is implemented in Tcl/Tk and runs in command line on all platforms. The source code is available under the GNU GPL license. Source code, README and Supplementary data are available at
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Results: In this paper, we describe a pathway-based method using random forests to correlate gene expression data with survival outcomes and introduce a novel bivariate node-splitting random survival forests. The proposed method allows researchers to identify important pathways for predicting patient prognosis and time to disease progression, and discover important genes within those pathways. We compared different implementations of random forests with different split criteria and found that bivariate nodesplitting random survival forests with log-rank test is among the best. We also performed simulation studies that showed random forests outperforms several other machine learning algorithms and has comparable results with a newly developed componentwise Cox boosting model. Thus, pathway-based survival analysis using machine learning tools represents a promising approach in dissecting pathways and for generating new biological hypothesis from microarray studies.
Availability: R package
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Supplementary Information: Supplementary Materials are available at
Results: We have developed mimiRNA, an on-line resource that integrates expression data from 1483 samples and permits visualization of the expression of 635 human miRNAs across 188 different tissues or cell types. mimiRNA incorporates a novel sample classification algorithm, ExParser, that groups identical miRNA or mRNA experiments from separate sources. This enables mimiRNA to provide reliable expression profiles and to discover functional relations between miRNAs and mRNAs such as miRNA targets. Additionally, mimiRNA incorporates a decision tree algorithm to discover distinguishing miRNA features between two tissue or cell types. We validate the efficacy of our resource on independent experimental data and through biologically relevant analyses.
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Supplementary information: Supplementary data are available at Bioinformatics online.
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Supplementary information: Supplementary data available at the journal's web site.
]]>Results: For each SNP, the SCAN database provides: (1) Summary information from eQTL mapping of HapMap SNPs to gene expression (evaluated by the Affymetrix exon array) in the full set of HapMap CEU (Caucasians from Utah, USA) and YRI (Yoruba people from Ibadan, Nigeria) samples; (2) LD information, in the case of a HapMap SNP, including what genes have variation in strong LD (pairwise or multilocus LD) with the variant and how well the SNP is covered by different high-throughput platforms; (3) Summary information available from public databases (e.g., physical and functional annotations); and (4) Summary information from other GWAS. For each gene, SCAN provides annotations on: (1) eQTLs for the gene (both local and distant SNPs); and (2) The coverage of all variants in the HapMap at that gene on each high-throughput platform. For each genomic region, SCAN provides annotations on: (1) Physical and functional annotations of all SNPs, genes, and known CNVs within the region; and (2) All genes regulated by the eQTLs within the region.
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Supplementary Information: Supplementary data are available at Bioinformatics online
]]>Availability: MADS+ scripts, documentations and annotation files are available at
Availability: SemanticSBML is free software written in Python and released under the GPL 3. A Debian package, a source package for other Linux distributions, a Windows installer, and an online version of semanticSBML with reduced functionality are available at
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Supplementary Information: Supplementary data are available at Bioinformatics online.
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Supplementary Information: The VIBE 2.0 User manual is available at Bioinformatics online in addition to availability through the software.
]]>Results: We propose a Bayesian stochastic variable selection approach for gene selection based on a probit regression model with a generalized singular g-prior distribution for regression coefficients. Using simulation-based MCMC methods for simulating parameters from the posterior distribution, an efficient and dependable algorithm is implemented. It is also shown that this algorithm is robust to the choices of initial values, and produces posterior probabilities of related genes for biological interpretation. The performance of the proposed approach is compared with other popular methods in gene selection and classification via the well known colon cancer and leukemia data sets in microarray literature.
Availability: A free Matlab code to perform gene selection is available at
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Results: The availability of PyNAST will make the popular NAST algorithm more portable and thereby applicable to data sets orders of magnitude larger by allowing users to install PyNAST on their own hardware. Additionally because users can align to arbitrary template alignments, a feature not available via the original NAST web interface, the NAST algorithm will be readily applicable to novel tasks outside of microbial community analysis.
Availability: PyNAST is available at
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Availability: PerturbationAnalyzer can be accessed from the Cytoscape website
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Results Modifications to the grammars underlying earlier approaches enables the calculation of interaction probabilities for any given interval on the target RNA. The computation of the "hybrid probabilities" is complemented by a stochastic sampling algorithm that produces a Boltzmann weighted ensemble of RNA-RNA interaction structures. The sampling of k structures requires only negligible additional memory resources and runs in O(k · N3).
Availability The algorithms described here are implemented in C as part of the rip package. The source code of rip2 can be downloaded from
Contact Christian Reidys
Results: In this work, for the first time, we have used residue based statistical pair potentials for scoring the binding energy of various substrate peptides in complex with kinases. Extensive benchmarking on Phospho.ELM data set indicate that our method outperforms other structure based methods and has a prediction accuracy comparable to available sequence based methods. We also demonstrate that the rank of the true substrate can be further improved, if the high scoring candidate substrates that are shortlisted based on pair potential score, are modeled using all atom forcefield and MM/PBSA approach.
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Results: These topological comparisons indicate that co-expression networks are not distinctly related with either the protein-protein interaction or the MIPS physical interaction networks, showing important structural differences between them. When focusing on a more literal comparison, vertex by vertex and edge by edge, the conclusion is the same: the fact that two genes exhibit a high gene expression correlation degree does not seem to obviously correlate with the existence of a physical binding between the proteins produced by these genes or the existence of a MIPS physical interaction between the genes. The comparison of the yeast regulatory network with inferred yeast co-expression networks would suggest, however, that they could somehow be related.
Conclusions: We conclude that the gene expression-based co-expression networks reflect more on the gene regulatory networks but less on the protein-protein interaction or MIPS physical interaction networks.
Contact: Hongzhe Li, email:
Making the assumption that active compounds should have specific contacts with their target to display activity, it would be possible to discriminate active compounds from inactive ones with careful analysis of interatomic contacts between the molecule and the target. However, compounds clustering is very tedious due to the large number of contacts extracted from the different conformations proposed by docking experiments.
Results: Structural analysis of docked structures is processed in three steps: (1) a Kohonen self-organising map (SOM) training phase using drug-protein contact descriptors followed by (2) an unsupervised cluster analysis and (3) a Newick file generation for results visualisation as a tree. The docking poses are then analysed and classified quickly and automatically by AuPosSOM (Automatic analysis of Poses using SOM). AuPosSOM can be integrated into strategies for virtual screening currently employed.
We demonstrate that it is possible to discriminate active compounds from inactive ones using only mean protein contacts footprints calculation from the multiple conformations given by the docking software. Chemical structure of the compound and key binding residues information are not necessary to find out active molecules. Thus, contact activity relationship (CAR) can be employed as a new virtual screening process.
Availability: AuPosSOM is available at
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Supplementary information: Supplementary data are available at Bioinformatics online.
]]>Results: We developed a method based on an enhanced version of the multi-level model used by CRLMM version 1 (Carvalho et al., 2007). Two key differences are that we now account for variability across batches and improve the call-specific assessment of each call. The new model permits the development of quality metrics for SNPs, samples, and batches of samples. Using three independent datasets we demonstrate that the CRLMM version 2 outperforms CRLMM version 1 and the algorithm provided by Affymetrix, Birdseed. The main advantage of the new approach is that it enables the identification of low quality SNPs , samples, and batches.
Availability: Software implementing of the method described in this paper is available as free and open source code in the
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Supplementary information: Supplementary data are available at Bioinformatics online.
]]>Availability: The package is freely available under the LGPL licence from the Bioconductor web site (
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Results: The ModFOLDclustQ method is competitive with leading clustering based MQAPs for the prediction of global model quality, yet it is up to 150 times faster than the previous version of the ModFOLDclust method at comparing models of small proteins (<60 residues) and over 5 times faster at comparing models of large proteins (>800 residues). Furthermore, a significant improvement in accuracy can be gained over the previous clustering based MQAPs by combining the scores from ModFOLDclustQ and ModFOLDclust to form the new ModFOLDclust2 method, with little impact on the overall time taken for each prediction.
Availability: The ModFOLDclustQ and ModFOLDclust2 methods are available to download from:
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Results: We used the effect of miRNAs over their targets for the detection of miRNA activity using mRNAs expression profiles. Here we describe the method, called T-REX (from Targets' Reverse EXpression), compare it to other similar applications, show its effectiveness and apply it to build activity maps. We used six different target predictions from each of four algorithms: TargetScan, PicTar, DIANA-microT and DIANA Union.
First, we proved the sensitivity and specificity of our technique in miRNA over-expression and knock-out animal models. Then, we used whole transcriptome data from acute myeloid leukemia to show that we could identify critical miRNAs in a real life, complex, clinically relevant dataset. Finally, we studied sixty-six different cellular conditions to confirm and extend the current knowledge on the role of miRNAs in cellular physiology and in cancer.
]]>Availability: GATE is available for download and is free for academic use from
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Results: We examined a variety of algorithms that estimate protein differential expression ratios from multiple peptide intensity measurements. Algorithms that account for the variation of measurement error with intensity were found to provide the most accurate estimates of differential abundance. A simple Sum-of-Intensities algorithm provided the best estimates of true protein ratios of all algorithms tested.
]]>Results: We develop a model for predicting nucleic acid secondary structure in the presence of single stranded binding proteins, and implement it as an extension of the Vienna RNA Package. All parameters needed to model nucleic acid secondary structures in the absence of proteins have been previously determined. This leaves the footprint and sequence dependent binding affinity of the protein as adjustable parameters of our model. Using this model we are able to predict the probability of the protein binding at any position in the nucleic acid sequence, the impact of the protein on nucleic acid base pairing, the end-to-end distance distribution for the nucleic acid, and FRET distributions for fluorophores attached to the nucleic acid.
Availability: Source code for our modified version of the Vienna RNA package is freely available at
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Results: We have developed an alternative splicing robust prediction method based on entropy (ARH). We can show that this measure copes with bias inherent in the analysis of alternative splicing such as the dependency of prediction performance on the number of exons or variable exon expression. In order to judge the performance of ARH. we have compared it with eight existing splicing prediction methods using experimental benchmark data and demonstrate that ARH is a well-performing new method for the prediction of splice variants.
Availability and Implementation: ARH is implemented in R and provided in the supplementary material.
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Supplementary Information: The supplementary material provides additional figures and tables, the R implementation of ARH, a basic implementation for the method comparison and the AEdb true positive set.
]]>Availability: SimBoolNet package (with manual) is freely available at
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Availability and Implementation: MATICCE is written in the open-source R language and freely available through the Comprehensive R Archive Network (
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Results: Our extensive experiments on both simulated data and real genome-wide data from Wellcome Trust Case Control Consortium (WTCCC) show that SNPRuler significantly outperforms its recent competitor. To our knowledge, SNPRuler is the first method that guarantees to find the epistatic interactions without exhaustive search. Our results indicate that finding epistatic interactions in GWAS is computationally attainable in practice.
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Results: In a widely used F2 reciprocal mating population for mapping imprinting genes, we herein propose a genomic imprinting model which describes additive, dominance, and imprinting effects of multiple imprinted quantitative trait loci (iQTL) for traits of interest. Depending upon the estimates of the above genetic effects, we categorized imprinting patterns into seven types, which provides a complete classification scheme for describing imprinting patterns. Bayesian model selection was employed to identify iQTL along with many genetic parameters in a computationally efficient manner. To make statistical inference on the imprinting types of iQTL detected, a set of Bayes factors were formulated using the posterior probabilities for the genetic effects being compared. We demonstrated the performance of the proposed method by computer simulation experiments and then applied this method to two real data sets. Our approach can be generally used to identify inheritance modes and determine the contribution of major genes for quantitative variations.
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Availability: Phenopedia and Genopedia can be freely accessed at
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Availability: inGAP is available at
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Supplementary information: Supplementary data are available at Bioinformatics online.
]]>Results: Here we develop such a model selection framework based on approximate Bayesian computation and employing sequential Monte Carlo sampling. We show that our approach can be applied across a wide range of biological scenarios, and we illustrate its use on real data describing influenza dynamics and the JAK-STAT signalling pathway. Bayesian model selection strikes a balance between the complexity of the simulation models and their ability to describe observed data. The present approach enables us to employ the whole formal apparatus to any system that can be (efficiently) simulated, even when exact likelihoods are computationally intractable.
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Supplementary Information: Tutorial on ABC rejection and ABC SMC for parameter estimation and model selection. Derivation of ABC SMC model selection algorithms. Supplementary figures and datasets.
]]>Results: We present MicroRazerS, a tool optimized for mapping small RNAs onto a reference genome. It is an order of magnitude faster than Mega BLAST and comparable in speed to other short read mapping tools. In addition, it is more sensitive and easy to handle and adjust.
Availability: MicroRazerS is part of the SeqAn C++ library and can be downloaded from
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Results: We have implemented a model editor that incorporates model aggregation, and we suggest supporting extensions to the Systems Biology Markup Language (SBML) Level 3. We illustrate aggregation with a model of the eukaryotic cell cycle ‘engine’ created from smaller pieces.
Availability: Java implementations of our SBML proposal are available in the JigCell Aggregation Connector. See
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Results: In this paper, we present GNUMAP (Genomic Nextgeneration Universal MAPper), a program capable of overcoming two major obstacles in the mapping of reads from next-generation sequencing runs. First, we have created an algorithm that probabilistically maps reads to repeat regions in the genome on a quantitative basis. Second, we have developed a probabilistic Needleman-Wunsch algorithm which utilizes _prb.txt and _int.txt files produced in the Solexa/Illumina pipeline to improve the mapping accuracy for lower quality reads and increase the amount of usable data produced in a given experiment.
Availability: The source code for the software can be downloaded from
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Results: We use protein profile similarity screening to identify candidate proteins whose abundances are post-transcriptionally controlled by the Anaphase Promoting Complex (APC/C), a specific E3 ubiquitin ligase that is a master regulator of the cell cycle. Results are compared with an established protein correlation profiling method. The proposed procedure yields a 50.9-fold enrichment of co-regulated protein candidates and a 2.5-fold improvement over the previous method.
Availability: A MATLAB toolbox is available from
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Results: A Bayesian model for estimating the haplotypes and their frequencies from pooled allelic observations is introduced. The model combines an idea of using database information for haplotype estimation with a computationally efficient multinormal approximation. In addition, the model treats the number and structures of the unknown haplotypes as random variables whose joint posterior distribution is estimated. The results on real human data from the HapMap database show that the proposed method provides significant improvements over the existing methods.
Availability: A reversible-jump Markov chain Monte Carlo algorithm for analysing the model is implemented in a program called Hippo. For comparisons, an approximate EM-algorithm that utilises database information about the existing haplotypes is implemented in a program called AEML. The source codes written in C (using Gnu Scientific Library) are available at
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Results: In this paper, we propose a novel annotation quality or confidence scoring scheme, called Annotation Confidence Score (ACS), using a genome comparison approach. The scoring scheme is computed by combining sequence and textual annotation similarity using a modified version of a logistic curve. The most important feature of the proposed scoring scheme is to generate a score that reflects the excellence in annotation quality of genes by automatically adjusting the number of genomes used to compute the score and their phylogenetic distance. Extensive experiments with bacterial genomes showed that the proposed scoring scheme generated scores for annotation quality according to the quality of annotation regardless of the number of reference genomes and their phylogenetic distance.
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Availability: The R package and a quick-start vignette is available at
Contact: XW:
Supplementary information: Supplementary data are available at Bioinformatics online.
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Results: Target predictions for the cyanobacterial small RNA Yfr1 were carried out with I
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Results: R users can take advantage of the better performance provided by an Nvidia GPU.
Availability: The package is available from CRAN, the R project's repository of packages, at
More information about our gputools R package is available at
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Results: We apply the CTGDR (Clustering Threshold Gradient Directed Regularization) method to genetic association studies using SNPs, analyze data from an association study of NHL, and identify prognosis signatures for diffuse large B cell lymphoma (DLBCL) and follicular lymphoma (FL), the two most common subtypes of NHL. With the CTGDR method, we are able to account for the joint effects of multiple genes/SNPs, whereas most existing studies are single-marker based. In addition, we are able to account for the "gene and SNPwithin-gene" hierarchical structure and identify not only predictive genes but also predictive SNPs within identified genes. In contrast, existing studies are limited to either gene or SNP identification, but not both. We propose using resampling methods to evaluate the predictive power and reproducibility of identified genes and SNPs. Simulation study and data analysis suggest satisfactory performance of the CTGDR method.
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Results: We developed an interaction detection method and explored usefulness of various features in automatically identifying PPIs in text. The results show that our approach outperforms other systems using the AImed dataset. In the tests where our system achieves better precision with reduced recall, we discuss possible approaches for improvement. In addition to test datasets, we evaluated performance on interactions from five human-curated databases—BIND, DIP, HPRD, IntAct and MINT—where our system consistently identified evidence for about 60% of interactions when both proteins appear in at least one sentence in the PubMed abstract. We then applied the system to extract articles from PubMed to annotate known, high-throughput and interologous interactions in I2D.
Availability: The data and software are available at:
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Availability: The Ancestors 1.0 is available at <
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Availability: Source code and documentation are available for noncommercial use at
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Supplementary Information: Supplementary data are available at Bioinformatics online.
]]>Results: This paper characterizes reporting bias with several statistics and computes these statistics in a large simulation study using both modeled and real data. The results appear as curves giving the different reporting biases as functions of the number of samples tested when reporting only the best or second best performance. It does this for two classification rules, linear discriminant analysis (LDA) and 3 nearest-neighbor (3NN), and for filter and wrapper feature selection, t-test and sequential forward search. These were chosen on account of their well-studied properties and because they were amenable to the extremely large amount of processing required for the simulations. The results across all the experiments are consistent: there is generally large bias overriding what would be considered a significant performance differential, when reporting the best or second best performing data set. We conclude that there needs to be a database of data sets and that, for those studies depending on real data, results should be reported for all data sets in the database.
Availability: Companion website at
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Results: We introduce a novel evolutionary fuzzy clustering (EFC) algorithm, which is able to deal with overlapping clusterings. Our method assesses these overlaps by using cluster membership degrees, which we use here as a confidence measure for individual samples to be assigned to a given tumor type. We first demonstrate the usefulness of our method using a synthetic aCGH dataset and subsequently show that EFC outperforms existing methods on four real datasets of aCGH tumor profiles involving four different cancer types. We also show that in general best performance is obtained using 1— Pearson correlation coefficient as a distance measure and that extra pre processing steps, such as segmentation and calling, lead to decreased clustering performance.
Availability: The source code of the program is available from
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Results: We present a new algorithm, Roll, implemented in a program named POCASA, which can predict binding sites by detecting pockets and cavities of proteins with a rolling sphere. To evaluate the performance of POCASA, a test with the same data set as used in several existing methods was carried out. POCASA achieved a high success rate of 77%. In addition, the test results indicated that POCASA can predict good shapes of ligand binding sites.
Availability: A web version of POCASA is freely available at
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Availability: G-compass is freely available at
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Availability: CRISPI free access at
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Availability: The software is available at
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Availability: NAViGaTOR is freely available to the research community from
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Results: We propose a new method for efficient protein family classification and for speeding up database searches with pHMMs as is necessary for large scale analysis scenarios. We employ simpler models of protein families called PSSM family models. For fast database search, we combine full text indexing, efficient exact p-value computation of PSSM match scores, and fast fragment chaining. The resulting method is well suited to pre-filter the set of sequences to be searched for subsequent database searches with pHMMs.
We achieved a classification performance only marginally inferior to hmmsearch, yet, results could be obtained in a fraction of runtime with a speedup of more than 64 fold. In experiments addressing the method's ability to pre-filter the sequence space for subsequent database searches with pHMMs, our method reduces the number of sequences to be searched with hmmsearch to only 0.80% of all sequences. The filter is very fast and leads to a total speedup of factor 43 over the unfiltered search while retaining more than 99.5% of the original results. In a lossless filter setup for hmmsearch on UniProtKB/Swiss-Prot, we observed a speedup of factor 92.
Availability: The presented algorithms are implemented in the program PoSSuMsearch2, available for download at
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Results: In an application to acute myeloid leukemia, our procedure is able to identify various regions on different chromosomes with characteristic abnormalities in gene expression and copy number data and shows a higher sensitivity to differences in abnormalities than standard approaches. While the results support various findings of previous studies, some new interesting DNA regions can be identified. In a simulation study, our procedure also shows more reliable results than standard approaches.
Availability: Code and data available as R packages edira and ediraAMLdata from
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Supplementary Information: Supplementary material is available at Bioinformatics online.
]]>Availability: The web server is freely available to non-commercial users at the following address:
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Supplementary Information: Supplementary data are available at
Results: We present an algorithm to extract (
Availability: Version 2 of kr can be tested via a web interface at
It is written in standard C and its source code is available under the GNU General Public License from the same web site.
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Results: We used the granular support vector machines (SVMs)repetitive undersampling method (GSVM-RU) to construct an SVM from luciferase inhibition bioassay data that the imbalance ratio of active/inactive is high (1/377). The best model recognized the active and inactive compounds at the accuracies of 86.60% and 88.89 with a total accuracy of 87.74%, by cross-validation test and blind test. These results demonstrate the robustness of the model in handling the intrinsic imbalance problem in HTS data and it can be used as a virtual screening tool to identify potential interference compounds in luciferase-based HTS experiments. Additionally, this method has also proved computationally efficient by greatly reducing the computational cost and can be easily adopted in the analysis of HTS data for other biological systems.
Availability: Data are publicly available in PubChem with AIDs of 773, 1006 and 1379.
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Supplementary information: Supplementary data are available at Bioinformatics online.
]]>Results: We present the COALESCE system for regulatory module prediction. The algorithm is efficient enough to discover expression biclusters and putative regulatory motifs in metazoan genomes (>20,000 genes) and very large microarray compendia (>10,000 conditions). Using Bayesian data integration, it can also include diverse supporting data types such as evolutionary conservation or nucleosome placement. We validate its performance using a functional evaluation of coclustered genes, known yeast and E. coli transcription factor targets, synthetic data, and various metazoan data compendia. In all cases, COALESCE performs as well or better than current biclustering and motif prediction tools, with high accuracy in functional and TF/target assignments and zero false positives on synthetic data. COALESCE provides an efficient and flexible plat-form within which large, diverse data collections can be integrated to predict metazoan regulatory networks.
Availability: Source code (C++) is available at
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Availability: The web interface is available at
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Supplementary information: Detailed documentation is available on the Exon Array Analyzer web site (
Results: This paper presents a new approach based on building several prediction models for the Bioinformatics journal. These models predict the citation count of an article within four years after publication (global models). To build these models, tokens found in the abstracts of Bioinformatics papers have been used as predictive features, along with other features like the journal sections and two-week post publication periods. To improve the accuracy of the global models, specific models have been built for each Bioinformatics journal section (Data and Text Mining, Databases and Ontologies, Gene Expression, Genetics and Population Analysis, Genome Analysis, Phylogenetics, Sequence Analysis, Structural Bioinformatics and Systems Biology). In these new models, the average success rate for predictions using the naive Bayes and logistic regression supervised classification methods was 89.4% and 91.5%, respectively, within the nine sections and for four-year time horizon.
Availability: Supplementary material on this experimental survey is available at
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Results: We have developed a desktop application, QSVanalyser, which allows high throughput quantification of the proportions of DNA sequences containing single-nucleotide variants. In reconstruction experiments, QSVanalyser accurately estimated the known relative proportions of SNVs. By analysing a large panel of genomic DNA samples, we demonstrate the ability of the software to analyse not only common biallelic SNVs, but also SNVs within a locus at which gene conversion between 4 genomic paralogues operates, and within another that is subject to copy number variation.
Availability and Implementation: QSVAnalyser is freely available at
Results: Here we present a novel Bayesian approach to align the complete spectra. The approach is based on a parametric model which assumes the spectrum and alignment function are Gaussian processes, but the alignment function is monotone. We show how to use the expectation-maximization algorithm to find the posterior mode of the set of alignment functions and the mean spectrum for a patient population. After alignment, we conduct tests while controlling for error attributable to multiple comparisons on the level of the peaks identified from the absolute mean spectra difference of two patient populations.
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Results: We have developed a method for adding full atomic detail to coarse-grain models of RNA 3D structures. Our method (C2A) uses geometries observed in known RNA crystal structures. Our method rebuilds full atomic detail from ideal coarse-grain backbones taken from crystal structures to within 1.87 to 3.31 Å RMSd of the full atomic crystal structure. When starting from coarse-grain models generated by the modeling tool NAST, our method builds full atomic structures that are within 1.00 Å RMSd of the starting structure. The resulting full atomic structures can be used as starting points for higher resolution modeling, thus bridging high and low resolution approaches to modeling RNA 3D structure.
Availability: Code for the C2A method, as well as the examples discussed in this paper, are freely available at
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Results: We designed a novel estimator for multiple alignments of structured RNAs, based on maximizing the expected accuracy of predictions. First, we define the maximum expected accuracy (MEA) estimator for pairwise alignment of RNA sequences. This maximizes the expected sum-of-pairs score (SPS) of a predicted alignment under a probability distribution of alignments given by marginalizing the Sankoff model. Then, by approximating the MEA estimator, we obtain an estimator whose time complexity is O(L3 + c2dL2) where L is the length of input sequences and both c and d are constants independent of L. The proposed estimator can handle uncertainty of secondary structures and alignments that are obstacles in Bioinformatics because it considers all the secondary structures and all the pairwise alignments as input sequences. Moreover, we integrate the probabilistic consistency transformation (PCT) on alignments into the proposed estimator. Computational experiments using six benchmark datasets indicate that the proposed method achieved a favorable SPS and was the fastest of many state–of–the–art tools for multiple alignments of structured RNAs.
Availability: The software called CentroidAlign, which is an implementation of the algorithm in this paper, is freely available on our website:
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Results: We generated sixteen million 35 bp reads from mRNA of each of two HapMap Yoruba individuals. When we mapped these reads to the human genome we found that, at heterozygous SNPs, there was a significant bias towards higher mapping rates of the allele in the reference sequence, compared to the alternative allele. Masking known SNP positions in the genome sequence eliminated the reference bias but, surprisingly, did not lead to more reliable results overall. We find that even after masking, ~5-10% of SNPs still have an inherent bias towards more effective mapping of one allele. Filtering out inherently biased SNPs removes 40% of the top signals of ASE. The remaining SNPs showing ASE are enriched in genes previously known to harbor cis-regulatory variation or known to show uniparental imprinting. Our results have implications for a variety of applications involving detection of alternate alleles from short-read sequence data.
Availability: Scripts, written in Perl and R, for simulating short reads, masking SNP variation in a reference genome, and analyzing the simulation output are available upon request from JFD. Raw short read data were deposited in GEO (
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Results: We have developed HTqPCR, a package for the R statistical computing environment, to enable the processing and analysis of qPCR data across multiple conditions and replicates.
Availability: HTqPCR and user documentation can be obtained from the Bioconductor project, or at
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Results: In this paper we analyse how the Escherichia coli metabolic network responds to pruning in the form of sequential removal of metabolites with highest degree. As expected this leads to network fragmentation, but the process by which it occurs suggest modularity and long range correlations within the network. We find that the pruned networks contain longer paths than the random expectation, and that the paths that survive the pruning also exhibit a lower cost (no. of involved metabolites) compared to random paths in the full metabolic network. Finally we confirm that paths detected by pruning overlap with known metabolic pathways. We conclude that pruning reveals functional pathways in metabolic networks, where currency metabolites may be seen as ingredients in a well-balanced soup in which main metabolic production lines are immersed.
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