Results: We propose two methods for estimating molecular copy numbers from single uncalibrated expression images of tissues. These methods rely on expression variability between cells, due either to steady state fluctuations or unequal distribution of molecules during cell division, to make their estimates. We apply these methods to 152 protein fluorescence expression images of Drosophila melanogaster embryos during early development, generating copy number estimates for 14 genes in the segmentation network. We also analyze the effects of noise on our estimators and compare with empirical findings. Finally, we confirm an observation of Bar-Even et al., made in the much different setting of Saccharomyces cerevisiae, that steady state expression variance tends to scale with mean expression.
Availability: The data is all drawn from FlyEx (explained within), and is available at
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Results: In this paper we compare the performance of univariate and multivariate tests on both simulated and biological data. In the simulation study we demonstrate that high correlations equally affect the power of both, univariate as well as multivariate tests. In addition, for most of them the power is similarly affected by the dimensionality of the gene set and by the percentage of genes in the set, for which expression is changing between two pheno-types. The application of different test statistics to biological data reveals that three statistics (sum of squared t-tests, Hotelling's T2, N-statistic), testing different null hypotheses, find some common but also some complementing differentially expressed gene sets under specific settings. This demonstrates that due to comple-menting null hypotheses each test projects on different aspects of the data and for the analysis of biological data it is beneficial to use all three tests simultaneously instead of focusing exclusively on just one.
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Availability: Affy Exon Tissues track is freely available under the UCSC Genome Browser (
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Supplementary information: Supplementary data are available at Bioinformatics online.
]]>Availability: The executable and user manual can be freely downloaded from
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Results: We propose a gamma-bernoulli mixture model clustering algorithm (BMM), tailored for quantizing states from gamma and bernoulli distributed data, to determine the noisy attractors of stochastic GRN. BMM uses multiple data sources, naturally selects the number of states and can be extended to other parametric distributions according to the number and type of data sources available. We apply it to protein and RNA levels, and promoter occupancy state of a toggle switch and show that it can be bistable, tristable, or monostable depending on its internal noise level. We show that these results are in agreement with the patterns of differentiation of model cells whose pathway choice is driven by the switch. We further apply BMM to a model of the MeKS module of Bacillus subtilis, and the results match experimental data, demonstrating the usability of BMM.
Availability: Implementation software is available upon request.
Contact: andre.sanchesribeiro@tut.fi and xiaofeng.dai@tut.fi
]]>Results: We introduce the concept of k-link clustering for EST data. We evaluate how clustering error rates vary over a range of linkage thresholds. Using k-link, we show that type II error decreases in response to increasing the number of shared ESTs (ie. links) required. We observe a base level of type II error likely caused by the presence of unmasked low-complexity or repetitive sequence.We find that Type I error increases gradually with increased linkage. To minimise the type I error introduced by increased linkage requirements, we propose an extension to k-link which modifies the required number of links with respect to the size of clusters being compared.
Availability: The implementation of k-link is available under the terms of the GPL from
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Supplementary Information: Supplementary data are available at Bioinformatics online.
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Results: Comparison with known mHag data reveals that some but not all of the previously known mHags can be reproduced. By applying a system of filtering and ranking, we were able to produce an ordered list of potential mHag candidates in which HA-1, HA-3, and HA-8 occur in the best 0.25 per cent. By combining SNP, protein, tissue expression, and genotypic frequency data, together with antigen presentation prediction algorithms, we propose a list of the best peptide candidates which could potentially induce the graft versus leukemia effect without causing graft versus host disease.
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Results: This paper describes the development of an ontological framework for annotating CellML models with biophysical concepts. We demonstrate that, by using these ontological mappings, in com-bination with a set of graph reduction rules, it is possible to repre-sent the underlying biological process described in a CellML model.
]]>Availability: Haplowser, written in Java, supports multiple platforms including Windows and Linux. Haplowser is publicly available at
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Supplemental information: Supplemental data are available at
Availability: ITM Probe web service and documentation can be foundat
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Results: We have developed an Expert Review (ER) version of the Integrated Microbial Genomes (IMG) system, with the goal of supporting systematic and efficient revision of microbial genome annotations. IMG ER provides tools for the review and curation of annotations of both new and publicly available microbial genomes within IMG's rich integrated genome framework. New genome datasets are included into IMG ER prior to their public release either with their native annotations or with annotations generated by IMG ER's annotation pipeline. IMG ER tools allow addressing annotation problems detected with IMG's comparative analysis tools, such as genes missed by gene prediction pipelines or genes without an associated function. Over the past year, IMG ER was used for improving the annotations of about 150 microbial genomes.
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Results: We address this concern by constructing and analyzing an experimentally-based gold standard through comprehensive validation of protein function predictions for mitochondrion biogenesis in Saccharomyces cerevisiae. Specifically, we determine that A) current machine learning approaches are able to generalize and predict novel biology from an incomplete gold standard and B) incomplete functional annotations adversely affect the evaluation of machine learning performance. While computational approaches performed better than predicted in the face of incomplete data, relative comparison of competing approaches - even those employing the same training data - is problematic with a sparse gold standard. Incomplete knowledge causes individual methods' performances to be differentially underestimated, resulting in misleading performance evaluations. We provide a benchmark gold standard for yeast mitochondria to complement current databases and an analysis of our experimental results in the hopes of mitigating these effects in future comparative evaluations.
Availability: The mitochondrial benchmark gold standard, as well as experimental results and additional data, is available at
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Results: This paper describes a new methodology based on a hidden Markov model that embeds the segmentation of a continuous-valued signal in a probabilistic setting. For a computationally affordable cost, this framework (i) alleviates the difficulty of choosing a fixed number of breakpoints, and (ii) permits retrieving more information than a unique segmentation by giving access to the whole probability distribution of the transcription profile. Importantly, the model is also enriched and accounts for subtle effects such as signal "drift" and covariates. Relevance of this framework is demonstrated on a Bacillus subtilis data-set.
Availability: A software is distributed under the GPL.
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Results: We present Pindel, a pattern growth approach, to detect breakpoints of large deletions and medium sized insertions from paired-end short reads. We use both simulated reads and real data to demonstrate the efficiency of the computer program and accuracy of the results.
Availability: The binary code and a short user manual can be freely downloaded from
libSBML (Bornstein et al., 2008) is an application programming interface library for the manipulation of SBML files. While libSBML provides the facilities for reading and writing such annotations from and to models, it is beyond the scope of libSBML to provide interpretation of these terms. The libAnnotationSBML library introduced here acts as a layer on top of libSBML linking SBML annotations to the web services that describe these ontological terms. Two applications that use this library are described: SbmlSynonymExtractor finds name synonyms of SBML model entities, and SbmlReactionBalancer checks SBML files to determine whether specifed reactions are elementally balanced.
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Results: A conversion function is proposed to convert serum tests of antigens on patients to binary values based on which Boolean functions as the diagnostic patterns are developed. A genetic programming approach is designed for optimising the diagnostic patterns in terms of their accuracy and effectiveness. During optimisation, it is aimed to maximise the coverage (the rate of positive response to antigens) in the infected patients and minimize the coverage in the non-infected patients while maintaining the fewest number of testable antigens used in the Boolean functions as possible. The final cover-age in the infected patients is 96.55% using 17 of 215 (7.4%) antigens with zero coverage in the non-infected patients. Among these 17 antigens, BPSL2697 is the most frequently selected one for the diagnosis of Burkholderia Pseudomallei. The approach has been evaluated using both the cross-validation and the Jack-knife simulation methods with the prediction accuracy as 93% and 92%, respectively. A novel approach is also proposed in this study to evaluate a model with binary data using ROC analysis.
]]>Results: In consideration of the variability in tests results, we find that the widely used Benjamini and Hochberg's (BH) false discovery rate (FDR) analysis is less robust than alternative procedures. BH's error control requires a large number of hypothesis tests, a reasonable assumption for differential gene expression analysis, though not the case with pathway-based analysis. Therefore, we advocate through a series of simulations and applications to real gene expression data, that researchers control the number of false positives rather than the FDR.
Availability: Our R package, EPath.omg is available at
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Results: We apply a two-step nonlinear normalization method based on locally weighted regression (LOESS) approach to compare ChIPseq data across multiple samples and model the difference using an Exponential-NormalKmixture model. Fitted model is used to identify genes associated with differential binding sites based on local false discovery rate (fdr). These genes are then standardized and hierarchically clustered to characterize their Pol II binding patterns. As a case study, we apply the analysis procedure comparing normal breast cancer (MCF7) to tamoxifen-resistant (OHT) cell line. We find enriched regions that are associated with cancer (p-value < 0.0001). Our findings also imply that there may be a dysregulation of cell cycle and gene expression control pathways in the tamoxifen resistant cells. These results show that the nonlinear normalization method can be used to analyze ChIP-seq data.
Availability: Data is available at
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Supplementary info: Supplementary figures and tables are available at Bioinformatics online.
]]>Results and Implementation: In this light, we developed a novel network based approach which considers gene expression within each replicate across its entire gene expression profile, and identifies outliers across replicates. The power of this method is demonstrated by its ability to enrich for distant metastasis related genes derived from noisy expression data of CD44+CD24-/low tumor initiating cells.
]]>Results: Here we first curate a large, non-redundant, and balanced training set of more than 17,000 proteins. Next, we extract and study twenty three groups of features computed directly or predicted (e.g. secondary structure) from the primary sequence. The data and the features are used to train a two-stage SVM architecture. The resulting predictor, SOLpro, is compared directly to existing methods and shows significant improvement according to standard evaluation metrics, with an overall accuracy of over 74% estimated using multiple runs of ten-fold cross-validation.
Availability: SOLpro is integrated in the SCRATCH suite of predictors and is available for download as a stand-alone application and as a web server at:
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Results: In this paper we describe Swift, a new tool for performing primary data analysis on the Illumina Solexa Sequencing Platform. Swift is the first tool, outside of the vendors own software, which completes the full analysis process, from raw images through to base-calls. As such it provides an alternative to, and independent validation of, the vendor supplied tool. Our results show that Swift is able to increase yield by 13.8%, at comparable error rate.
Availability and Implementation: Swift is implemented in C++ and supported under Linux. It is supplied under an open source license (LGPL3), allowing researchers to build upon the platform. Swift is available from
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Supplementary Information: Details, examples and tutorials can be found at
Results: We present SHREC, a new algorithm for correcting errors in short-read data that uses a generalized suffix trie on the read data as the underlying data structure. Our results show that the method can identify erroneous reads with sensitivity and specificity of over 99% and 96% for simulated data with error rates of up to 3% as well as for real data. Furthermore, it achieves an error correction accuracy of over 80% for simulated data and over 88% for real data. These results are clearly superior to previously published approaches. SHREC is available as an efficient open-source Java implementa-tion that allows processing of ten million of short reads on a stan-dard workstation.
Availability: SHREC source code in JAVA is freely available at
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Results: We present ISOLATE, a new statistical method that simultaneously predicts the primary site of origin of cancers and addresses sample heterogeneity, while taking advantage of new high throughput sequencing technology that promises to bring higher accuracy and reproducibility to gene expression profiling experiments. ISOLATE makes predictions de novo, without having seen any training expression profiles of cancers with identified origin. Compared to previous methods, ISOLATE is able to predict the primary site of origin, de-convolve and remove the effect of sample heterogeneity, and identify differentially expressed genes with higher accuracy, across both synthetic and clinical datasets. Methods such as ISOLATE are invaluable tools for clinicians faced with carcinomas of unknown primary origin.
Availability: ISOLATE is available for download at:
Contact: {gerald.quon, quaid.morris}@utoronto.ca
]]>Results: Considering the reconstruction of gene network as a matrix factorization problem, we first use the gene expression data to estimate a correlation matrix, and then factorize the correlation matrix to recover the gene modules and the interactions between them. Prior knowledge from Gene Ontology is integrated into the matrix factorization. We applied this KMF algorithm to hepatocellular carcinoma (HepG2) cells treated with free fatty acids (FFAs). By comparing the module networks for the different conditions, we identified the specific modules that are involved in conferring the cytotoxic phenotype induced by palmitate. Further analysis of the gene modules of the different conditions suggested individual genes that play important roles in palmitate-induced cytotoxicity. In summary, KMF can efficiently integrate gene expression data with prior knowledge, thereby providing a powerful method of reconstructing phenotype-specific gene networks and valuable insights into the mechanisms that govern the phenotype.
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Results: We infer pathway topologies from gene knockdown data using Bayesian networks with probabilistic Boolean threshold functions. To deal with the problem of under-determined network parameters, we employ a Bayesian learning approach, in which we can integrate arbitrary prior information on the network under consideration. Missing observations are integrated out. We compute the exact likelihood function for smaller networks, and use an approximation to evaluate the likelihood for larger networks. The posterior distribution is evaluated using mode hopping Markov chain Monte Carlo, distributions over topologies and parameters can then be used to design additional experiments. We evaluate our approach on a small artificial dataset, and present inference results on RNAi data from the Jak/Stat pathway in a human hepatoma cell line.
Availability: Software is available on request.
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Supplementary Information: Available at Bioinformatics online.
]]>Availability and Implementation: Source code and documentation freely available at
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Supplementary Information: Supplementary data are available at Bioinformatics online.
]]>Results: We propose an effective and efficient pairwise sequence alignment algorithm, called GR-Aligner, which can find breakpoints of rearrangement events by integrating the forward and reverse alignments of the breakpoint regions flanked by homologously rearranged sequences. In addition, GR-Aligner also provides an option to view the alignments of sequences extended to the breakpoints. These outputs provide materials for studying possible evolutionary mechanisms and biological functionalities of the rearrangement.
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Results: Statistical analysis of observational data produced results consistent with those anticipated from theoretical mathematical properties. Average beta value reported by Illumina GoldenGate (a bead-array platform) was significantly smaller than a similar measure constructed from the ratio of average dye intensities. Among CpGs that had only small variations in measured methylation across tumors (filtering out clearly biological methylation signatures), there were no systematic copy number effects on methylation for 3 and 4+ copies; however, 1 copy led to small systematic negative effects, and 0 copies led to substantial significant negative effects.
Conclusions: Since mathematical considerations suggest little bias in methylation assayed using bead-arrays, the consistency of observational data with anticipated properties suggests little bias.However, further analysis of systematic copy number effects across CpGs suggest that though there may be little bias when there are copy number gains, small biases may result when 1 allele is lost, and substantial biases when both alleles are lost. These results suggest that further integration of these measures can be useful for characterizing the biological relationships between these somatic events.
]]>Availability and Implementation: Source code in C running on Linux is freely available at
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Results: As with our method for earlier generations of arrays, this one controls for allelic crosstalk, probe affinities and PCR fragmentlength effects. Additionally, it also corrects for probe-sequence effects and co-hybridization of fragments digested by multiple enzymes that takes place on the latest chips. We compare our method with Affymetrix' CN5 method and the dChip method by assessing how well they differentiate between various CN states at the full resolution and various amounts of smoothing. Although CRMA v2 is a singlearray method, we observe that it performs as well as or better than alternative methods that use data from all arrays for their preprocessing. This shows that it is possible to do online analysis in large-scale projects where additional arrays are introduced over time.
Availability: A bounded-memory implementation that can process any number of arrays is available in the open-source R package aroma.affymetrix.
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Supplementary information: Supplementary data are available at Bioinformatics online.
]]>Results: We propose a software package, PhyloBayes 3, that can be used for conducting Bayesian phylogenetic reconstruction and molecular dating analyses, using a large variety of amino-acid replacement and nucleotide substitution models, including empirical mixtures or non-parametric models, as well as alternative clock relaxation processes.
Availability: PhyloBayes is freely available from our website
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Results: Very often, although the target protein is novel, it has a homologous protein included in a known database. When this happens, we propose a novel algorithm and automated software tool, named Champs, for sequencing the complete protein from MS/MS data of a few enzymatic digestions of the purified protein. Validation with two standard proteins showed that our automated method yields greater than 99% sequence coverage and 100% sequence accuracy on these two proteins. Our method is useful to sequence novel proteins or "re-sequence" a protein that has mutations comparing with the database protein sequence.
Availability: The software is freely available at
Results: We present a statistical model that carefully accounts for informative missingness in peak intensities and allows unbiased, model-based, protein-level estimation and inference. The model is applicable to both label-based and label-free quantitation experiments. We also provide automated, model-based, algorithms for filtering of proteins and peptides as well as imputation of missing values. Two LC-MS datasets are used to illustrate the methods. In simulation studies, our methods are shown to achieve substantially more discoveries than standard alternatives.
Availability: The software has been made available in the open-source proteomics platform DAnTE (Polpitiya et al. (2008)) (
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Results: : We developed a graphical modeling system for multi-agent based simulation of tissue homeostasis. An editor allows the intuitive and hierarchically structured specification of cellular behavior. The models are then automatically compiled into highly efficient source code and dynamically linked to an interactive graphical simulation environment. The system allows the quantitative analysis of the morphological and functional tissue properties emerging from the cell behavioral model. We demonstrate the relevance of the approach using a recently published model of epidermal homeostasis as well as a series of cell cycle models.
Availability: The complete software is available in binary executables for MS-Windows and Linux at tiga.uni-hd.de
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Results: We compared the observed empirical distributions with a number of distributions: power law, lognormal, loglogistic, loggamma, right Pareto-lognormal, and double Pareto-lognormal. The best-fit for mRNA, protein, and metabolite population abundance distributions was found to be the double Pareto-lognormal. This distribution behaves like a lognormal distribution around the centre, and like a power law distribution in the tails. To better understand the cause of this observed distribution we explored a simple stochastic model based on geometric Brownian motion. The distribution indicates that multiplicative effects are causally dominant in biological systems. We speculate that these effects arise from chemical reactions: the central-limit theorem then explains the central lognormal, and a number of possible mechanisms could explain the long tails - positivefeedback effects, network topology, etc. Many of the components in the central lognormal parts of the empirical distributions are unidentified and/or have unknown function. This indicates that much more biology awaits discovery.
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Results: The SADR-Gengle database, which is made up of gene-SADR relationships extracted from Pubmed, has been constructed, covering six major SADRs, namely cholestasis, deafness, muscle toxicity, QT prolongation, Stevens-Johnson syndrome and torsades de points. The CitationRank algorithm, which inherits the principle of the Google PageRank algorithm that a gene should be highly ranked when biologically related to other highly ranked genes, is devised. The algorithm performs robustly in recovering SADR related genes in the presence of extraneous noise, and the use of the algorithm has been extended to sorting genes in our database. Users can browse genes in a Google-type system where genes are ordered according to their descending relevance to the SADR topic selected by the user. The database also provides users with visualized gene-gene knowledge chain networks, helping them to systematize their gene-oriented knowledge chain whilst navigating these networks.
Availability: The SADR-Gengle is freely available at
Contact: Lin He helinhelin@gmail.com or Lun Yang Lun.Yang@gmail.com
]]>Results: Transcriptome from tumor tissue of a patient with follicular lymphoma was sequenced with 36 base-pair (bp) single- and paired-end reads on the Illumina Genome Analyzer II platform. We assembled approximately 194 million reads using ABySS into 66,921 contigs 100bp or longer, with a maximum contig length of 10,951bp, representing over 30 million base pairs of unique transcriptome sequence, or roughly 1% of the genome.
Availability and Implementation: Source code and binaries of ABySS are freely available for download at
Contact: Software help: abyss@bcgsc.ca, authors {ibirol, sjackman, cydneyn, jqian, sjones}@bcgsc.ca
]]>Results: This paper develops an efficient method that can accurately model the progression of the cancer markers and reconstruct evolutionary relationship between multiple types of cancers using Comparative Genomic Hybridization (CGH) data. Such modeling can lead to better understanding of the commonalities and differences between multiple cancer types and potential therapies. We have developed an automatic method to infer a graph model for the markers of multiple cancers from a large population of CGH data. Our method identifies highly related markers across different cancer types. It then builds a directed acyclic graph that shows the evolutionary history of these markers based on how common each marker is in different cancer types. We demonstrated the use of this model in determining the importance of markers in cancer evolution. We have also developed a new method to measure the evolutionary distance between different cancers based on their markers. This method employs the graph model we developed for the individual markers to measure the distance between pairs of cancers. We used this measure to create an evolutionary tree for multiple cancers.
Our experiments on Progenetix database show that our markers are largely consistent to the reported hot-spot imbalances and most frequent imbalances. The results show that our distance measure can accurately reconstruct the evolutionary relationship between multiple cancer types.
Availability: All the code developed in this paper are available at
Contact: nirmalya@cise.ufl.edu
]]>Results: With unbalanced data, permutation tests may not be suitable because they do not test the hypothesis of interest. In addition, permutation tests can be biased. Using biased p-values to estimate the false discovery rate can produce unacceptable bias in those estimates. Results also show that the approach of pooling permutation null distributions across genes can produce invalid p-values, since even non-differentially-expressedgenes can have different permutation null distributions.We encourage researchers to use statistics that have been shown to reliably discriminate differentially-expressed genes, but caution that associated p-values may be either invalid, or a less effective metric for discriminating differentially-expressed genes.
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Results: In this paper, we first systematically analyze the similarities and differences between the two types of promoters (CGI-related and non-CGI-related) from a novel structural perspective, and then devise a unified framework, called PNNP (Pattern-based Nearest Neighbor search for Promoter), to predict both CGI-related and non-CGIrelated promoters based on their structural features. Our comparative analysis on the structural characteristics of promoters reveals two interesting facts: 1) the structural values of CGI-related and non-CGI-related promoters are quite different, but they exhibit nearly similar structural patterns; 2) the structural patterns of promoters are obviously different from that of non-promoter sequences though the sequences have almost similar structural values. Extensive experiments demonstrate that the proposed PNNP approach is effective in capturing the structural patterns of promoters, and can significantly improve genome-wide performance of promoters prediction, especially non-CGI-related promoters prediction.
Availability: The implementation of the program PNNP is available at
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Availability: The software is available for download at
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Supplemental information: Supplemental data are available from Bioinformatics online and
Results: Previously, we proposed a coarse-grained, quantitative approach based on the basic Petri net formalism, to mimic the behaviour of the biological processes during multicellular differentiation. Here we apply our modelling approach to the well-studied process of C. elegans vulval development. We show that our model correctly reproduces a large set of in vivo experiments with statistical accuracy. It also generates gene expression time series in accordance with recent biological evidence. Finally, we modelled the role of microRNA mir-61 during vulval development and predict its contribution in stabilising cell pattern formation.
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Results: This paper describes two new and helpful techniques for comparing multiple metagenomic datasets. The first is a visualization technique for multiple datasets and the second is a new statistical method for highlighting the differences in a pairwise comparison. We have developed implementations of both methods that are suitable for very large datasets and provide these in Version 3 of our stand-alone metagenome analysis tool MEGAN.
Conclusion: These new methods are suitable for the visual comparison of many large metagenomes and the statistical comparison of two metagenomes at a time. Nevertheless, more work needs to be done to support the comparative analysis of multiple metagenome datasets.
Availability: Version 3 of MEGAN, which implements all ideaspresented in this paper, can be obtained from our website at:
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