%% This BibTeX bibliography file was created using BibDesk.
%% http://bibdesk.sourceforge.net/


%% Created for Eric Coissac at 2019-05-20 11:33:01 +0200 


%% Saved with string encoding Unicode (UTF-8) 


@comment{jabref-meta: selector_publisher:}
@comment{jabref-meta: selector_author:}
@comment{jabref-meta: selector_journal:}
@comment{jabref-meta: selector_keywords:}



@misc{CSoRgo:96:00,
	Author = {Cs{\"o}rg{\H o}, S{\'a}ndor and Faraway, Julian J},
	Date-Added = {2019-05-20 11:28:37 +0200},
	Date-Modified = {2019-05-20 11:32:25 +0200},
	Journal = {Journal of the Royal Statistical Society: Series B (Methodological)},
	Number = 1,
	Pages = {221--234},
	Title = {The Exact and Asymptotic Distributions of {Cram{\'e}r-Von} Mises Statistics},
	Volume = 58,
	Year = 1996}

@article{Robert:76:00,
	Abstract = {[Consider two data matrices on the same sample of n individuals,
               X(p $\times$ n), Y(q $\times$ n). From these matrices,
               geometrical representations of the sample are obtained as two
               configurations of n points, in Rp and Rq. It is shown that the
               RV-coefficient (Escoufier, 1970, 1973) can be used as a measure
               of similarity of the two configurations, taking into account the
               possibly distinct metrics to be used on them to measure the
               distances between points. The purpose of this paper is to show
               that most classical methods of linear multivariate statistical
               analysis can be interpreted as the search for optimal linear
               transformations or, equivalently, the search for optimal metrics
               to apply on two data matrices on the same sample; the optimality
               is defined in terms of the similarity of the corresponing
               configurations of points. which, in turn, calls for the
               maximization of the associated RV-coefficient. The methods
               studied are principal components, principal components of
               instrumental variables, multivariate regression, canonical
               variables, discriminant analysis; they are differentiated by the
               possible relationships existing between the two data matrices
               involved and by additional constraints under which the maximum
               of RV is to be obtained. It is also shown that the
               RV-coefficient can be used as a measure of goodness of a
               solution to the problem of discarding variables.]},
	Author = {Robert, P and Escoufier, Y},
	Date-Added = {2019-05-17 10:53:50 +0200},
	Date-Modified = {2019-05-17 10:54:04 +0200},
	Journal = {J. R. Stat. Soc. Ser. C Appl. Stat.},
	Number = 3,
	Pages = {257--265},
	Publisher = {[Wiley, Royal Statistical Society]},
	Title = {A Unifying Tool for Linear Multivariate Statistical Methods: The {RV-} Coefficient},
	Volume = 25,
	Year = 1976}

@article{Mayer:11:00,
	Abstract = {The integration of multiple high-dimensional data sets (omics
              data) has been a very active but challenging area of
              bioinformatics research in recent years. Various adaptations of
              non-standard multivariate statistical tools have been suggested
              that allow to analyze and visualize such data sets
              simultaneously. However, these methods typically can deal with
              two data sets only, whereas systems biology experiments often
              generate larger numbers of high-dimensional data sets. For this
              reason, we suggest an explorative analysis of similarity between
              data sets as an initial analysis steps. This analysis is based on
              the RV coefficient, a matrix correlation, that can be interpreted
              as a generalization of the squared correlation from two single
              variables to two sets of variables. It has been shown before
              however that the high-dimensionality of the data introduces
              substantial bias to the RV. We therefore introduce an alternative
              version, the adjusted RV, which is unbiased in the case of
              independent data sets. We can also show that in many situations,
              particularly for very high-dimensional data sets, the adjusted RV
              is a better estimator than previously RV versions in terms of the
              mean square error and the power of the independence test based on
              it. We demonstrate the usefulness of the adjusted RV by applying
              it to data set of 19 different multivariate data sets from a
              systems biology experiment. The pairwise RV values between the
              data sets define a similarity matrix that we can use as an input
              to a hierarchical clustering or a multidimensional scaling. We
              show that this reveals biological meaningful subgroups of data
              sets in our study.},
	Author = {Mayer, Claus-Dieter and Lorent, Julie and Horgan, Graham W},
	Date-Added = {2019-05-17 10:52:46 +0200},
	Date-Modified = {2019-05-17 10:52:51 +0200},
	Journal = {Stat. Appl. Genet. Mol. Biol.},
	Language = {en},
	Pages = {Article 14},
	Title = {Exploratory analysis of multiple omics datasets using the adjusted {RV} coefficient},
	Volume = 10,
	Year = 2011}

@article{El-Ghaziri:15:00,
	Abstract = {We review three measures of association between two datasets in
              view of their use in sensory data. The aim is threefold: (i) to
              show in which situations each measure of association is
              appropriate, (ii) to show their properties and how they can be
              applied efficiently to sensory data, (iii) to compare them. The
              three measures of association are multivariate correlation
              coefficient, RV coefficient and Procrustes similarity index. A
              particular emphasis is put on RV coefficient since it is very
              popular among sensory scientists. We stress the properties and
              shortcomings of this coefficient and propose an adjusted RV
              coefficient to be used instead of RV coefficient, particularly in
              situations where the number of samples is small or/and the number
              of variables is large.},
	Author = {El Ghaziri, Ang{\'e}lina and Qannari, El Mostafa},
	Date-Added = {2019-05-17 10:52:46 +0200},
	Date-Modified = {2019-05-17 10:52:51 +0200},
	Journal = {Food Qual. Prefer.},
	Keywords = {Multivariate correlation coefficient; Procrustes similarity index; RV coefficient; Permutation test; Adjusted RV coefficient},
	Month = mar,
	Pages = {116--124},
	Title = {Measures of association between two datasets; Application to sensory data},
	Volume = 40,
	Year = 2015}

@article{Jackson:95:00,
	Abstract = {Abstract:A multivariate measure of the concordance or
               association between matrices of species abundances and
               environmental variables was generally lacking in ecology until
               recently. Traditional statistical procedures comparing such
               relationships are often unsuitable because of non-linearity
               among species and/or environmental data. To address these
               problems, I propose a randomization test based on Procrustes
               analysis. One matrix is subject to reflection, rigid rotation,
               translation, and dilation to minimize the sum of the squared
               residual deviations between points for each observation and the
               identical observation in the target matrix. This is a classical
               Procrustes approach to matrix analysis. To assess the
               significance of this measure of matrix concordance, I use a
               randomization test to determine whether the sum of residual
               deviations is less than that expected by chance. The PROcrustean
               randomization TEST (PROTEST) may be used with either raw data
               matrices or with multivariate summaries of the original data
               (i.e. both direct or indirect gradient analysis). I provide
               examples of PROTEST analyses with benthic invertebrate
               communities, lake-water chemistry, lake morphology, and lake
               geographic position. Significant concordance between the benthic
               community and both lake-water chemistry and geographic position
               were found. PROTEST results differed from Mantel test results as
               the choice of distance measure with Mantel tests will influence
               the level of significance obtained.},
	Author = {Jackson, Donald A},
	Date-Added = {2019-05-14 18:22:51 +0200},
	Date-Modified = {2019-05-14 18:22:54 +0200},
	Journal = {{\'E}coscience},
	Month = jan,
	Number = 3,
	Pages = {297--303},
	Publisher = {Taylor \& Francis},
	Title = {{PROTEST}: A {PROcrustean} Randomization {TEST} of community environment concordance},
	Volume = 2,
	Year = 1995}

@article{Dray:07:00,
	Abstract = {Multivariate analyses are well known and widely used to identify
              and understand structures of ecological communities. The ade4
              package for the R statistical environment proposes a great number
              of multivariate methods. Its implementation follows the tradition
              of the French school of ``Analyse des Donnees'' and is based on
              the use of the duality diagram. We present the theory of the
              duality diagram and discuss its implementation in ade4. Classes
              and main functions are presented. An example is given to
              illustrate the ade4 philosophy.},
	Author = {Dray, St{\'e}phane and Dufour, Anne-B{\'e}atrice},
	Date-Added = {2019-05-13 19:18:23 +0200},
	Date-Modified = {2019-05-13 19:18:25 +0200},
	Journal = {Journal of Statistical Software, Articles},
	Number = 4,
	Pages = {1--20},
	Title = {The ade4 Package: Implementing the Duality Diagram for Ecologists},
	Volume = 22,
	Year = 2007}

@article{Dixon:03:00,
	Abstract = {Abstract. VEGAN adds vegetation analysis functions to the
              general-purpose statistical program R. Both R and VEGAN can be
              downloaded for free. VEGAN implements several ordination methods,
              including Canonical Correspondence Analysis and Non-metric
              Multidimensional Scaling, vector fitting of environmental
              variables, randomization tests, and various other analyses of
              vegetation data. It can be used for large data. Graphical output
              can be customized using the R language's extensive graphics
              capabilities. VEGAN is appropriate for routine and research use,
              if you are willing to learn some R.},
	Author = {Dixon, Philip},
	Date-Added = {2019-05-13 19:15:06 +0200},
	Date-Modified = {2019-05-13 19:15:09 +0200},
	Journal = {J. Veg. Sci.},
	Month = dec,
	Number = 6,
	Pages = {927--930},
	Title = {{VEGAN}, a package of {R} functions for community ecology},
	Volume = 14,
	Year = 2003}

@book{Bravais:44:00,
	Author = {Bravais, A},
	Date-Added = {2019-05-10 13:28:14 +0200},
	Date-Modified = {2019-05-10 13:28:16 +0200},
	Language = {fr},
	Publisher = {Impr. Royale},
	Title = {Analyse math{\'e}matique sur les probabilit{\'e}s des erreurs de situation d'un point},
	Year = 1844}

@article{Peres-Neto:01:00,
	Abstract = {The Mantel test provides a means to test the association between
              distance matrices and has been widely used in ecological and
              evolutionary studies. Recently, another permutation test based on
              a Procrustes statistic (PROTEST) was developed to compare
              multivariate data sets. Our study contrasts the effectiveness, in
              terms of power and type I error rates, of the Mantel test and
              PROTEST. We illustrate the application of Procrustes
              superimposition to visually examine the concordance of
              observations for each dimension separately and how to conduct
              hypothesis testing in which the association between two data sets
              is tested while controlling for the variation related to other
              sources of data. Our simulation results show that PROTEST is as
              powerful or more powerful than the Mantel test for detecting
              matrix association under a variety of possible scenarios. As a
              result of the increased power of PROTEST and the ability to
              assess the match for individual observations (not available with
              the Mantel test), biologists now have an additional and powerful
              analytical tool to study ecological and evolutionary
              relationships.},
	Author = {Peres-Neto, Pedro R and Jackson, Donald A},
	Date-Added = {2019-05-10 12:59:02 +0200},
	Date-Modified = {2019-05-10 12:59:05 +0200},
	Journal = {Oecologia},
	Keywords = {Mantel test; Matrix association; Multivariate analysis; Procrustes analysis; Randomization test},
	Language = {en},
	Month = oct,
	Number = 2,
	Pages = {169--178},
	Title = {How well do multivariate data sets match? The advantages of a Procrustean superimposition approach over the Mantel test},
	Volume = 129,
	Year = 2001}

@article{Gower:71:00,
	Author = {Gower, J C},
	Date-Added = {2019-04-19 12:11:20 +0200},
	Date-Modified = {2019-04-19 12:11:23 +0200},
	Journal = {Mathematics in the archaeological and historical sciences},
	Pages = {138--149},
	Publisher = {Edinburgh University Press Edinburgh},
	Title = {Statistical methods of comparing different multivariate analyses of the same data},
	Year = 1971}

@article{Lingoes:74:00,
	Abstract = {In connection with a least-squares solution for fitting one
              matrix,A, to another,B, under optimal choice of a rigid motion
              and a dilation, Sch{\"o}nemann and Carroll suggested two measures
              of fit: a raw measure,e, and a refined similarity measure,es,
              which is symmetric. Both measures share the weakness of depending
              upon the norm of the target matrix,B,e.g.,e(A,kB) $\neq$e(A,B)
              fork $\neq$ 1. Therefore, both measures are useless for answering
              questions of the type: ``DoesA fitB better thanA fitsC?''. In
              this note two new measures of fit are suggested which do not
              depend upon the norms ofA andB, which are (0, 1)-bounded, and
              which, therefore, provide meaningful answers for comparative
              analyses.},
	Author = {Lingoes, James C and Sch{\"o}nemann, Peter H},
	Date-Added = {2019-04-19 12:07:12 +0200},
	Date-Modified = {2019-04-19 12:07:17 +0200},
	Journal = {Psychometrika},
	Month = dec,
	Number = 4,
	Pages = {423--427},
	Title = {Alternative measures of fit for the Sch{\"o}nemann-carroll matrix fitting algorithm},
	Volume = 39,
	Year = 1974}

@article{SzeKely:13:00,
	Address = {Orlando, FL, USA},
	Author = {Sz{\'e}Kely, G{\'a}bor J and Rizzo, Maria L},
	Date-Added = {2019-04-19 00:38:28 +0200},
	Date-Modified = {2019-04-19 00:38:39 +0200},
	Journal = {J. Multivar. Anal.},
	Keywords = {Distance correlation, Distance covariance, High dimension, Multivariate independence, dCor, dCov, primary, secondary},
	Month = may,
	Pages = {193--213},
	Publisher = {Academic Press, Inc.},
	Title = {The Distance Correlation T-test of Independence in High Dimension},
	Volume = 117,
	Year = 2013}

@article{Szekely:07:00,
	Abstract = {Project Euclid - mathematics and statistics online},
	Author = {Sz{\'e}kely, G{\'a}bor J and Rizzo, Maria L and Bakirov, Nail K},
	Date-Added = {2019-04-19 00:25:31 +0200},
	Date-Modified = {2019-04-19 00:25:35 +0200},
	Journal = {Ann. Stat.},
	Keywords = {Distance correlation; distance covariance; multivariate independence},
	Language = {en},
	Month = dec,
	Number = 6,
	Pages = {2769--2794},
	Publisher = {Institute of Mathematical Statistics},
	Title = {Measuring and testing dependence by correlation of distances},
	Volume = 35,
	Year = 2007}

@article{Escoufier:73:00,
	Author = {Escoufier, Yves},
	Date-Added = {2019-04-19 00:11:19 +0200},
	Date-Modified = {2019-04-19 00:11:23 +0200},
	Journal = {Biometrics},
	Pages = {751--760},
	Publisher = {JSTOR},
	Title = {Le traitement des variables vectorielles},
	Year = 1973}

@article{Smilde:09:00,
	Abstract = {MOTIVATION: Modern functional genomics generates high-dimensional
              datasets. It is often convenient to have a single simple number
              characterizing the relationship between pairs of such
              high-dimensional datasets in a comprehensive way. Matrix
              correlations are such numbers and are appealing since they can be
              interpreted in the same way as Pearson's correlations familiar to
              biologists. The high-dimensionality of functional genomics data
              is, however, problematic for existing matrix correlations. The
              motivation of this article is 2-fold: (i) we introduce the idea
              of matrix correlations to the bioinformatics community and (ii)
              we give an improvement of the most promising matrix correlation
              coefficient (the RV-coefficient) circumventing the problems of
              high-dimensional data. RESULTS: The modified RV-coefficient can
              be used in high-dimensional data analysis studies as an easy
              measure of common information of two datasets. This is shown by
              theoretical arguments, simulations and applications to two
              real-life examples from functional genomics, i.e. a
              transcriptomics and metabolomics example. AVAILABILITY: The
              Matlab m-files of the methods presented can be downloaded from
              http://www.bdagroup.nl.},
	Author = {Smilde, A K and Kiers, H A L and Bijlsma, S and Rubingh, C M and van Erk, M J},
	Date-Added = {2019-04-19 00:08:07 +0200},
	Date-Modified = {2019-04-19 00:08:17 +0200},
	Journal = {Bioinformatics},
	Language = {en},
	Month = feb,
	Number = 3,
	Pages = {401--405},
	Title = {Matrix correlations for high-dimensional data: the modified {RV-coefficient}},
	Volume = 25,
	Year = 2009}

@article{Ramsay:84:00,
	Abstract = {A correlational measure for ann byp matrixX and ann byq matrixY
              assesses their relation without specifying either as a fixed
              target. This paper discusses a number of useful measures of
              correlation, with emphasis on measures which are invariant with
              respect to rotations or changes in singular values of either
              matrix. The maximization of matrix correlation with respect to
              transformationsXL andYM is discussed where one or both
              transformations are constrained to be orthogonal. Special
              attention is focussed on transformations which causeXL andYM to
              ben bys, wheres may be any number between 1 and min (p, q). An
              efficient algorithm is described for maximizing the correlation
              betweenXL andYM where analytic solutions do not exist. A factor
              analytic example is presented illustrating the advantages of
              various coefficients and of varying the number of columns of the
              transformed matrices.},
	Author = {Ramsay, J O and ten Berge, Jos and Styan, G P H},
	Date-Added = {2019-04-18 23:38:55 +0200},
	Date-Modified = {2019-04-18 23:39:01 +0200},
	Journal = {Psychometrika},
	Month = sep,
	Number = 3,
	Pages = {403--423},
	Title = {Matrix correlation},
	Volume = 49,
	Year = 1984}

@article{Boffelli03,
	Abstract = {BACKGROUND: The discovery of functional non-coding RNA sequences has
    led to an increasing interest in algorithms related to RNA analysis.
    Traditional sequence alignment algorithms, however, fail at computing
    reliable alignments of low-homology RNA sequences. The spatial conformation
    of RNA sequences largely determines their function, and therefore
    RNA alignment algorithms have to take structural information into
    account. RESULTS: We present a graph-based representation for sequence-structure
    alignments, which we model as an integer linear program (ILP). We
    sketch how we compute an optimal or near-optimal solution to the
    ILP using methods from combinatorial optimization, and present results
    on a recently published benchmark set for RNA alignments. CONCLUSION:
    The implementation of our algorithm yields better alignments in terms
    of two published scores than the other programs that we tested: This
    is especially the case with an increasing number of input sequences.
    Our program LARA is freely available for academic purposes from http://www.planet-lisa.net.},
	Author = {Markus Bauer and Gunnar W Klau and Knut Reinert},
	Doi = {10.1186/1471-2105-8-271},
	Institution = {Department of Mathematics and Computer Science, Free University Berlin, Berlin, Germany. mbauer@inf.fu-berlin.de},
	Journal = {BMC Bioinformatics},
	Keywords = {Algorithms; Computer Simulation; Linear Models; Models, Chemical; Models, Genetic; RNA; Sensitivity and Specificity; Sequence Alignment; Sequence Analysis, RNA; Sequence Homology, Nucleic Acid},
	Owner = {binf007},
	Pages = {271},
	Pii = {1471-2105-8-271},
	Pmid = {17662141},
	Timestamp = {2008.01.21},
	Title = {{Accurate multiple sequence-structure alignment of RNA sequences using combinatorial optimization.}},
	Url = {http://dx.doi.org/10.1186/1471-2105-8-271},
	Volume = {8},
	Year = {2007},
	Bdsk-Url-1 = {http://dx.doi.org/10.1186/1471-2105-8-271}}

@article{Bag01,
	Abstract = {SUMMARY: ProfDist is a user-friendly software package using the profile-neighbor-joining
    method (PNJ) in inferring phylogenies based on profile distances
    on DNA or RNA sequences. It is a tool for reconstructing and visualizing
    large phylogenetic trees providing new and standard features with
    a special focus on time efficency, robustness and accuracy. AVAILABILITY:
    A Windows version of ProfDist comes with a graphical user interface
    and is freely available at http://profdist.bioapps.biozentrum.uni-wuerzburg.de},
	Author = {Joachim Friedrich and Thomas Dandekar and Matthias Wolf and Tobias M{\"u}ller},
	Doi = {10.1093/bioinformatics/bti289},
	Institution = {Department of Bioinformatics, Biocenter, University of W{\"u}rzburg, Germany.},
	Journal = {Bionformatics},
	Keywords = {Algorithms; Chromosome Mapping; DNA Mutational Analysis; Gene Expression Profiling; Linkage Disequilibrium; Phylogeny; Sequence Alignment; Sequence Analysis, DNA; Software; User-Computer Interface},
	Month = {May},
	Number = {9},
	Owner = {binf007},
	Pages = {2108--2109},
	Pii = {bti289},
	Pmid = {15677706},
	Timestamp = {2008.01.21},
	Title = {{ProfDist: a tool for the construction of large phylogenetic trees based on profile distances.}},
	Url = {http://dx.doi.org/10.1093/bioinformatics/bti289},
	Volume = {21},
	Year = {2005},
	Bdsk-Url-1 = {http://dx.doi.org/10.1093/bioinformatics/bti289}}

@article{Gascuel1997,
	Abstract = {We propose an improved version of the neighbor-joining (NJ) algorithm
    of Saitou and Nei. This new algorithm, BIONJ, follows the same agglomerative
    scheme as NJ, which consists of iteratively picking a pair of taxa,
    creating a new mode which represents the cluster of these taxa, and
    reducing the distance matrix by replacing both taxa by this node.
    Moreover, BIONJ uses a simple first-order model of the variances
    and covariances of evolutionary distance estimates. This model is
    well adapted when these estimates are obtained from aligned sequences.
    At each step it permits the selection, from the class of admissible
    reductions, of the reduction which minimizes the variance of the
    new distance matrix. In this way, we obtain better estimates to choose
    the pair of taxa to be agglomerated during the next steps. Moreover,
    in comparison with NJ's estimates, these estimates become better
    and better as the algorithm proceeds. BIONJ retains the good properties
    of NJ--especially its low run time. Computer simulations have been
    performed with 12-taxon model trees to determine BIONJ's efficiency.
    When the substitution rates are low (maximum pairwise divergence
    approximately 0.1 substitutions per site) or when they are constant
    among lineages, BIONJ is only slightly better than NJ. When the substitution
    rates are higher and vary among lineages,BIONJ clearly has better
    topological accuracy. In the latter case, for the model trees and
    the conditions of evolution tested, the topological error reduction
    is on the average around 20\%. With highly-varying-rate trees and
    with high substitution rates (maximum pairwise divergence approximately
    1.0 substitutions per site), the error reduction may even rise above
    50\%, while the probability of finding the correct tree may be augmented
    by as much as 15\%.},
	Author = {O. Gascuel},
	Institution = {GERAD, Ecole des HEC, Montreal, Quebec, Canada. gascuel@lirmm.fr},
	Journal = {Mol Biol Evol},
	Keywords = {Algorithms; Evolution; Models, Biological; Phylogeny; Sequence Analysis; Software},
	Month = {Jul},
	Number = {7},
	Owner = {binf007},
	Pages = {685--695},
	Pmid = {9254330},
	Timestamp = {2008.01.21},
	Title = {{BIONJ: an improved version of the NJ algorithm based on a simple model of sequence data.}},
	Volume = {14},
	Year = {1997}}

@article{Gerlach2007,
	Abstract = {We reconstructed a robust phylogenetic tree of the Metazoa, consisting
    of almost 1,500 taxa, by profile neighbor joining (PNJ), an automated
    computational method that inherits the efficiency of the neighbor
    joining algorithm. This tree supports the one proposed in the latest
    review on metazoan phylogeny. Our main goal is not to discuss aspects
    of the phylogeny itself, but rather to point out that PNJ can be
    a valuable tool when the basal branching pattern of a large phylogenetic
    tree must be estimated, whereas traditional methods would be computationally
    impractical.},
	Author = {Daniel Gerlach and Matthias Wolf and Thomas Dandekar and Tobias M{\"u}ller and Andreas Pokorny and Sven Rahmann},
	Institution = {Department of Bioinformatics, Biocenter, University of W{\"u}rzburg, Am Hubland, D-97074 W{\"u}rzburg, Germany.},
	Journal = {In Silico Biol},
	Keywords = {Algorithms; Animals; Computational Biology; Models, Genetic; Phylogeny; RNA, Ribosomal, 18S},
	Number = {2},
	Owner = {binf007},
	Pages = {151--154},
	Pii = {2007070015},
	Pmid = {17688440},
	Timestamp = {2008.01.21},
	Title = {{Deep metazoan phylogeny.}},
	Volume = {7},
	Year = {2007}}

@article{Grajales2007,
	Abstract = {BACKGROUND: Most phylogenetic studies using current methods have focused
    on primary DNA sequence information. However, RNA secondary structures
    are particularly useful in systematics because they include characteristics,
    not found in the primary sequence, that give "morphological" information.
    Despite the number of recent molecular studies on octocorals, there
    is no consensus opinion about a region that carries enough phylogenetic
    resolution to solve intrageneric or close species relationships.
    Moreover, intrageneric morphological information by itself does not
    always produce accurate phylogenies; intra-species comparisons can
    reveal greater differences than intra-generic ones. The search for
    new phylogenetic approaches, such as by RNA secondary structure analysis,
    is therefore a priority in octocoral research. RESULTS: Initially,
    twelve predicted RNA secondary structures were reconstructed to provide
    the basic information for phylogenetic analyses; they accorded with
    the 6 helicoidal ring model, also present in other groups of corals
    and eukaryotes. We obtained three similar topologies for nine species
    of the Caribbean gorgonian genus Eunicea (candelabrum corals) with
    two sister taxa as outgroups (genera Plexaura and Pseudoplexaura)
    on the basis of molecular morphometrics of ITS2 RNA secondary structures
    only, traditional primary sequence analyses and maximum likelihood,
    and a Bayesian analysis of the combined data. The latter approach
    allowed us to include both primary sequence and RNA molecular morphometrics;
    each data partition was allowed to have a different evolution rate.
    In addition, each helix was partitioned as if it had evolved at a
    distinct rate. Plexaura flexuosa was found to group within Eunicea;
    this was best supported by both the molecular morphometrics and combined
    analyses. We suggest Eunicea flexuosa (Lamouroux, 1821) comb. nov.,
    and we present a new species description including Scanning Electron
    Microscopy (SEM) images of morphological characteristics (sclerites).
    Eunicea flexuosa, E. pallida, E. laxispica and E. mammosa formed
    a separate clade in the molecular phylogenies, and were reciprocally
    monophyletic with respect to other Eunicea (Euniceopsis subgenus,
    e.g. E. tourneforti and E. laciniata) in the molecular morphometrics
    tree, with the exception of E. fusca. Moreover, we suggest a new
    diagnostic character for Eunicea, also present in E. flexuosa: middle
    layer sclerites > 1 mm in length. CONCLUSION: ITS2 was a reliable
    sequence for intrageneric studies in gorgonian octocorals because
    of the amount of phylogenetic signal, and was corroborated against
    morphological characters separating Eunicea from Plexaura. The ITS2
    RNA secondary structure approach to phylogeny presented here did
    not rely on alignment methods such as INDELS, but provided clearly
    homologous characters for partition analysis and RNA molecular morphometrics.
    These approaches support the divergence of Eunicea flexuosa comb.
    nov. from the outgroup Plexaura, although it has been considered
    part of this outgroup for nearly two centuries because of morphological
    resemblance.},
	Author = {Alejandro Grajales and Catalina Aguilar and Juan A S{\'a}nchez},
	Doi = {10.1186/1471-2148-7-90},
	Institution = {>},
	Journal = {BMC Evol Biol},
	Keywords = {Animals; Anthozoa; DNA, Ribosomal Spacer; Evolution, Molecular; Genetic Speciation; Nucleic Acid Conformation; Phylogeny; RNA, Ribosomal; Variation (Genetics)},
	Owner = {binf007},
	Pages = {90},
	Pii = {1471-2148-7-90},
	Pmid = {17562014},
	Timestamp = {2008.07.30},
	Title = {Phylogenetic reconstruction using secondary structures of Internal Transcribed Spacer 2 (ITS2, rDNA): finding the molecular and morphological gap in Caribbean gorgonian corals.},
	Url = {http://dx.doi.org/10.1186/1471-2148-7-90},
	Volume = {7},
	Year = {2007},
	Bdsk-Url-1 = {http://dx.doi.org/10.1186/1471-2148-7-90}}

@article{Hochsmann2004,
	Abstract = {In functional, noncoding RNA, structure is often essential to function.
    While the full 3D structure is very difficult to determine, the 2D
    structure of an RNA molecule gives good clues to its 3D structure,
    and for molecules of moderate length, it can be predicted with good
    reliability. Structure comparison is, in analogy to sequence comparison,
    the essential technique to infer related function. We provide a method
    for computing multiple alignments of RNA secondary structures under
    the tree alignment model, which is suitable to cluster RNA molecules
    purely on the structural level, i.e., sequence similarity is not
    required. We give a systematic generalization of the profile alignment
    method from strings to trees and forests. We introduce a tree profile
    representation of RNA secondary structure alignments which allows
    reasonable scoring in structure comparison. Besides the technical
    aspects, an RNA profile is a useful data structure to represent multiple
    structures of RNA sequences. Moreover, we propose a visualization
    of RNA consensus structures that is enriched by the full sequence
    information.},
	Author = {Hochsmann, M. and Hochsmann, M. and Voss, B. and Giegerich, R.},
	Booktitle = {IEEE/ACM Transactions on Computational Biology and Bioinformatics},
	Doi = {10.1109/TCBB.2004.11},
	Editor = {Voss, B.},
	Issn = {1545-5963},
	Journal = {IEEE/ACM Transactions on Computational Biology and Bioinformatics},
	Keywords = {biology computing, macromolecules, molecular biophysics, trees (mathematics), forest alignment, functional noncoding RNA structure, progressive profile approach, pure multiple RNA secondary structure alignments, strings, structure comparison, tree alignment model, tree profile representation, 65, Index Terms- Alignment of trees, RNA secondary structures, noncoding RNAs.},
	Number = {1},
	Owner = {binf007},
	Pages = {53--62},
	Timestamp = {2008.01.23},
	Title = {{Pure multiple RNA secondary structure alignments: a progressive profile approach}},
	Volume = {1},
	Year = {2004},
	Bdsk-Url-1 = {https://doi.org/10.1109/TCBB.2004.11}}

@article{Hudelot2003,
	Abstract = {The PHASE software package allows phylogenetic tree construction with
    a number of evolutionary models designed specifically for use with
    RNA sequences that have conserved secondary structure. Evolution
    in the paired regions of RNAs occurs via compensatory substitutions,
    hence changes on either side of a pair are correlated. Accounting
    for this correlation is important for phylogenetic inference because
    it affects the likelihood calculation. In the present study we use
    the complete set of tRNA and rRNA sequences from 69 complete mammalian
    mitochondrial genomes. The likelihood calculation uses two evolutionary
    models simultaneously for different parts of the sequence: a paired-site
    model for the paired sites and a single-site model for the unpaired
    sites. We use Bayesian phylogenetic methods and a Markov chain Monte
    Carlo algorithm is used to obtain the most probable trees and posterior
    probabilities of clades. The results are well resolved for almost
    all the important branches on the mammalian tree. They support the
    arrangement of mammalian orders within the four supra-ordinal clades
    that have been identified by studies of much larger data sets mainly
    comprising nuclear genes. Groups such as the hedgehogs and the murid
    rodents, which have been problematic in previous studies with mitochondrial
    proteins, appear in their expected position with the other members
    of their order. Our choice of genes and evolutionary model appears
    to be more reliable and less subject to biases caused by variation
    in base composition than previous studies with mitochondrial genomes.},
	Author = {Cendrine Hudelot and Vivek Gowri-Shankar and Howsun Jow and Magnus Rattray and Paul G Higgs},
	Institution = {School of Biological Sciences, University of Manchester, UK.},
	Journal = {Mol Phylogenet Evol},
	Keywords = {Animals; Bayes Theorem; Mammals; Models, Genetic; Phylogeny; RNA},
	Month = {Aug},
	Number = {2},
	Owner = {binf007},
	Pages = {241--252},
	Pii = {S1055790303000617},
	Pmid = {12878461},
	Timestamp = {2008.01.21},
	Title = {{RNA-based phylogenetic methods: application to mammalian mitochondrial RNA sequences.}},
	Volume = {28},
	Year = {2003}}

@article{Jow2002,
	Abstract = {We study the phylogeny of the placental mammals using molecular data
    from all mitochondrial tRNAs and rRNAs of 54 species. We use probabilistic
    substitution models specific to evolution in base paired regions
    of RNA. A number of these models have been implemented in a new phylogenetic
    inference software package for carrying out maximum likelihood and
    Bayesian phylogenetic inferences. We describe our Bayesian phylogenetic
    method which uses a Markov chain Monte Carlo algorithm to provide
    samples from the posterior distribution of tree topologies. Our results
    show support for four primary mammalian clades, in agreement with
    recent studies of much larger data sets mainly comprising nuclear
    DNA. We discuss some issues arising when using Bayesian techniques
    on RNA sequence data.},
	Author = {H. Jow and C. Hudelot and M. Rattray and P. G. Higgs},
	Institution = {Department of Computer Science, University of Manchester, UK.},
	Journal = {Mol Biol Evol},
	Keywords = {Animals; Base Sequence; Bayes Theorem; Databases, Genetic; Evolution, Molecular; Humans; Mammals; Models, Genetic; Phylogeny; RNA; Species Specificity},
	Month = {Sep},
	Number = {9},
	Owner = {binf007},
	Pages = {1591--1601},
	Pmid = {12200486},
	Timestamp = {2008.06.06},
	Title = {Bayesian phylogenetics using an RNA substitution model applied to early mammalian evolution.},
	Volume = {19},
	Year = {2002}}

@incollection{Jukes69,
	Address = {New York, USA},
	Author = {Jukes, T. and Cantor, C.R.},
	Booktitle = {Mammalian Protein Metabolism},
	Editor = {Munro, H},
	Pages = {21-132},
	Publisher = {Academic Press},
	Title = {Evolution of protein molecules},
	Year = {1969}}

@article{Mueller2004,
	Abstract = {BACKGROUND: In phylogenetic analysis we face the problem that several
    subclade topologies are known or easily inferred and well supported
    by bootstrap analysis, but basal branching patterns cannot be unambiguously
    estimated by the usual methods (maximum parsimony (MP), neighbor-joining
    (NJ), or maximum likelihood (ML)), nor are they well supported. We
    represent each subclade by a sequence profile and estimate evolutionary
    distances between profiles to obtain a matrix of distances between
    subclades. RESULTS: Our estimator of profile distances generalizes
    the maximum likelihood estimator of sequence distances. The basal
    branching pattern can be estimated by any distance-based method,
    such as neighbor-joining. Our method (profile neighbor-joining, PNJ)
    then inherits the accuracy and robustness of profiles and the time
    efficiency of neighbor-joining. CONCLUSIONS: Phylogenetic analysis
    of Chlorophyceae with traditional methods (MP, NJ, ML and MrBayes)
    reveals seven well supported subclades, but the methods disagree
    on the basal branching pattern. The tree reconstructed by our method
    is better supported and can be confirmed by known morphological characters.
    Moreover the accuracy is significantly improved as shown by parametric
    bootstrap.},
	Author = {Tobias M{\"u}ller and Sven Rahmann and Thomas Dandekar and Matthias Wolf},
	Doi = {10.1186/1471-2148-4-20},
	Institution = {Department of Bioinformatics, Biocenter, University of W{\"u}rzburg, Am Hubland, D-97074 W{\"u}rzburg, Germany. tobias.mueller@biozentrum.uni-wuerzburg.de},
	Journal = {BMC Evol Biol},
	Keywords = {Algae, Green; Animals; Computational Biology; Evolution, Molecular; Models, Genetic; Phylogeny; RNA, Plant; RNA, Ribosomal; RNA, Ribosomal, 18S},
	Month = {Jun},
	Owner = {binf007},
	Pages = {20},
	Pii = {1471-2148-4-20},
	Pmid = {15222898},
	Timestamp = {2008.01.21},
	Title = {{Accurate and robust phylogeny estimation based on profile distances: a study of the Chlorophyceae (Chlorophyta).}},
	Url = {http://dx.doi.org/10.1186/1471-2148-4-20},
	Volume = {4},
	Year = {2004},
	Bdsk-Url-1 = {http://dx.doi.org/10.1186/1471-2148-4-20}}

@article{Mueller2002,
	Abstract = {Evolution of proteins is generally modeled as a Markov process acting
    on each site of the sequence. Replacement frequencies need to be
    estimated based on sequence alignments. Here we compare three approaches:
    First, the original method by Dayhoff, Schwartz, and Orcutt (1978)
    Atlas Protein Seq. Struc. 5:345-352, secondly, the resolvent method
    (RV) by M{\"u}ller and Vingron (2000) J. Comput. Biol. 7(6):761-776,
    and finally a maximum likelihood approach (ML) developed in this
    paper. We evaluate the methods using a highly divergent and inhomogeneous
    set of sequence alignments as an input to the estimation procedure.
    ML is the method of choice for small sets of input data. Although
    the RV method is computationally much less demanding it performs
    only slightly worse than ML. Therefore, it is perfectly appropriate
    for large-scale applications.},
	Author = {Tobias M{\"u}ller and Rainer Spang and Martin Vingron},
	Institution = {Deutsches Krebsforschungszentrum, Theoretische Bioinformatik, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. t.mueller@dkfz.de},
	Journal = {Mol Biol Evol},
	Keywords = {Algorithms; Amino Acid Sequence; Amino Acid Substitution; Computer Simulation; Evolution, Molecular; Likelihood Functions; Markov Chains; Models, Genetic; Proteins; Sequence Alignment},
	Month = {Jan},
	Number = {1},
	Owner = {binf007},
	Pages = {8--13},
	Pmid = {11752185},
	Timestamp = {2008.01.25},
	Title = {{Estimating amino acid substitution models: a comparison of Dayhoff's estimator, the resolvent approach and a maximum likelihood method.}},
	Volume = {19},
	Year = {2002}}

@article{Mueller2000,
	Abstract = {The estimation of amino acid replacement frequencies during molecular
    evolution is crucial for many applications in sequence analysis.
    Score matrices for database search programs or phylogenetic analysis
    rely on such models of protein evolution. Pioneering work was done
    by Dayhoff et al. (1978) who formulated a Markov model of evolution
    and derived the famous PAM score matrices. Her estimation procedure
    for amino acid exchange frequencies is restricted to pairs of proteins
    that have a constant and small degree of divergence. Here we present
    an improved estimator, called the resolvent method, that is not subject
    to these limitations. This extension of Dayhoff's approach enables
    us to estimate an amino acid substitution model from alignments of
    varying degree of divergence. Extensive simulations show the capability
    of the new estimator to recover accurately the exchange frequencies
    among amino acids. Based on the SYSTERS database of aligned protein
    families (Krause and Vingron, 1998) we recompute a series of score
    matrices.},
	Author = {T. M{\"u}ller and M. Vingron},
	Doi = {10.1089/10665270050514918},
	Institution = {Deutsches Krebsforschungszentrum, Theoretische Bioinformatik, 69120 Heidelberg, Germany. t.mueller/m.vingron},
	Journal = {J Comput Biol},
	Keywords = {Amino Acid Substitution; Computer Simulation; Evolution, Molecular; Likelihood Functions; Markov Chains; Models, Biological; Proteins; Stochastic Processes; Time Factors},
	Number = {6},
	Owner = {binf007},
	Pages = {761--776},
	Pmid = {11382360},
	Timestamp = {2008.01.25},
	Title = {{Modeling amino acid replacement.}},
	Url = {http://dx.doi.org/10.1089/10665270050514918},
	Volume = {7},
	Year = {2000},
	Bdsk-Url-1 = {http://dx.doi.org/10.1089/10665270050514918}}

@incollection{Buch2006,
	Abstract = {The goal of phylogenetics is to reconstruct ancestral relationships
    between different taxa, e.g., different species in the tree of life,
    by means of certain characters, such as genomic sequences. We consider
    the prominent problem of reconstructing the basal phylogenetic tree
    topology when several subclades have already been identified or are
    well known by other means, such as morphological characteristics.
    Whereas most available tools attempt to estimate a fully resolved
    tree from scratch, the profile neighbor-joining (PNJ) method focuses
    directly on the mentioned problem and has proven a robust and efficient
    method for large-scale data sets, especially when used in an iterative
    way. We describe an implementation of this idea, the ProfDist software
    package, which is freely available, and apply the method to estimate
    the phylogeny of the eukaryotes. Overall, the PNJ approach provides
    a novel effective way to mine large sequence datasets for relevant
    phylogenetic information.},
	Address = {Hershey, PA, USA},
	Author = {Sven Rahmann and Tobias Muller and Thomas Dandekar and Matthias Wolf},
	Booktitle = {Advanced Data Mining Technologies in Bioinformatics},
	Editor = {Hui-Huang Hsu},
	Pages = {104-117},
	Publisher = {Idea Group, Inc.},
	Title = {{Efficient and robust analysis of large phylogenetic datasets}},
	Year = {2006}}

@article{Saitou1987,
	Abstract = {A new method called the neighbor-joining method is proposed for reconstructing
    phylogenetic trees from evolutionary distance data. The principle
    of this method is to find pairs of operational taxonomic units (OTUs
    [= neighbors]) that minimize the total branch length at each stage
    of clustering of OTUs starting with a starlike tree. The branch lengths
    as well as the topology of a parsimonious tree can quickly be obtained
    by using this method. Using computer simulation, we studied the efficiency
    of this method in obtaining the correct unrooted tree in comparison
    with that of five other tree-making methods: the unweighted pair
    group method of analysis, Farris's method, Sattath and Tversky's
    method, Li's method, and Tateno et al.'s modified Farris method.
    The new, neighbor-joining method and Sattath and Tversky's method
    are shown to be generally better than the other methods.},
	Author = {N. Saitou and M. Nei},
	Institution = {Center for Demographic and Population Genetics, University of Texas Health Science Center, Houston 77225.},
	Journal = {Mol Biol Evol},
	Keywords = {Animals; Biometry; Evolution; Models, Genetic; Phylogeny; Ranidae},
	Month = {Jul},
	Number = {4},
	Owner = {binf007},
	Pages = {406--425},
	Pmid = {3447015},
	Timestamp = {2008.01.21},
	Title = {{The neighbor-joining method: a new method for reconstructing phylogenetic trees.}},
	Volume = {4},
	Year = {1987}}

@article{Schultz2005,
	Abstract = {The ongoing characterization of novel species creates the need for
    a molecular marker which can be used for species- and, simultaneously,
    for mega-systematics. Recently, the use of the internal transcribed
    spacer 2 (ITS2) sequence was suggested, as it shows a high divergence
    in sequence with an assumed conservation in structure. This hypothesis
    was mainly based on small-scale analyses, comparing a limited number
    of sequences. Here, we report a large-scale analysis of more than
    54,000 currently known ITS2 sequences with the goal to evaluate the
    hypothesis of a conserved structural core and to assess its use for
    automated large-scale phylogenetics. Structure prediction revealed
    that the previously described core structure can be found for more
    than 5000 sequences in a wide variety of taxa within the eukaryotes,
    indicating that the core secondary structure is indeed conserved.
    This conserved structure allowed an automated alignment of extremely
    divergent sequences as exemplified for the ITS2 sequences of a ctenophorean
    eumetazoon and a volvocalean green alga. All classified sequences,
    together with their structures can be accessed at http://www.biozentrum.uni-wuerzburg.de/bioinformatik/projects/ITS2.html.
    Furthermore, we found that, although sample sequences are known for
    most major taxa, there exists a profound divergence in coverage,
    which might become a hindrance for general usage. In summary, our
    analysis strengthens the potential of ITS2 as a general phylogenetic
    marker and provides a data source for further ITS2-based analyses.},
	Author = {J{\"o}rg Schultz and Stefanie Maisel and Daniel Gerlach and Tobias M{\"u}ller and Matthias Wolf},
	Doi = {10.1261/rna.7204505},
	Institution = {entrum.uni-wuerzburg.de},
	Journal = {RNA},
	Keywords = {Algae; Animals; Base Sequence; Conserved Sequence; DNA, Ribosomal Spacer; Fungi; Genetic Markers; Invertebrates; Molecular Sequence Data; Nucleic Acid Conformation; Phylogeny; Plants; Sequence Alignment; Transcription, Genetic},
	Month = {Apr},
	Number = {4},
	Owner = {binf007},
	Pages = {361--364},
	Pii = {11/4/361},
	Pmid = {15769870},
	Timestamp = {2008.01.21},
	Title = {{A common core of secondary structure of the internal transcribed spacer 2 (ITS2) throughout the Eukaryota.}},
	Url = {http://dx.doi.org/10.1261/rna.7204505},
	Volume = {11},
	Year = {2005},
	Bdsk-Url-1 = {http://dx.doi.org/10.1261/rna.7204505}}

@article{Schultz2006,
	Abstract = {The internal transcribed spacer 2 (ITS2) is a phylogenetic marker
    which has been of broad use in generic and infrageneric level classifications,
    as its sequence evolves comparably fast. Only recently, it became
    clear, that the ITS2 might be useful even for higher level systematic
    analyses. As the secondary structure is highly conserved within all
    eukaryotes it serves as a valuable template for the construction
    of highly reliable sequence-structure alignments, which build a fundament
    for subsequent analyses. Thus, any phylogenetic study using ITS2
    has to consider both sequence and structure. We have integrated a
    homology based RNA structure prediction algorithm into a web server,
    which allows the detection and secondary structure prediction for
    ITS2 in any given sequence. Furthermore, the resource contains more
    than 25,000 pre-calculated secondary structures for the currently
    known ITS2 sequences. These can be taxonomically searched and browsed.
    Thus, our resource could become a starting point for ITS2-based phylogenetic
    analyses and is therefore complementary to databases of other phylogenetic
    markers, which focus on higher level analyses. The current version
    of the ITS2 database can be accessed via http://its2.bioapps.biozentrum.uni-wuerzburg.de.},
	Author = {J{\"o}rg Schultz and Tobias M{\"u}ller and Marco Achtziger and Philipp N Seibel and Thomas Dandekar and Matthias Wolf},
	Doi = {10.1093/nar/gkl129},
	Institution = {Department of Bioinformatics, Biocenter, University of W{\"u}rzburg Am Hubland, 97074 W{\"u}rzburg, Germany. Joerg.Schultz@biozentrum.uni-wuerzburg.de},
	Journal = {Nucleic Acids Res},
	Keywords = {DNA, Ribosomal Spacer; Databases, Nucleic Acid; Internet; Nucleic Acid Conformation; Phylogeny; Sequence Analysis, RNA; Software; User-Computer Interface},
	Month = {Jul},
	Number = {Web Server issue},
	Owner = {binf007},
	Pages = {W704--W707},
	Pii = {34/suppl_2/W704},
	Pmid = {16845103},
	Timestamp = {2008.01.21},
	Title = {{The internal transcribed spacer 2 database--a web server for (not only) low level phylogenetic analyses.}},
	Url = {http://dx.doi.org/10.1093/nar/gkl129},
	Volume = {34},
	Year = {2006},
	Bdsk-Url-1 = {http://dx.doi.org/10.1093/nar/gkl129}}

@article{Schoeniger1994,
	Abstract = {Currently used stochastic models of DNA sequence evolution assume
    independent and identically distributed nucleotide sites. They are
    too simple to account for dependence structures obviously present
    in molecular data. Up to now more realistic stochastic models for
    nucleotide substitutions have been considered intractable. In this
    paper a procedure that accounts for non-overlapping correlations
    among pairs of sites of a DNA sequence is developed. We show that
    currently used models that ignore correlated sites underestimate
    distances inferred from observed sequence dissimilarities. For the
    analyzed mitochondrial sequence data this underestimation is not
    drastic in contrast to paired regions (stems) of bacterial 23S rRNA
    sequences.},
	Author = {M. Sch{\"o}niger and A. von Haeseler},
	Doi = {10.1006/mpev.1994.1026},
	Institution = {Technical University Munich, Germany.},
	Journal = {Mol Phylogenet Evol},
	Keywords = {Animals; DNA; DNA, Mitochondrial; Evolution; Mammals; Markov Chains; Mutation; RNA, Bacterial; RNA, Ribosomal, 23S; Species Specificity; Stochastic Processes},
	Month = {Sep},
	Number = {3},
	Owner = {binf007},
	Pages = {240--247},
	Pii = {S1055-7903(84)71026-8},
	Pmid = {7529616},
	Timestamp = {2008.01.25},
	Title = {{A stochastic model for the evolution of autocorrelated DNA sequences.}},
	Url = {http://dx.doi.org/10.1006/mpev.1994.1026},
	Volume = {3},
	Year = {1994},
	Bdsk-Url-1 = {http://dx.doi.org/10.1006/mpev.1994.1026}}

@article{Seibel2006,
	Abstract = {BACKGROUND: In sequence analysis the multiple alignment builds the
    fundament of all proceeding analyses. Errors in an alignment could
    strongly influence all succeeding analyses and therefore could lead
    to wrong predictions. Hand-crafted and hand-improved alignments are
    necessary and meanwhile good common practice. For RNA sequences often
    the primary sequence as well as a secondary structure consensus is
    well known, e.g., the cloverleaf structure of the t-RNA. Recently,
    some alignment editors are proposed that are able to include and
    model both kinds of information. However, with the advent of a large
    amount of reliable RNA sequences together with their solved secondary
    structures (available from e.g. the ITS2 Database), we are faced
    with the problem to handle sequences and their associated secondary
    structures synchronously. RESULTS: 4SALE fills this gap. The application
    allows a fast sequence and synchronous secondary structure alignment
    for large data sets and for the first time synchronous manual editing
    of aligned sequences and their secondary structures. This study describes
    an algorithm for the synchronous alignment of sequences and their
    associated secondary structures as well as the main features of 4SALE
    used for further analyses and editing. 4SALE builds an optimal and
    unique starting point for every RNA sequence and structure analysis.
    CONCLUSION: 4SALE, which provides an user-friendly and intuitive
    interface, is a comprehensive toolbox for RNA analysis based on sequence
    and secondary structure information. The program connects sequence
    and structure databases like the ITS2 Database to phylogeny programs
    as for example the CBCAnalyzer. 4SALE is written in JAVA and therefore
    platform independent. The software is freely available and distributed
    from the website at http://4sale.bioapps.biozentrum.uni-wuerzburg.de.},
	Author = {Philipp N Seibel and Tobias M{\"u}ller and Thomas Dandekar and J{\"o}rg Schultz and Matthias Wolf},
	Doi = {10.1186/1471-2105-7-498},
	Institution = {>},
	Journal = {BMC Bioinformatics},
	Keywords = {Algorithms; Base Pairing; Computational Biology; Databases, Genetic; Nucleic Acid Conformation; RNA; Sequence Alignment; Sequence Analysis, RNA; Software Validation; Time Factors; User-Computer Interface},
	Owner = {binf007},
	Pages = {498},
	Pii = {1471-2105-7-498},
	Pmid = {17101042},
	Timestamp = {2008.01.21},
	Title = {{4SALE--a tool for synchronous RNA sequence and secondary structure alignment and editing.}},
	Url = {http://dx.doi.org/10.1186/1471-2105-7-498},
	Volume = {7},
	Year = {2006},
	Bdsk-Url-1 = {http://dx.doi.org/10.1186/1471-2105-7-498}}

@article{Selig2008,
	Abstract = {An increasing number of phylogenetic analyses are based on the internal
    transcribed spacer 2 (ITS2). They mainly use the fast evolving sequence
    for low-level analyses. When considering the highly conserved structure,
    the same marker could also be used for higher level phylogenies.
    Furthermore, structural features of the ITS2 allow distinguishing
    different species from each other. Despite its importance, the correct
    structure is only rarely found by standard RNA folding algorithms.
    To overcome this hindrance for a wider application of the ITS2, we
    have developed a homology modelling approach to predict the structure
    of RNA and present the results of modelling the ITS2 in the ITS2
    Database. Here, we describe the database and the underlying algorithms
    which allowed us to predict the structure for 86 784 sequences, which
    is more than 55\% of all GenBank entries concerning the ITS2. These
    are not equally distributed over all genera. There is a substantial
    amount of genera where the structure of nearly all sequences is predicted
    whereas for others no structure at all was found despite high sequence
    coverage. These genera might have evolved an ITS2 structure diverging
    from the standard one. The current version of the ITS2 Database can
    be accessed via http://its2.bioapps.biozentrum.uni-wuerzburg.de.},
	Author = {Christian Selig and Matthias Wolf and Tobias M{\"u}ller and Thomas Dandekar and J{\"o}rg Schultz},
	Doi = {10.1093/nar/gkm827},
	Institution = {Department of Bioinformatics, Biocenter, University of W{\"u}rzburg, Am Hubland 97074 W{\"u}rzburg, Germany.},
	Journal = {Nucleic Acids Res},
	Month = {Jan},
	Number = {Database issue},
	Owner = {binf007},
	Pages = {D377--D380},
	Pii = {gkm827},
	Pmid = {17933769},
	Timestamp = {2008.01.21},
	Title = {{The ITS2 Database II: homology modelling RNA structure for molecular systematics.}},
	Url = {http://dx.doi.org/10.1093/nar/gkm827},
	Volume = {36},
	Year = {2008},
	Bdsk-Url-1 = {http://dx.doi.org/10.1093/nar/gkm827}}

@article{Siebert2005,
	Abstract = {MOTIVATION: Due to the importance of considering secondary structures
    in aligning functional RNAs, several pairwise sequence-structure
    alignment methods have been developed. They use extended alignment
    scores that evaluate secondary structure information in addition
    to sequence information. However, two problems for the multiple alignment
    step remain. First, how to combine pairwise sequence-structure alignments
    into a multiple alignment and second, how to generate secondary structure
    information for sequences whose explicit structural information is
    missing. RESULTS: We describe a novel approach for multiple alignment
    of RNAs (MARNA) taking into consideration both the primary and the
    secondary structures. It is based on pairwise sequence-structure
    comparisons of RNAs. From these sequence-structure alignments, libraries
    of weighted alignment edges are generated. The weights reflect the
    sequential and structural conservation. For sequences whose secondary
    structures are missing, the libraries are generated by sampling low
    energy conformations. The libraries are then processed by the T-Coffee
    system, which is a consistency based multiple alignment method. Furthermore,
    we are able to extract a consensus-sequence and -structure from a
    multiple alignment. We have successfully tested MARNA on several
    datasets taken from the Rfam database.},
	Author = {Sven Siebert and Rolf Backofen},
	Doi = {10.1093/bioinformatics/bti550},
	Institution = {Department of Bioinformatics, Institute of Computer Science, Friedrich-Schiller-University Jena, Ernst-Abbe Platz 2, 07743 Jena, Germany.},
	Journal = {Bioinformatics},
	Keywords = {Algorithms; Computer Simulation; Consensus Sequence; RNA; Sensitivity and Specificity; Sequence Alignment; Sequence Analysis, RNA; Sequence Homology, Nucleic Acid; Software; Structure-Activity Relationship},
	Month = {Aug},
	Number = {16},
	Owner = {binf007},
	Pages = {3352--3359},
	Pii = {bti550},
	Pmid = {15972285},
	Timestamp = {2008.01.21},
	Title = {{MARNA: multiple alignment and consensus structure prediction of RNAs based on sequence structure comparisons.}},
	Url = {http://dx.doi.org/10.1093/bioinformatics/bti550},
	Volume = {21},
	Year = {2005},
	Bdsk-Url-1 = {http://dx.doi.org/10.1093/bioinformatics/bti550}}

@article{Smith2004,
	Abstract = {Empirical models of substitution are often used in protein sequence
    analysis because the large alphabet of amino acids requires that
    many parameters be estimated in all but the simplest parametric models.
    When information about structure is used in the analysis of substitutions
    in structured RNA, a similar situation occurs. The number of parameters
    necessary to adequately describe the substitution process increases
    in order to model the substitution of paired bases. We have developed
    a method to obtain substitution rate matrices empirically from RNA
    alignments that include structural information in the form of base
    pairs. Our data consisted of alignments from the European Ribosomal
    RNA Database of Bacterial and Eukaryotic Small Subunit and Large
    Subunit Ribosomal RNA ( Wuyts et al. 2001. Nucleic Acids Res. 29:175-177;
    Wuyts et al. 2002. Nucleic Acids Res. 30:183-185). Using secondary
    structural information, we converted each sequence in the alignments
    into a sequence over a 20-symbol code: one symbol for each of the
    four individual bases, and one symbol for each of the 16 ordered
    pairs. Substitutions in the coded sequences are defined in the natural
    way, as observed changes between two sequences at any particular
    site. For given ranges (windows) of sequence divergence, we obtained
    substitution frequency matrices for the coded sequences. Using a
    technique originally developed for modeling amino acid substitutions
    ( Veerassamy, Smith, and Tillier. 2003. J. Comput. Biol. 10:997-1010),
    we were able to estimate the actual evolutionary distance for each
    window. The actual evolutionary distances were used to derive instantaneous
    rate matrices, and from these we selected a universal rate matrix.
    The universal rate matrices were incorporated into the Phylip Software
    package ( Felsenstein 2002. http://evolution.genetics.washington.edu/phylip.html),
    and we analyzed the ribosomal RNA alignments using both distance
    and maximum likelihood methods. The empirical substitution models
    performed well on simulated data, and produced reasonable evolutionary
    trees for 16S ribosomal RNA sequences from sequenced Bacterial genomes.
    Empirical models have the advantage of being easily implemented,
    and the fact that the code consists of 20 symbols makes the models
    easily incorporated into existing programs for protein sequence analysis.
    In addition, the models are useful for simulating the evolution of
    RNA sequence and structure simultaneously.},
	Author = {Andrew D Smith and Thomas W H Lui and Elisabeth R M Tillier},
	Doi = {10.1093/molbev/msh029},
	Institution = {Department of Medical Biophysics, University of Toronto, and Ontario Cancer Institute, University Health Network, Toronto, Ontario, Canada.},
	Journal = {Mol Biol Evol},
	Keywords = {Amino Acid Substitution; Animals; Computer Simulation; Databases, Nucleic Acid; Evolution, Molecular; Likelihood Functions; Models, Genetic; Phylogeny; RNA, Ribosomal; Sequence Alignment},
	Month = {Mar},
	Number = {3},
	Owner = {binf007},
	Pages = {419--427},
	Pii = {msh029},
	Pmid = {14660689},
	Timestamp = {2008.01.21},
	Title = {{Empirical models for substitution in ribosomal RNA.}},
	Url = {http://dx.doi.org/10.1093/molbev/msh029},
	Volume = {21},
	Year = {2004},
	Bdsk-Url-1 = {http://dx.doi.org/10.1093/molbev/msh029}}

@misc{QT,
	Author = {Trolltech},
	Owner = {binf007},
	Timestamp = {2008.07.19},
	Title = {http://trolltech.com/products/qt/},
	Url = {http://trolltech.com/products/qt/},
	Year = {2008},
	Bdsk-Url-1 = {http://trolltech.com/products/qt/}}

@article{Vanormelingen2007,
	Author = {P Vanormelingen and E Hegewald and A Braband and M Kitschke and T Friedl and K Sabbe and W Vyverman},
	Journal = {Journal of Phyclology},
	Month = {APR},
	Number = {2},
	Pages = {378-396},
	Title = {{The systematics of a small spineless Desmodesmus species, D-costato-granulatus (Sphaeropleales, Chlorophyceae), based on ITS2 rDNA sequence analyses and cell wall morphology}},
	Volume = {43},
	Year = {2007}}

@article{Wheeler2000,
	Abstract = {In addition to maintaining the GenBank(R) nucleic acid sequence database,
    the National Center for Biotechnology Information (NCBI) provides
    data analysis and retrieval and resources that operate on the data
    in GenBank and a variety of other biological data made available
    through NCBI's Web site. NCBI data retrieval resources include Entrez,
    PubMed, LocusLink and the Taxonomy Browser. Data analysis resources
    include BLAST, Electronic PCR, OrfFinder, RefSeq, UniGene, Database
    of Single Nucleotide Polymorphisms (dbSNP), Human Genome Sequencing
    pages, GeneMap'99, Davis Human-Mouse Homology Map, Cancer Chromosome
    Aberration Project (CCAP) pages, Entrez Genomes, Clusters of Orthologous
    Groups (COGs) database, Retroviral Genotyping Tools, Cancer Genome
    Anatomy Project (CGAP) pages, SAGEmap, Online Mendelian Inheritance
    in Man (OMIM) and the Molecular Modeling Database (MMDB). Augmenting
    many of the Web applications are custom implementations of the BLAST
    program optimized to search specialized data sets. All of the resources
    can be accessed through the NCBI home page at: http://www.ncbi.nlm.nih.
    gov},
	Author = {D. L. Wheeler and C. Chappey and A. E. Lash and D. D. Leipe and T. L. Madden and G. D. Schuler and T. A. Tatusova and B. A. Rapp},
	Institution = {National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Building 38A, 8600 Rockville Pike, Bethesda, MD 20894, USA.},
	Journal = {Nucleic Acids Res},
	Keywords = {Animals; Biology; Databases, Factual; Gene Expression; Genome, Human; Humans; Information Storage and Retrieval; Mice; Models, Molecular; National Library of Medicine (U.S.); Neoplasms; Phenotype; United States},
	Month = {Jan},
	Number = {1},
	Owner = {binf007},
	Pages = {10--14},
	Pii = {gkd055},
	Pmid = {10592169},
	Timestamp = {2008.01.21},
	Title = {{Database resources of the National Center for Biotechnology Information.}},
	Volume = {28},
	Year = {2000}}

@article{Wolf2005,
	Abstract = {Structural genomics meets phylogenetics and vice versa: Knowing rRNA
    secondary structures is a prerequisite for constructing rRNA alignments
    for inferring phylogenies, and inferring phylogenies is a precondition
    to understand the evolution of such rRNA secondary structures. Here,
    both scientific worlds go together. The rRNA internal transcribed
    spacer 2 (ITS2) region is a widely used phylogenetic marker. Because
    of its high variability at the sequence level, correct alignments
    have to take into account structural information. In this study,
    we examine the extent of the conservation in structure. We present
    (1) the homology modeled secondary structure of more than 20,000
    ITS2 covering about 14,000 species; (2) a computational approach
    for homology modeling of rRNA structures, which additionally can
    be applied to other RNA families; and (3) a database providing about
    25,000 ITS2 sequences with their associated secondary structures,
    a refined ITS2 specific general time reversible (GTR) substitution
    model, and a scoring matrix, available at http://its2.bioapps.biozentrum.uni-wuerzburg.de.},
	Author = {Matthias Wolf and Marco Achtziger and J{\"o}rg Schultz and Thomas Dandekar and Tobias M{\"u}ller},
	Doi = {10.1261/rna.2144205},
	Institution = {Department of Bioinformatics, University of W{\"u}rzburg, Biocenter, Am Hubland, Germany. matthias.wolf@biozentrum.uni-wuerzburg.de},
	Journal = {RNA},
	Keywords = {Algae; Animals; Base Sequence; DNA, Ribosomal Spacer; Evolution, Molecular; Fungi; Models, Molecular; Molecular Sequence Data; Nucleic Acid Conformation; RNA, Ribosomal; Sequence Alignment},
	Month = {Nov},
	Number = {11},
	Owner = {binf007},
	Pages = {1616--1623},
	Pii = {11/11/1616},
	Pmid = {16244129},
	Timestamp = {2008.01.21},
	Title = {{Homology modeling revealed more than 20,000 rRNA internal transcribed spacer 2 (ITS2) secondary structures.}},
	Url = {http://dx.doi.org/10.1261/rna.2144205},
	Volume = {11},
	Year = {2005},
	Bdsk-Url-1 = {http://dx.doi.org/10.1261/rna.2144205}}
