document.bib

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@ARTICLE{Boffelli03,
  author = {Markus Bauer and Gunnar W Klau and Knut Reinert},
  title = {{Accurate multiple sequence-structure alignment of RNA sequences
    using combinatorial optimization.}},
  journal = {BMC Bioinformatics},
  year = {2007},
  volume = {8},
  pages = {271},
  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.},
  doi = {10.1186/1471-2105-8-271},
  institution = {Department of Mathematics and Computer Science, Free University Berlin,
    Berlin, Germany. mbauer@inf.fu-berlin.de},
  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},
  pii = {1471-2105-8-271},
  pmid = {17662141},
  timestamp = {2008.01.21},
  url = {http://dx.doi.org/10.1186/1471-2105-8-271}
}

@ARTICLE{Bag01,
  author = {Joachim Friedrich and Thomas Dandekar and Matthias Wolf and Tobias
    Müller},
  title = {{ProfDist: a tool for the construction of large phylogenetic trees
    based on profile distances.}},
  journal = {Bionformatics},
  year = {2005},
  volume = {21},
  pages = {2108--2109},
  number = {9},
  month = {May},
  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},
  doi = {10.1093/bioinformatics/bti289},
  institution = {Department of Bioinformatics, Biocenter, University of Würzburg,
    Germany.},
  keywords = {Algorithms; Chromosome Mapping; DNA Mutational Analysis; Gene Expression
    Profiling; Linkage Disequilibrium; Phylogeny; Sequence Alignment;
    Sequence Analysis, DNA; Software; User-Computer Interface},
  owner = {binf007},
  pii = {bti289},
  pmid = {15677706},
  timestamp = {2008.01.21},
  url = {http://dx.doi.org/10.1093/bioinformatics/bti289}
}

@ARTICLE{Gascuel1997,
  author = {O. Gascuel},
  title = {{BIONJ: an improved version of the NJ algorithm based on a simple
    model of sequence data.}},
  journal = {Mol Biol Evol},
  year = {1997},
  volume = {14},
  pages = {685--695},
  number = {7},
  month = {Jul},
  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\%.},
  institution = {GERAD, Ecole des HEC, Montreal, Quebec, Canada. gascuel@lirmm.fr},
  keywords = {Algorithms; Evolution; Models, Biological; Phylogeny; Sequence Analysis;
    Software},
  owner = {binf007},
  pmid = {9254330},
  timestamp = {2008.01.21}
}

@ARTICLE{Gerlach2007,
  author = {Daniel Gerlach and Matthias Wolf and Thomas Dandekar and Tobias Müller
    and Andreas Pokorny and Sven Rahmann},
  title = {{Deep metazoan phylogeny.}},
  journal = {In Silico Biol},
  year = {2007},
  volume = {7},
  pages = {151--154},
  number = {2},
  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.},
  institution = {Department of Bioinformatics, Biocenter, University of Würzburg,
    Am Hubland, D-97074 Würzburg, Germany.},
  keywords = {Algorithms; Animals; Computational Biology; Models, Genetic; Phylogeny;
    RNA, Ribosomal, 18S},
  owner = {binf007},
  pii = {2007070015},
  pmid = {17688440},
  timestamp = {2008.01.21}
}

@ARTICLE{Grajales2007,
  author = {Alejandro Grajales and Catalina Aguilar and Juan A Sánchez},
  title = {Phylogenetic reconstruction using secondary structures of Internal
    Transcribed Spacer 2 (ITS2, rDNA): finding the molecular and morphological
    gap in Caribbean gorgonian corals.},
  journal = {BMC Evol Biol},
  year = {2007},
  volume = {7},
  pages = {90},
  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.},
  doi = {10.1186/1471-2148-7-90},
  institution = {>},
  keywords = {Animals; Anthozoa; DNA, Ribosomal Spacer; Evolution, Molecular; Genetic
    Speciation; Nucleic Acid Conformation; Phylogeny; RNA, Ribosomal;
    Variation (Genetics)},
  owner = {binf007},
  pii = {1471-2148-7-90},
  pmid = {17562014},
  timestamp = {2008.07.30},
  url = {http://dx.doi.org/10.1186/1471-2148-7-90}
}

@ARTICLE{Hochsmann2004,
  author = {Hochsmann, M. and Hochsmann, M. and Voss, B. and Giegerich, R.},
  title = {{Pure multiple RNA secondary structure alignments: a progressive
    profile approach}},
  journal = {IEEE/ACM Transactions on Computational Biology and Bioinformatics},
  year = {2004},
  volume = {1},
  pages = {53--62},
  number = {1},
  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.},
  booktitle = {IEEE/ACM Transactions on Computational Biology and Bioinformatics},
  doi = {10.1109/TCBB.2004.11},
  editor = {Voss, B.},
  issn = {1545-5963},
  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.},
  owner = {binf007},
  timestamp = {2008.01.23}
}

@ARTICLE{Hudelot2003,
  author = {Cendrine Hudelot and Vivek Gowri-Shankar and Howsun Jow and Magnus
    Rattray and Paul G Higgs},
  title = {{RNA-based phylogenetic methods: application to mammalian mitochondrial
    RNA sequences.}},
  journal = {Mol Phylogenet Evol},
  year = {2003},
  volume = {28},
  pages = {241--252},
  number = {2},
  month = {Aug},
  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.},
  institution = {School of Biological Sciences, University of Manchester, UK.},
  keywords = {Animals; Bayes Theorem; Mammals; Models, Genetic; Phylogeny; RNA},
  owner = {binf007},
  pii = {S1055790303000617},
  pmid = {12878461},
  timestamp = {2008.01.21}
}

@ARTICLE{Jow2002,
  author = {H. Jow and C. Hudelot and M. Rattray and P. G. Higgs},
  title = {Bayesian phylogenetics using an RNA substitution model applied to
    early mammalian evolution.},
  journal = {Mol Biol Evol},
  year = {2002},
  volume = {19},
  pages = {1591--1601},
  number = {9},
  month = {Sep},
  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.},
  institution = {Department of Computer Science, University of Manchester, UK.},
  keywords = {Animals; Base Sequence; Bayes Theorem; Databases, Genetic; Evolution,
    Molecular; Humans; Mammals; Models, Genetic; Phylogeny; RNA; Species
    Specificity},
  owner = {binf007},
  pmid = {12200486},
  timestamp = {2008.06.06}
}

@INCOLLECTION{Jukes69,
  author = {Jukes, T. and Cantor, C.R.},
  title = {Evolution of protein molecules},
  booktitle = {Mammalian Protein Metabolism},
  publisher = {Academic Press},
  year = {1969},
  editor = {Munro, H},
  pages = {21-132},
  address = {New York, USA}
}

@ARTICLE{Mueller2004,
  author = {Tobias Müller and Sven Rahmann and Thomas Dandekar and Matthias Wolf},
  title = {{Accurate and robust phylogeny estimation based on profile distances:
    a study of the Chlorophyceae (Chlorophyta).}},
  journal = {BMC Evol Biol},
  year = {2004},
  volume = {4},
  pages = {20},
  month = {Jun},
  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.},
  doi = {10.1186/1471-2148-4-20},
  institution = {Department of Bioinformatics, Biocenter, University of Würzburg,
    Am Hubland, D-97074 Würzburg, Germany. tobias.mueller@biozentrum.uni-wuerzburg.de},
  keywords = {Algae, Green; Animals; Computational Biology; Evolution, Molecular;
    Models, Genetic; Phylogeny; RNA, Plant; RNA, Ribosomal; RNA, Ribosomal,
    18S},
  owner = {binf007},
  pii = {1471-2148-4-20},
  pmid = {15222898},
  timestamp = {2008.01.21},
  url = {http://dx.doi.org/10.1186/1471-2148-4-20}
}

@ARTICLE{Mueller2002,
  author = {Tobias Müller and Rainer Spang and Martin Vingron},
  title = {{Estimating amino acid substitution models: a comparison of Dayhoff's
    estimator, the resolvent approach and a maximum likelihood method.}},
  journal = {Mol Biol Evol},
  year = {2002},
  volume = {19},
  pages = {8--13},
  number = {1},
  month = {Jan},
  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 Müller 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.},
  institution = {Deutsches Krebsforschungszentrum, Theoretische Bioinformatik, Im
    Neuenheimer Feld 280, 69120 Heidelberg, Germany. t.mueller@dkfz.de},
  keywords = {Algorithms; Amino Acid Sequence; Amino Acid Substitution; Computer
    Simulation; Evolution, Molecular; Likelihood Functions; Markov Chains;
    Models, Genetic; Proteins; Sequence Alignment},
  owner = {binf007},
  pmid = {11752185},
  timestamp = {2008.01.25}
}

@ARTICLE{Mueller2000,
  author = {T. Müller and M. Vingron},
  title = {{Modeling amino acid replacement.}},
  journal = {J Comput Biol},
  year = {2000},
  volume = {7},
  pages = {761--776},
  number = {6},
  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.},
  doi = {10.1089/10665270050514918},
  institution = {Deutsches Krebsforschungszentrum, Theoretische Bioinformatik, 69120
    Heidelberg, Germany. t.mueller/m.vingron},
  keywords = {Amino Acid Substitution; Computer Simulation; Evolution, Molecular;
    Likelihood Functions; Markov Chains; Models, Biological; Proteins;
    Stochastic Processes; Time Factors},
  owner = {binf007},
  pmid = {11382360},
  timestamp = {2008.01.25},
  url = {http://dx.doi.org/10.1089/10665270050514918}
}

@INCOLLECTION{Buch2006,
  author = {Sven Rahmann and Tobias Muller and Thomas Dandekar and Matthias Wolf},
  title = {{Efficient and robust analysis of large phylogenetic datasets}},
  booktitle = {Advanced Data Mining Technologies in Bioinformatics},
  publisher = {Idea Group, Inc.},
  year = {2006},
  editor = {Hui-Huang Hsu},
  pages = {104-117},
  address = {Hershey, PA, USA},
  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.}
}

@ARTICLE{Saitou1987,
  author = {N. Saitou and M. Nei},
  title = {{The neighbor-joining method: a new method for reconstructing phylogenetic
    trees.}},
  journal = {Mol Biol Evol},
  year = {1987},
  volume = {4},
  pages = {406--425},
  number = {4},
  month = {Jul},
  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.},
  institution = {Center for Demographic and Population Genetics, University of Texas
    Health Science Center, Houston 77225.},
  keywords = {Animals; Biometry; Evolution; Models, Genetic; Phylogeny; Ranidae},
  owner = {binf007},
  pmid = {3447015},
  timestamp = {2008.01.21}
}

@ARTICLE{Schultz2005,
  author = {Jörg Schultz and Stefanie Maisel and Daniel Gerlach and Tobias Müller
    and Matthias Wolf},
  title = {{A common core of secondary structure of the internal transcribed
    spacer 2 (ITS2) throughout the Eukaryota.}},
  journal = {RNA},
  year = {2005},
  volume = {11},
  pages = {361--364},
  number = {4},
  month = {Apr},
  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.},
  doi = {10.1261/rna.7204505},
  institution = {entrum.uni-wuerzburg.de},
  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},
  owner = {binf007},
  pii = {11/4/361},
  pmid = {15769870},
  timestamp = {2008.01.21},
  url = {http://dx.doi.org/10.1261/rna.7204505}
}

@ARTICLE{Schultz2006,
  author = {Jörg Schultz and Tobias Müller and Marco Achtziger and Philipp N
    Seibel and Thomas Dandekar and Matthias Wolf},
  title = {{The internal transcribed spacer 2 database--a web server for (not
    only) low level phylogenetic analyses.}},
  journal = {Nucleic Acids Res},
  year = {2006},
  volume = {34},
  pages = {W704--W707},
  number = {Web Server issue},
  month = {Jul},
  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.},
  doi = {10.1093/nar/gkl129},
  institution = {Department of Bioinformatics, Biocenter, University of Würzburg Am
    Hubland, 97074 Würzburg, Germany. Joerg.Schultz@biozentrum.uni-wuerzburg.de},
  keywords = {DNA, Ribosomal Spacer; Databases, Nucleic Acid; Internet; Nucleic
    Acid Conformation; Phylogeny; Sequence Analysis, RNA; Software; User-Computer
    Interface},
  owner = {binf007},
  pii = {34/suppl_2/W704},
  pmid = {16845103},
  timestamp = {2008.01.21},
  url = {http://dx.doi.org/10.1093/nar/gkl129}
}

@ARTICLE{Schoeniger1994,
  author = {M. Schöniger and A. von Haeseler},
  title = {{A stochastic model for the evolution of autocorrelated DNA sequences.}},
  journal = {Mol Phylogenet Evol},
  year = {1994},
  volume = {3},
  pages = {240--247},
  number = {3},
  month = {Sep},
  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.},
  doi = {10.1006/mpev.1994.1026},
  institution = {Technical University Munich, Germany.},
  keywords = {Animals; DNA; DNA, Mitochondrial; Evolution; Mammals; Markov Chains;
    Mutation; RNA, Bacterial; RNA, Ribosomal, 23S; Species Specificity;
    Stochastic Processes},
  owner = {binf007},
  pii = {S1055-7903(84)71026-8},
  pmid = {7529616},
  timestamp = {2008.01.25},
  url = {http://dx.doi.org/10.1006/mpev.1994.1026}
}

@ARTICLE{Seibel2006,
  author = {Philipp N Seibel and Tobias Müller and Thomas Dandekar and Jörg Schultz
    and Matthias Wolf},
  title = {{4SALE--a tool for synchronous RNA sequence and secondary structure
    alignment and editing.}},
  journal = {BMC Bioinformatics},
  year = {2006},
  volume = {7},
  pages = {498},
  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.},
  doi = {10.1186/1471-2105-7-498},
  institution = {>},
  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},
  pii = {1471-2105-7-498},
  pmid = {17101042},
  timestamp = {2008.01.21},
  url = {http://dx.doi.org/10.1186/1471-2105-7-498}
}

@ARTICLE{Selig2008,
  author = {Christian Selig and Matthias Wolf and Tobias Müller and Thomas Dandekar
    and Jörg Schultz},
  title = {{The ITS2 Database II: homology modelling RNA structure for molecular
    systematics.}},
  journal = {Nucleic Acids Res},
  year = {2008},
  volume = {36},
  pages = {D377--D380},
  number = {Database issue},
  month = {Jan},
  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.},
  doi = {10.1093/nar/gkm827},
  institution = {Department of Bioinformatics, Biocenter, University of Würzburg,
    Am Hubland 97074 Würzburg, Germany.},
  owner = {binf007},
  pii = {gkm827},
  pmid = {17933769},
  timestamp = {2008.01.21},
  url = {http://dx.doi.org/10.1093/nar/gkm827}
}

@ARTICLE{Siebert2005,
  author = {Sven Siebert and Rolf Backofen},
  title = {{MARNA: multiple alignment and consensus structure prediction of
    RNAs based on sequence structure comparisons.}},
  journal = {Bioinformatics},
  year = {2005},
  volume = {21},
  pages = {3352--3359},
  number = {16},
  month = {Aug},
  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.},
  doi = {10.1093/bioinformatics/bti550},
  institution = {Department of Bioinformatics, Institute of Computer Science, Friedrich-Schiller-University
    Jena, Ernst-Abbe Platz 2, 07743 Jena, Germany.},
  keywords = {Algorithms; Computer Simulation; Consensus Sequence; RNA; Sensitivity
    and Specificity; Sequence Alignment; Sequence Analysis, RNA; Sequence
    Homology, Nucleic Acid; Software; Structure-Activity Relationship},
  owner = {binf007},
  pii = {bti550},
  pmid = {15972285},
  timestamp = {2008.01.21},
  url = {http://dx.doi.org/10.1093/bioinformatics/bti550}
}

@ARTICLE{Smith2004,
  author = {Andrew D Smith and Thomas W H Lui and Elisabeth R M Tillier},
  title = {{Empirical models for substitution in ribosomal RNA.}},
  journal = {Mol Biol Evol},
  year = {2004},
  volume = {21},
  pages = {419--427},
  number = {3},
  month = {Mar},
  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.},
  doi = {10.1093/molbev/msh029},
  institution = {Department of Medical Biophysics, University of Toronto, and Ontario
    Cancer Institute, University Health Network, Toronto, Ontario, Canada.},
  keywords = {Amino Acid Substitution; Animals; Computer Simulation; Databases,
    Nucleic Acid; Evolution, Molecular; Likelihood Functions; Models,
    Genetic; Phylogeny; RNA, Ribosomal; Sequence Alignment},
  owner = {binf007},
  pii = {msh029},
  pmid = {14660689},
  timestamp = {2008.01.21},
  url = {http://dx.doi.org/10.1093/molbev/msh029}
}

@MISC{QT,
  author = {Trolltech},
  title = {http://trolltech.com/products/qt/},
  year = {2008},
  owner = {binf007},
  timestamp = {2008.07.19},
  url = {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},
  title = {{The systematics of a small spineless Desmodesmus species, D-costato-granulatus
    (Sphaeropleales, Chlorophyceae), based on ITS2 rDNA sequence analyses
    and cell wall morphology}},
  journal = {Journal of Phyclology},
  year = {2007},
  volume = {43},
  pages = {378-396},
  number = {2},
  month = {APR}
}

@ARTICLE{Wheeler2000,
  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},
  title = {{Database resources of the National Center for Biotechnology Information.}},
  journal = {Nucleic Acids Res},
  year = {2000},
  volume = {28},
  pages = {10--14},
  number = {1},
  month = {Jan},
  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},
  institution = {National Center for Biotechnology Information, National Library of
    Medicine, National Institutes of Health, Building 38A, 8600 Rockville
    Pike, Bethesda, MD 20894, USA.},
  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},
  owner = {binf007},
  pii = {gkd055},
  pmid = {10592169},
  timestamp = {2008.01.21}
}

@ARTICLE{Wolf2005,
  author = {Matthias Wolf and Marco Achtziger and Jörg Schultz and Thomas Dandekar
    and Tobias Müller},
  title = {{Homology modeling revealed more than 20,000 rRNA internal transcribed
    spacer 2 (ITS2) secondary structures.}},
  journal = {RNA},
  year = {2005},
  volume = {11},
  pages = {1616--1623},
  number = {11},
  month = {Nov},
  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.},
  doi = {10.1261/rna.2144205},
  institution = {Department of Bioinformatics, University of Würzburg, Biocenter,
    Am Hubland, Germany. matthias.wolf@biozentrum.uni-wuerzburg.de},
  keywords = {Algae; Animals; Base Sequence; DNA, Ribosomal Spacer; Evolution, Molecular;
    Fungi; Models, Molecular; Molecular Sequence Data; Nucleic Acid Conformation;
    RNA, Ribosomal; Sequence Alignment},
  owner = {binf007},
  pii = {11/11/1616},
  pmid = {16244129},
  timestamp = {2008.01.21},
  url = {http://dx.doi.org/10.1261/rna.2144205}
}

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