References of "Bioinformatics"
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See detailjClust: a clustering and visualization toolbox
Pavlopoulos, Georgios A.; Moschopoulos, Charalampos N.; Hooper, Sean D. et al

in Bioinformatics (2009), 25(15), 1994-1996

jClust is a user-friendly application which provides access to a set of widely used clustering and clique finding algorithms. The toolbox allows a range of filtering procedures to be applied and is ... [more ▼]

jClust is a user-friendly application which provides access to a set of widely used clustering and clique finding algorithms. The toolbox allows a range of filtering procedures to be applied and is combined with an advanced implementation of the Medusa interactive visualization module. These implemented algorithms are k-Means, Affinity propagation, Bron-Kerbosch, MULIC, Restricted neighborhood search cluster algorithm, Markov clustering and Spectral clustering, while the supported filtering procedures are haircut, outside-inside, best neighbors and density control operations. The combination of a simple input. le format, a set of clustering and filtering algorithms linked together with the visualization tool provides a powerful tool for data analysis and information extraction. [less ▲]

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See detailMetaQuant: a tool for the automatic quantification of GC/MS-based metabolome data
Bunk, Boyke; Kucklick, Martin; Münch, Richard et al

in Bioinformatics (2006)

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See detailA framework for computational and experimental methods: identifying dimerization residues in CCR chemokine receptors.
de Juan, David; Mellado, Mario; Rodriguez-Frade, Jose Miguel et al

in Bioinformatics (2005), 21 Suppl 2

Solving relevant biological problems requires answering complex questions. Addressing such questions traditionally implied the design of time-consuming experimental procedures which most of the time are ... [more ▼]

Solving relevant biological problems requires answering complex questions. Addressing such questions traditionally implied the design of time-consuming experimental procedures which most of the time are not accessible to average-sized laboratories. The current trend is to move towards a multidisciplinary approach integrating both theoretical knowledge and experimental work. This combination creates a powerful tool for shedding light on biological problems. To illustrate this concept, we present here a descriptive example of where computational methods were shown to be a key aspect in detecting crucial players in an important biological problem: the dimerization of chemokine receptors. Using evolutionary based sequence analysis in combination with structural predictions two CCR5 residues were selected as important for dimerization and further validated experimentally. The experimental validation of computational procedures demonstrated here provides a wealth of valuable information not obtainable by any of the individual approaches alone. [less ▲]

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See detailComputational methods for the design of effective therapies against drug resistant HIV strains
Beerenwinkel, N.; Sing, T.; Lengauer, T. et al

in Bioinformatics (2005), 21(21), 3943-50

Summary: The development of drug resistance is a major obstacle to successful treatment of HIV infection. The extraordinary replication dynamics of HIV facilitates its escape from selective pressure ... [more ▼]

Summary: The development of drug resistance is a major obstacle to successful treatment of HIV infection. The extraordinary replication dynamics of HIV facilitates its escape from selective pressure exerted by the human immune system and by combination drug therapy. We have developed several computational methods whose combined use can support the design of optimal antiretroviral therapies based on viral genomic data. [less ▲]

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See detailTopology of small-world networks of protein-protein complex structures.
del Sol Mesa, Antonio UL; Fujihashi, Hirotomo; O'Meara, Paul

in Bioinformatics (2005), 21(8), 1311-5

The majority of real examples of small-world networks exhibit a power law distribution of edges among the nodes, therefore not fitting into the wiring model proposed by Watts and Strogatz. However ... [more ▼]

The majority of real examples of small-world networks exhibit a power law distribution of edges among the nodes, therefore not fitting into the wiring model proposed by Watts and Strogatz. However, protein structures can be modeled as small-world networks, with a distribution of the number of links decaying exponentially as in the case of this wiring model. We approach the protein-protein interaction mechanism by viewing it as a particular rewiring occurring in the system of two small-world networks represented by the monomers, where a re-arrangement of links takes place upon dimerization leaving the small-world character in the dimer network. Due to this rewiring, the most central residues at the complex interfaces tend to form clusters, which are not homogenously distributed. We show that these highly central residues are strongly correlated with the presence of hot spots of binding free energy. CONTACT: ao-mesa@fujirebio.co.jp SUPPLEMENTARY INFORMATION: http://www.fujirebio.co.jp/support/index.php (under construction). [less ▲]

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See detailA Gibbs sampler for identification of symmetrically structured, spaced DNA motifs with improved estimation of the signal length
Favorov, A.A.; Gelfand, M.S.; Gerasimova, A.V. et al

in Bioinformatics (2005), 21(10), 2240-2245

Motivation: Transcription regulatory protein factors often bind DNA as homo-dimers or hetero-dimers. Thus they recognize structured DNA motifs that are inverted or direct repeats or spaced motif pairs ... [more ▼]

Motivation: Transcription regulatory protein factors often bind DNA as homo-dimers or hetero-dimers. Thus they recognize structured DNA motifs that are inverted or direct repeats or spaced motif pairs. However, these motifs are often difficult to identify owing to their high divergence. The motif structure included explicitly into the motif recognition algorithm improves recognition efficiency for highly divergent motifs as well as estimation of motif geometric parameters. Result: We present a modification of the Gibbs sampling motif extraction algorithm, SeSiMCMC (Sequence Similarities by Markov Chain Monte Carlo), which finds structured motifs of these types, as well as non-structured motifs, in a set of unaligned DNA sequences. It employs improved estimators of motif and spacer lengths. The probability that a sequence does not contain any motif is accounted for in a rigorous Bayesian manner. We have applied the algorithm to a set of upstream regions of genes from two Escherichia coli regulons involved in respiration. We have demonstrated that accounting for a symmetric motif structure allows the algorithm to identify weak motifs more accurately. In the examples studied, ArcA binding sites were demonstrated to have the structure of a direct spaced repeat, whereas NarP binding sites exhibited the palindromic structure. Availability: The WWW interface of the program, its FreeBSD (4.0) and Windows 32 console executables are available at http://bioinform.genetika.ru/SeSiMCMC [less ▲]

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See detailVirtual Footprint and PRODORIC: an integrative framework for regulon prediction in prokaryotes
Münch, Richard; Hiller, Karsten UL; Grote, Andreas et al

in Bioinformatics (2005)

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See detailPTGL--a web-based database application for protein topologies.
May, Patrick UL; Barthel, Stefan; Koch, Ina

in Bioinformatics (2004), 20(17), 3277-9

Protein Topology Graph Library (PTGL) is a database application for the representation and retrieval of protein topologies. Protein topologies are based on a graph-theoretical protein model at secondary ... [more ▼]

Protein Topology Graph Library (PTGL) is a database application for the representation and retrieval of protein topologies. Protein topologies are based on a graph-theoretical protein model at secondary structure level. Different views on protein topology are given by four linear notations for their characterization. Protein topologies can be derived at different description levels considering alpha- and beta-structures. The on-line search tool is based on an object-relational database and provides a query browser for data interrogation by string patterns, keyword queries and sequence similarity. Protein topologies are represented both as schematic diagrams and as three-dimensional images. [less ▲]

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See detailLimited conformational space for early-stage protein folding simulation
Brylinski, M.; Jurkowski, Wiktor UL; Konieczny, L. et al

in Bioinformatics (2004), 20(2), 199-205

MOTIVATION: The problem of early-stage protein folding is critical for protein structure prediction. The model presented introduces a common definition of protein structures which may be treated as the ... [more ▼]

MOTIVATION: The problem of early-stage protein folding is critical for protein structure prediction. The model presented introduces a common definition of protein structures which may be treated as the possible in silico early-stage form of the polypeptide chain. Limitation of the conformational space to the ellipse path on the Ramachandran map was tested as a possible sub-space to represent the early-stage structure for simulation of protein folding. The proposed conformational sub-space was developed on the basis of the backbone conformation, with side-chain interactions excluded. RESULTS: The ellipse-path-limited conformation of BPTI was created using the criterion of shortest distance between Phi, Psi angles in native form of protein and the Phi, Psi angles belonging to the ellipse. No knots were observed in the structure created according to ellipse-path conformational sub-space. The energy minimization procedure applied to ellipse-path derived conformation directed structural changes toward the native form of the protein with SS-bonds system introduced to the procedure. AVAILABILITY: Program 'Ellipse' to create the ellipse-path derived structure available on request: myroterm@cyf-kr.edu.pl [less ▲]

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See detailA comprehensive set of protein complexes in yeast: mining large scale protein-protein interaction screens.
Krause, Roland UL; von Mering, Christian; Bork, Peer

in Bioinformatics (2003), 19(15), 1901-8

MOTIVATION: The analysis of protein-protein interactions allows for detailed exploration of the cellular machinery. The biochemical purification of protein complexes followed by identification of ... [more ▼]

MOTIVATION: The analysis of protein-protein interactions allows for detailed exploration of the cellular machinery. The biochemical purification of protein complexes followed by identification of components by mass spectrometry is currently the method, which delivers the most reliable information--albeit that the data sets are still difficult to interpret. Consolidating individual experiments into protein complexes, especially for high-throughput screens, is complicated by many contaminants, the occurrence of proteins in otherwise dissimilar purifications due to functional re-use and technical limitations in the detection. A non-redundant collection of protein complexes from experimental data would be useful for biological interpretation, but manual assembly is tedious and often inconsistent. RESULTS: Here, we introduce a measure to define similarity within collections of purifications and generate a set of minimally redundant, comprehensive complexes using unsupervised clustering. AVAILABILITY: Programs and results are freely available from http://www.bork.embl-heidelberg.de/Docu/purclust/ [less ▲]

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See detailINTERPRO
Apweiler, R.; Attwood, T. K.; Bairoch, A. et al

in Bioinformatics (2000)

InterPro is a new integrated documentation resource for protein families, domains and functional sites, developed as a means of rationalising the complementary efforts of the PROSITE, PRINTS, Pfam and ... [more ▼]

InterPro is a new integrated documentation resource for protein families, domains and functional sites, developed as a means of rationalising the complementary efforts of the PROSITE, PRINTS, Pfam and ProDom database projects. Merged annotations from PRINTS, PROSITE and Pfam form the InterPro core. Each combined InterPro entry includes functional descriptions and literature references, and links are made back to the relevant parent database(s), allowing users to see at a glance whether a particular family or domain has associated patterns, profiles, fingerprints, etc.. Merged and individual entries (i.e., those that have no counterpart in the companion resources) are assigned unique accession numbers. The first release of InterPro contains around 2,400 entries, representing families, domains, repeats and sites of post-translational modification (PTMs) encoded by 4,300 regular expressions, profiles, fingerprints and Hidden Markov Models (HMMs). Each InterPro entry lists all the matches against SWISS-PROT and TrEMBL (more than 370,000 hits in total). The database is accessible for text-based searches at http://www.ebi.ac.uk/ interpro/. [less ▲]

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