Nucleic Acids Research

Geraci, Filippo; Pellegrini, Marco; Renda, M. Elena

doi: 10.1093/nar/gkn265pmid: 18477631

The AMIC@ Web Server offers a light-weight multi-method clustering engine for microarray gene-expression data. AMIC@ is a highly interactive tool that stresses user-friendliness and robustness by adopting AJAX technology, thus allowing an effective interleaved execution of different clustering algorithms and inspection of results. Among the salient features AMIC@ offers, there are: (i) automatic file format detection, (ii) suggestions on the number of clusters using a variant of the stability-based method of Tibshirani et al. (iii) intuitive visual inspection of the data via heatmaps and (iv) measurements of the clustering quality using cluster homogeneity. Large data sets can be processed efficiently by selecting algorithms (such as FPF-SB and k-Boost), specifically designed for this purpose. In case of very large data sets, the user can opt for a batch-mode use of the system by means of the Clustering wizard that runs all algorithms at once and delivers the results via email. AMIC@ is freely available and open to all users with no login requirement at the following URL http://bioalgo.iit.cnr.it/amica.

Lyskov, Sergey; Gray, Jeffrey J.

doi: 10.1093/nar/gkn216pmid: 18442991

The RosettaDock server (http://rosettadock.graylab.jhu.edu) identifies low-energy conformations of a protein–protein interaction near a given starting configuration by optimizing rigid-body orientation and side-chain conformations. The server requires two protein structures as inputs and a starting location for the search. RosettaDock generates 1000 independent structures, and the server returns pictures, coordinate files and detailed scoring information for the 10 top-scoring models. A plot of the total energy of each of the 1000 models created shows the presence or absence of an energetic binding funnel. RosettaDock has been validated on the docking benchmark set and through the Critical Assessment of PRedicted Interactions blind prediction challenge.

Walsh, Thomas P.; Webber, Caleb; Searle, Stephen; Sturrock, Shane S.; Barton, Geoffrey J.

doi: 10.1093/nar/gkn320pmid: 18503088

SCANPS performs iterative profile searching similar to PSI-BLAST but with full dynamic programing on each cycle and on-the-fly estimation of significance. This combination gives good sensitivity and selectivity that outperforms PSI-BLAST in domain-searching benchmarks. Although computationally expensive, SCANPS exploits onchip parallelism (MMX and SSE2 instructions on Intel chips) as well as MPI parallelism to give acceptable turnround times even for large databases. A web server developed to run SCANPS searches is now available at http://www.compbio.dundee.ac.uk/www-scanps. The server interface allows a range of different protein sequence databases to be searched including the SCOP database of protein domains. The server provides the user with regularly updated versions of the main protein sequence databases and is backed up by significant computing resources which ensure that searches are performed rapidly. For SCOP searches, the results may be viewed in a new tree-based representation that reflects the structure of the SCOP hierarchy; this aids the user in placing each hit in the context of its SCOP classification and understanding its relationship to other domains in SCOP.

Barquist, Lars; Holmes, Ian

doi: 10.1093/nar/gkn283pmid: 18522975

Phylo-grammars, probabilistic models combining Markov chain substitution models with stochastic grammars, are powerful models for annotating structured features in multiple sequence alignments and analyzing the evolution of those features. In the past, these methods have been cumbersome to implement and modify. xrate provides means for the rapid development of phylo-grammars (using a simple file format) and automated parameterization of those grammars from training data (via the Expectation Maximization algorithm). xREI (pron. ‘X-ray’) is an intuitive, flexible AJAX (Asynchronous Javascript And XML) web interface to xrate providing grammar visualization tools as well as access to xrate's training and annotation functionality. It is hoped that this application will serve as a valuable tool to those developing phylo-grammars, and as a means for the exploration and dissemination of such models. xREI is available at http://harmony.biowiki.org/xrei/

Schneidman-Duhovny, Dina; Dror, Oranit; Inbar, Yuval; Nussinov, Ruth; Wolfson, Haim J.

doi: 10.1093/nar/gkn187pmid: 18424800

Predicting molecular interactions is a major goal in rational drug design. Pharmacophore, which is the spatial arrangement of features that is essential for a molecule to interact with a specific target receptor, is an important model for achieving this goal. We present a freely available web server, named PharmaGist, for pharmacophore detection. The employed method is ligand based. Namely, it does not require the structure of the target receptor. Instead, the input is a set of structures of drug-like molecules that are known to bind to the receptor. The output consists of candidate pharmacophores that are computed by multiple flexible alignment of the input ligands. The method handles the flexibility of the input ligands explicitly and in deterministic manner within the alignment process. PharmaGist is also highly efficient, where a typical run with up to 32 drug-like molecules takes seconds to a few minutes on a stardard PC. Another important characteristic is the capability of detecting pharmacophores shared by different subsets of input molecules. This capability is a key advantage when the ligands belong to different binding modes or when the input contains outliers. The webserver has a user-friendly interface available at http://bioinfo3d.cs.tau.ac.il/PharmaGist.

Zhang, Qing; Wang, Peng; Kim, Yohan; Haste-Andersen, Pernille; Beaver, John; Bourne, Philip E.; Bui, Huynh-Hoa; Buus, Soren; Frankild, Sune; Greenbaum, Jason; Lund, Ole; Lundegaard, Claus; Nielsen, Morten; Ponomarenko, Julia; Sette, Alessandro; Zhu, Zhanyang; Peters, Bjoern

doi: 10.1093/nar/gkn254

Tjaden, Brian

doi: 10.1093/nar/gkn264pmid: 18477632

Many small RNA (sRNA) genes in bacteria act as posttranscriptional regulators of target messenger RNAs. Here, we present TargetRNA, a web tool for predicting mRNA targets of sRNA action in bacteria. TargetRNA takes as input a genomic sequence that may correspond to an sRNA gene. TargetRNA then uses a dynamic programming algorithm to search each annotated message in a specified genome for mRNAs that evince basepair-binding potential to the input sRNA sequence. Based on the calculated basepair-binding potential of each message with the given sRNA regulator, TargetRNA outputs a ranked list of candidate mRNA targets along with the predicted basepairing interaction of each target to the sRNA. The predictive performance of TargetRNA has been validated experimentally in several bacterial organisms. TargetRNA is freely available at http://snowwhite.wellesley.edu/targetRNA.

Šegota, Igor; Bartoniček, Nenad; Vlahoviček, Kristian

doi: 10.1093/nar/gkn289pmid: 18480121

MADNet is a user-friendly data mining and visualization tool for rapid analysis of diverse high-throughput biological data such as microarray, phage display or even metagenome experiments. It presents biological information in the context of metabolic and signalling pathways, transcription factors and drug targets through minimal user input, consisting only of the file with the experimental data. These data are integrated with information stored in various biological databases such as NCBI nucleotide and protein databases, metabolic and signalling pathway databases (KEGG), transcription regulation (TRANSFAC©) and drug target database (DrugBank). MADNet is freely available for academic use at http://www.bioinfo.hr/madnet.

Okuda, Shujiro; Yamada, Takuji; Hamajima, Masami; Itoh, Masumi; Katayama, Toshiaki; Bork, Peer; Goto, Susumu; Kanehisa, Minoru

doi: 10.1093/nar/gkn282pmid: 18477636

KEGG Atlas is a new graphical interface to the KEGG suite of databases, especially to the systems information in the PATHWAY and BRITE databases. It currently consists of a single global map and an associated viewer for metabolism, covering about 120 KEGG metabolic pathway maps and about 10 BRITE hierarchies. The viewer allows the user to navigate and zoom the global map under the Ajax technology. The mapping of high-throughput experimental data onto the global map is the main use of KEGG Atlas. In the global metabolism map, the node (circle) is a chemical compound and the edge (line) is a set of reactions linked to a set of KEGG Orthology (KO) entries for enzyme genes. Once gene identifiers in different organisms are converted to the K number identifiers in the KO system, corresponding line segments can be highlighted in the global map, allowing the user to view genome sequence data as organism-specific pathways, gene expression data as up- or down-regulated pathways, etc. Once chemical compounds are converted to the C number identifiers in KEGG, metabolomics data can also be displayed in the global map. KEGG Atlas is available at http://www.genome.jp/kegg/atlas/.

Lesburg, Charles A.; Duca, José S.

doi: 10.1093/nar/gkn270pmid: 18487276

soaPDB is a web application that allows generation and organization of saved PDB searches, and offers automatic email alerts. This tool is used from a web interface to store PDB searches and results in a backend relational database. Written using the Ruby on Rails open-source web framework, soaPDB is easy to deploy, maintain and customize. soaPDB is freely available upon request for local installation and is also available at http://soapdb.dyndns.org:3000.