Baran R, Robert M, Suematsu M, Soga T, Tomita M. Visualization of three-way comparisons of omics data. [BMC Bioinformatics. 2007 Mar 5;8:72]: Introduces a color-coding approach for representing three-way comparisons in heat maps, which are currently limited to single datasets or pairwise comparisons. The approach is based on the HSB (hue, saturation, brightness) color model. The three compared values are assigned specific hue values from a circular hue range, and the hue value representing the three-way comparison is calculated according to the distribution of three compared values.
Burgoon LD, Zacharewski TR. dbZach toxicogenomic information management system. [Pharmacogenomics. 2007 Mar;8(3):287-91]: Describes a toxicogenomic information management system called dbZach, a modular relational database with data insertion, retrieval, and mining tools. The database “manages traditional toxicology and complementary toxicogenomic data to facilitate comprehensive data integration, analysis and sharing,” according to the authors.
Doh ST, Zhang Y, Temple MH, Cai L. Non-coding sequence retrieval system for comparative genomic analysis of gene regulatory elements. [BMC Bioinformatics. 2007 Mar 15;8(1):94]: Introduces the NCSRS (non-coding sequence retrieval system), a web-based bioinformatics tool for retrieving non-coding and coding sequences from multiple species related to a specific gene or set of genes. Availability: http://cell.rutgers.edu/ncsrs/.
Grosdidier A, Zoete V, Michielin O. EADock: Docking of small molecules into protein active sites with a multiobjective evolutionary optimization. [Proteins. 2007 Mar 22 (e-pub ahead of print)]: Introduces a new docking software called EADock that uses a hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is integrated with the CHARMM package for energy calculations and coordinate handling.
Huber HJ, Rehm M, Plchut M, Dussmann H, Prehn JH. APOPTO-CELL—a simulation tool and interactive database for analyzing cellular susceptibility to apoptosis. [Bioinformatics 2007 23(5):648-650]: Describes a web service for analyzing the susceptibility of cells to undergo apoptosis in response to an activation of the mitochondrial apoptotic pathway. The service uses ordinary differential equations, pre-determined protein concentrations, and release kinetics of mitochondrial pro-apoptotic factors with a network of 52 reactions and 19 reaction partners. The service also enables the deposition of cell-type-specific quantitative data. Availability: http://systemsbiology.rcsi.ie/apopto-cell.html
Kristian H, Bohnebeck U, Beszteri B, Valentin K. PhyloGena — a user-friendly system for automated phylogenetic annotation of unknown sequences. [Bioinformatics. 2007 Mar 1; (e-pub ahead of print)]: Discusses a flexible pipeline called PhyloGena that runs on desktop computers that automatically performs a Blast search of query sequences, selects a representative subset of them, creates a multiple alignment from the selected sequences, and computes a phylogenetic tree. Availability: http://awi.de/en/go/phylogena.
Latek D, Ekonomiuk D, Kolinski A. Protein structure prediction: Combining de novo modeling with sparse experimental data. [J Comput Chem. 2007 Mar 6; (e-pub ahead of print)]: Presents an approach to protein structure modeling “supported by sparse, and relatively easy to obtain, experimental data,” such as chemical shift-based restraints from nuclear magnetic resonance. The computational procedure is based on the reduced representation approach implemented in the CABS modeling software.
Rodriguez N, Donizelli M, Le Novere N. SBMLeditor: effective creation of models in the Systems Biology Markup Language (SBML). [BMC Bioinformatics 2007, 8:79]: Introduces SBMLeditor, a low-level editor for Systems Biology Markup Language files. SBMLeditor can “create and remove all the necessary bits and pieces of SBML in a controlled way,” while maintaining the validity of the final SBML file, according to the authors.
Shen J, Zhang J, Luo X, Zhu W, Yu K, Chen K, Li Y, Jiang H. Predicting protein-protein interactions based only on sequences information. [Proc Natl Acad Sci USA. 2007 Mar 13;104(11):4337-41]: Proposes a method for predicting protein-protein interactions using only the information of protein sequences. This method is based on a support vector machine combined with a kernel function and a conjoint triad feature for describing amino acids.
Zhu H, Hu GQ, Yang YF, Wang J, She ZS. MED: a new non-supervised gene prediction algorithm for bacterial and archaeal genomes. [BMC Bioinformatics 2007, 8:97]: Describes a new prokaryotic gene-finding algorithm based on a statistical model of protein-coding open reading frames and translation initiation sites. The ORF-based approach is based on a linguistic entropy density profile model of coding DNA sequence and the second approach includes “several relevant features related to the translation initiation.” The two are combined to form a multivariate entropy distance algorithm.