Alter O, Golub GH. Reconstructing the pathways of a cellular system from genome-scale signals by using matrix and tensor computations. [Proc Natl Acad Sci USA. 2005 Dec 6;102(49):17559-64]: Describes the use of the matrix eigenvalue decomposition (EVD) and pseudoinverse projection and a tensor higher-order EVD (HOEVD) in reconstructing the pathways that compose a cellular system from genome-scale nondirectional networks of correlations among the genes of the system. The authors illustrate the method using yeast DNA microarray data.
Binkowski TA, Joachimiak A, Liang J. Protein surface analysis for function annotation in high-throughput structural genomics pipeline. [Protein Sci. 2005 Dec;14(12):2972-81]: Introduces pvSOAR (pocket and void Surface of Amino Acid Residues), a method for comparing the protein surfaces of geometrically defined pockets and voids in order to detect novel functional relationships between surface features of proteins.
Evans P, Liu C. SiteFind: A software tool for introducing a restriction site as a marker for successful site-directed mutagenesis. [BMC Molecular Biology 2005, 6:22]: Discusses a computer program called SiteFind that can be used when introducing a restriction site near a point mutation to act as a marker to indicate successful mutation. SiteFind helps design a restriction site within mutation primers without changing the peptide sequence. "Since the list of possible restriction sites for a given DNA sequence is not always obvious, SiteFind automates this task," the authors note in the paper abstract. Availability: http://www.utmb.edu/scccb/software/sitefind.html
Jain T, Jayaram B. An all atom energy based computational protocol for predicting binding affinities of protein-ligand complexes. [FEBS Lett. 2005 Dec 5;579(29):6659-66]: Presents a computational method for predicting binding affinities of non-metallo protein-ligand complexes. The method builds in an all atom energy based empirical scoring function using electrostatics, van der Waals, hydrophobicity, and loss of conformational entropy of protein side chains upon ligand binding. Availability: http://www.scfbio-iitd.res.in/software/drugdesign/bappl.jsp.
Kemmer D, Huang Y, Shah SP, Lim J, Brumm J, Yuen MM, Ling J, Xu T, Wasserman WW, Ouellette BF. Ulysses an application for the projection of molecular interactions across species. [Genome Biol. 2005;6(12):R106]: Describes Ulysses, a system that uses a process called Interolog Analysis for the parallel analysis and display of protein interactions detected in various species. Ulysses performs Interolog Analysis by projecting model organism interaction data onto homologous human proteins. Availability: http://www.cisreg.ca/ulysses.
Lei Z, Dai Y. An SVM-based system for predicting protein subnuclear localizations. [BMC Bioinformatics 2005, 6:291]: Describes a software tool for predicting subnuclear and subcellular localizations of proteins using a support vector machine learning model. Availability: http://array.bioengr.uic.edu/subnuclear.htm.
Marino-Ramirez L, Hsu B, Baxevanis AD, Landsman D. The histone database: A comprehensive resource for histones and histone fold-containing proteins. [Proteins. 2005 Dec 12 (e-pub ahead of print)]: Discusses the Histone Database, a curated collection of full-length sequences and structures of histones and nonhistone proteins containing histone-like folds, compiled from major public databases. Availability: http://research.nhgri.nih.gov/histones/.
Montana G. HapSim: a simulation tool for generating haplotype data with pre-specified allele frequencies and LD coefficients. [Bioinformatics 2005 21(23):4309-4311]: Presents a simulation tool called HapSim for generating simulated haplotypes with allele frequencies and linkage disequilibrium coefficients that match exactly those estimated in a real sample. Availability: http://cran.r-project.org/.
Rauch A, Bellew M, Eng J, et al. Computational Proteomics Analysis System (CPAS): An Extensible, Open-Source Analytic System for Evaluating and Publishing Proteomic Data and High Throughput Biological Experiments. [J Proteome Res. 2006 Jan-Feb;5(1):112-21]: Describes the open-source Computational Proteomics Analysis System (CPAS), which includes a data-analysis and -management pipeline for liquid chromatography tandem mass spectrometry proteomics, including experiment annotation, protein database searching and sequence management, and mining LC-MS/MS peptide and protein identifications. Availability: http://proteomics.fhcrc.org/CPAS.
Sethupathy P, Corda B, Hatzigeorgiou AG. TarBase: A comprehensive database of experimentally supported animal microRNA targets. [RNA. 2005 Dec 22 (e-pub ahead of print)]: Describes TarBase, a manually curated collection of experimentally tested miRNA targets in human, mouse, fruit fly, worm, and zebrafish. Each positive target site is described by the miRNA that binds it, the gene in which it occurs, the nature of the experiments that were conducted to test it, the sufficiency of the site to induce translational repression and/or cleavage, and the paper from which all these data were extracted. Availability: http://www.diana.pcbi.upenn.edu/tarbase.
Siddharthan R, Siggia ED, van Nimwegen E. PhyloGibbs: A Gibbs Sampling Motif Finder That Incorporates Phylogeny. [PLoS Comput Biol 1(7): e67]: Introduces a new motif sampling algorithm, PhyloGibbs, that searches over all ways in which an arbitrary number of binding sites for an arbitrary number of transcription factors can be assigned to the multiple sequence alignments. The binding site configurations are scored by a Bayesian probabilistic model that takes into account the evolution of binding sites, "background" intergenic DNA, and the phylogenetic relationship between the species in the alignment. Availability: http://www.biozentrum.unibas.ch/~nimwegen/cgi-bin/phylogibbs.cgi.
Simon I, Siegfried Z, Ernst J, Bar-Joseph Z. Combined static and dynamic analysis for determining the quality of time-series expression profiles. [Nat Biotechnol. 2005 Dec;23(12):1503-8]: Discusses an approach for expression profiling of time-series experiments that combines time-series and average expression data analysis. For each gene, the algorithm determines whether its temporal expression profile can be reconciled with its static expression levels. According to the authors, the method is able to identify many cycling genes that are missed when using only time-series data.
Vencio RZ, Koide T. HTself: Self-Self Based Statistical Test for Low Replication Microarray Studies. [DNA Res. 2005;12(3):211-4]: Discusses a web-based bioinformatics tool that uses an empirically derived criterion to classify a gene as differentially expressed by combining two ideas in microarray analysis: self-self experiments to derive intensity-dependent cutoffs and non-parametric estimation techniques. Availability: http://blasto.iq.usp.br/~rvencio/HTself.
Xia X, McClelland M, Wang Y. WebArray: an online platform for microarray data analysis. [BMC Bioinformatics. 2005 Dec 21;6(1):306]: Describes WebArray, a web-based user interface for the limma and affy packages in Bioconductor, which currently require "sophisticated knowledge of mathematics, statistics and computer skills for implementation," according to the authors. WebArray is based on the limma and affy packages, the spacings LOESS histogram (SPLOSH) method, and the PCA-assisted normalization method and genome mapping method. Availability: http://bioinformatics.skcc.org/webarray/.