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Bioinformatics Tool-Related Papers of Note, August 2006

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Atlamazoglou V, Thireou T, Hamodrakas Y, Spyrou G. MetaBasis: A Web-Based Database Containing Metadata on Software Tools and Databases in the Field of Bioinformatics. [Appl Bioinformatics. 2006;5(3):187-92]: Describes a web-based relational database that enables searching for available bioinformatics computing resources. Availability: http://metabasis.bioacademy.gr/.
 

 
Bellew M, Coram M, Fitzgibbon M, et al. A suite of algorithms for the comprehensive analysis of complex protein mixtures using high-resolution LC-MS. [Bioinformatics 2006 22(15):1902-1909]: Presents msInspect, an open-source application for analyzing multiple LC-MS experimental measurements. The platform integrates algorithms for detecting signatures of natural peptides within a single LC-MS measurement and combines multiple experimental measurements into a peptide array, “which may then be mined using analysis tools traditionally applied to genomic array analysis,” according to the paper’s abstract. The platform supports quantitation by both label-free and isotopic labeling approaches. Availability: http://proteomics.fhcrc.org/.
 

 
Boehm AM, Sickmann A. A comprehensive dictionary of protein accession codes for complete protein accession identifier alias resolving. [Proteomics. 2006 Aug 3;6(15):4223-4226]: Presents a method for addressing a challenge of mass spectrometry-based proteomics, in which certain annotations are only available in particular databases that must be queried by a certain identifier. The authors describe a system “capable of set-oriented mapping the different accession identifiers of proteins derived from multiple sequence database sources” in order to simplify the tracing of identified proteins back to their original annotation information. Availability: http://132.187.167.15/cgi-bin/seqdb/webseqinfo.pl.
 

 
Busch A, Backofen R. INFO-RNA — a fast approach to inverse RNA folding. [Bioinformatics 2006 22(15):1823-1831] 16709587: Discusses a new algorithm for inverse RNA folding that comprises a dynamic programming method for good initial sequences followed by a an improved stochastic local search. The algorithm performed better than RNAinverse and RNA-SSD in “most cases,” according to the authors. Availability: www.bioinf.uni-freiburg.de?Subpages/software.html
 

 
Gould J, Getz G, Monti S, Reich M, Mesirov JP. Comparative gene marker selection suite. [Bioinformatics 2006 22(15):1924-1925]: Introduces the Comparative Marker Selection suite, which includes three modules for comparing different methods of computing significance for marker genes, a viewer to assess the results, and a tool to create derivative datasets and marker lists based on user-defined significance criteria. Availability: http://www.broad.mit.edu/genepattern.
 

 
Huber W, Toedling J, Steinmetz LM. Transcript mapping with high-density oligonucleotide tiling arrays. [Bioinformatics 2006 22(16):1963-1970]: Presents a dynamic programming algorithm for finding a globally optimal fit of a piecewise constant expression profile along genomic coordinates in high-density DNA tiling microarrays. The probe-specific background correction and scaling method uses probe response parameters determined from reference hybridizations with no need for paired mismatch probes, according to the authors. Availability: http://www.bioconductor.org/ (TilingArray package).
 

 
Johnson WE, Li W, Meyer CA, Gottardo R, Carroll JS, Brown M, Liu XS. Model-based analysis of tiling-arrays for ChIP-chip. [Proc Natl Acad Sci USA. 2006 Aug 15;103(33):12457-62]: Presents Model-based Analysis of Tiling-arrays (MAT), an algorithm for detecting regions enriched by transcription factor chromatin immunoprecipitation on Affymetrix tiling arrays. MAT models baseline probe behavior by considering probe sequence and copy number on each array and standardizes the probe value through the probe model in order to eliminate the need for sample normalization. MAT uses an “innovative function” to score regions for ChIP enrichment, according to the paper’s abstract, “which allows robust P value and false discovery rate calculations.” Availability: http://chip.dfci.harvard.edu/~wli/MAT.
 

 
Morgan DH, Kristensen DM, Mittelman D, Lichtarge O. ET viewer: an application for predicting and visualizing functional sites in protein structures. [Bioinformatics 2006 22(16):2049-2050]: Describes the Evolutionary Trace Viewer, an environment in which to run, visualize, and interpret evolutionary trace (ET) predictions of functional sites in protein structures. Availability: http://mammoth.bcm.tmc.edu/traceview/index.html.
 

 
Nicolae DL, Wu X, Miyake K, Cox NJ. GEL: a novel genotype calling algorithm using empirical likelihood. [Bioinformatics 2006 22(16):1942-1947]: Introduces a genotype-calling algorithm for Affymetrix GeneChip arrays that uses likelihood calculations based on distributions inferred from the observed data. “A key ingredient in accurate genotype calling is weighting the information that comes from each probe quartet according to the quality/reliability of the data in the quartet, and prior information on the performance of the quartet,” the authors note in the paper’s abstract. The algorithm is expected to overcome some limitations of existing algorithms, which lead to an increased error rate in heterozygous genotypes, and a disproportionately large rate of heterozygotes with missing genotypes,” according to the authors. Availability: from the author upon request ([email protected]).
 

 
Roberts E, Eargle J, Wright D, Luthey-Schulten Z. MultiSeq: Unifying sequence and structure data for evolutionary analysis. [BMC Bioinformatics. 2006 Aug 16;7(1):382]: Describes MultiSeq, a bioinformatics analysis environment for organizing, displaying, aligning, and analyzing sequence and structure data for proteins and nucleic acids. MultiSeq includes a new algorithm to generate evolutionary profiles that represent the topology of the molecular phylogenetic tree of a homologous group of distantly related proteins. Availability: http://www.scs.uiuc.edu/~schulten/multiseq/.
 

 
Sole X, Guino E, Valls J, Iniesta R, Moreno V. SNPStats: a web tool for the analysis of association studies. [Bioinformatics 2006 22(15):1928-1929]: Describes a web-based application for analyzing association studies in the context of genetic epidemiology. Capabilities include descriptive analysis, a test for Hardy–Weinberg equilibrium and linkage disequilibrium, analysis of single SNPs, and analysis of multiple SNPs. Availability: http://bioinfo.iconcologia.net/SNPstats.
 

 
Swidan F, Rocha EPC, Shmoish M, Pinter RY. An Integrative Method for Accurate Comparative Genome Mapping. [PLoS Comput Biol 2(8): e75]: Introduces a method for comparative genome mapping that includes two phases: preprocessing for identifying “maximal similar segments,” and mapping for clustering and classifying these segments.

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