Chen R, Mallelwar R, Thosar A, Venkatasubrahmanyam S, Butte AJ. GeneChaser: Identifying all biological and clinical conditions in which genes of interest are differentially expressed. [BMC Bioinformatics. 2008 Dec 18;9(1):548]: Describes a web server, called Gene Change Browser, or GeneChaser, that automatically reannotates and analyzes data sets for the Gene Expression Omnibus, performs group-versus-group comparisons, identifies experimental conditions where the expression levels of a gene or set of genes is significantly changed, and displays them graphically with statistical comparisons and sort/filter functions. Available here.
Hill J, Hambley M, Forster T, Mewissen M, Sloan TM, Scharinger F, Trew A, Ghazal P. SPRINT: A new parallel framework for R. [BMC Bioinformatics. 2008 Dec 29;9(1):558]: Introduces a framework called the Simple Parallel R Interface, or SPRINT, that parallelizes R for use in high-performance computing systems. The approach “requires very little modification to existing sequential R scripts and no expertise in parallel computing,” according to the paper’s abstract. Available here.
Kratz A, Tomita M, Krishnan A. GeNESiS: gene network evolution simulation software. [BMC Bioinformatics. 2008 Dec 16;9(1):541]: Describes a parallel software package called GeNESiS (Gene Network Evolution Simulation Software) for modeling the evolution of gene regulatory networks through a combination of finite-state and stochastic models. “The evolution of GRNs is then simulated by means of a genetic algorithm with the network connections represented as binary strings,” according to the paper’s abstract. Available here.
Nielsen J, Mailund T. SNPFile — A software library and file format for large scale association mapping and population genetics studies. [BMC Bioinformatics. 2008 Dec 8;9(1):526]: Describes a new binary file format for SNP data, together with a software library for file manipulation. The file format stores genotype data together with additional data. Available here.
Paten B, Herrero J, Beal K, Birney E. Sequence progressive alignment, a framework for practical large-scale probabilistic consistency alignment. [Bioinformatics. 2008 Dec 4. (e-pub ahead of print)]: Describes a new method for aligning large genomic sequences called Pecan that is based on a “sequence progressive alignment” framework that allows users to iteratively compute an alignment by passing over the input sequences from left to right. “The result is that we massively decrease the memory consumption of the program relative to a naive implementation,” according to the paper’s abstract. Available here.
Pounds S, Cheng C, Mullighan C, Raimondi SC, Shurtleff S, Downing JR. Reference Alignment of SNP Microarray Signals for Copy Number Analysis of Tumors. [Bioinformatics. 2008 Dec 3. (e-pub ahead of print)]: Introduces a new method, called reference alignment procedure, or RAP, for aligning SNP microarray signals for copy number analysis. For each individual array, RAP uses a set of selected markers as internal references to direct the signal alignment and aligns the signals so that each array has a similar signal distribution among its reference markers. An accompanying method, called the reference selection algorithm, or RSA, uses genotype calls and initial signal intensities to choose two-copy markers as the internal references for each array. “RSA-RAP gives copy number analysis results that show substantially better concordance with cytogenetics than do two other alignment procedures,” according to the paper’s abstract. Available here.
Rhee H, Lee JS. MedRefSNP: a database of medically investigated SNPs. [Hum Mutat. 2008 Dec 22. (e-pub ahead of print)]: Describes the MedRefSNP database, which provides integrated information about SNPs collected from the PubMed and Online Mendelian Inheritance in Man databases. RefSNP identifiers are automatically identified and are linked to other resources, such as dbSNP, the HapMap database, the Entrez Gene database, the UCSC genome browser, the CGAP Pathway Searcher, and genetic association databases. MedRefSNP currently contains 36,199 unique SNPs (including 31,368 neighboring SNPs) collected from 25,906 PubMed abstracts and 590 OMIM records, along with 2,491 human genes related to 466 molecular pathways. Available here.
Stanislaus R, Carey M, Deus HF, Coombes K, Hennessy BT, Mills GB, Almeida JS. RPPAML/RIMS: A meta data format and an information management system for Reverse Phase Protein Arrays. [BMC Bioinformatics. 2008 Dec 22;9(1):555]: Presents an information management system for reverse phase protein arrays, which are used to investigate the presence of biomarkers in tissue lysates. The system, called the RPPA Information Management System, or RIMS, is implemented with a metadata format called reverse phase protein array markup language, or RPPAML. The RIMS platform was designed to interoperate with other data analysis and data visualization tools such as Cytoscape. Available here.
Yen CY, Meyer-Arendt K, Eichelberger B, Sun S, Houel S, Old WM, Knight R, Ahn NG, Hunter LE, Resing KA. A simulated MS/MS library for spectrum-to-spectrum searching in large-scale identification of proteins. [Mol Cell Proteomics. 2008 Dec 22. (e-pub ahead of print)]: Discusses the use of simulated spectral libraries as a substitute for the reference libraries used by the spectrum-to-spectrum peptide search programs X!Hunter and BiblioSpec. According to the authors, spectrum-to-spectrum matching offers advantages over search strategies that map protein sequences to spectra, but the approach has been limited by “the small sizes of the available peptide MS/MS libraries and the inability to evaluate the rate of false assignments.” They note that their study demonstrated “good performance of simulated spectra generated by the kinetic model implemented in MassAnalyzer” as a substitute for the X!Hunter and BiblioSpec reference libraries, and similar results compared to Mascot, a spectrum-to-sequence program. ”We conclude that simulated spectral libraries greatly expand the search space available for spectrum-to-spectrum searching while enabling principled analyses, and that the approach can be used in consensus strategies for large scale studies while reducing search times,” the paper’s abstract states.