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In Print: Bioinformatics Tool-Related Papers of Note, April 2005


Brown W, Faulon J, Sale K. A deterministic algorithm for constrained enumeration of transmembrane protein folds. [Comput Biol Chem. 2005 Apr;29(2):143-50]: Describes a deterministic algorithm for enumeration of transmembrane protein folds using a set of sparse pairwise atomic distance constraints. The algorithm results in a set of distinct protein conformations, which can be scored and refined as part of a process designed for computational elucidation of transmembrane protein structures.

Cavallo A, Martin A. Mapping SNPs to protein sequence and structure data. [Bioinformatics 2005 21(8):1443-1450]: Presents an integrated pipeline for the automated mapping of single amino acid polymorphism data from HGVbase to individual PDB residues. Availability:

Chou H. VECT: an automatic visual Perl programming tool for nonprogrammers. [Biotechniques. 2005 Apr;38(4):615-21]: Describes VECT (Visual Extraction and Conversion Tool), which was developed to enable nonprogrammers to create simple bioinformatics applications without mastering a programming language. VECT provides a unified graphical user interface for data extraction, data conversion, output composition, and Perl code generation. Availability:

Dowd S, Zaragoza J, Rodriguez J, Oliver M, Payton P. Windows .NET Network Distributed Basic Local Alignment Search Toolkit (W.ND-BLAST). [BMC Bioinformatics 2005, 6:93]: Describes a software application called Windows .NET Distributed Basic Local Alignment Search Toolkit (W.ND-BLAST), which enables users to distribute Blast queries across any number of Windows-based machines across a local area network. Availability:

Fayz B, Moldenhauer J, Wang D, et al. LARALink: a web application for cytogenetic linkage analysis. [Clin Genet. 2005 Apr;67(4):314-21]: Describes LARALink (Loci Analysis for Rearrangements Link), a web application that uses several public datasets to analyze clinical cytogenetic data to identify candidate genes. LARALink allows UniGene clusters or SNPs to be queried for multiple patients by cytoband, chromosome marker, or base pair. Availability:

Garcia A, Thoraval S, Garcia L, Ragan M. Workflows in bioinformatics: meta-analysis and prototype implementation of a workflow generator. [BMC Bioinformatics 2005, 6:87]: Describes GPIPE, a prototype graphic pipeline generator for the PISE application that allows the definition of a pipeline, parameterization of its component methods, and storage of metadata in XML formats. Availability:

Holford M, Li N, Nadkarni P, Zhao H. VitaPad: visualization tools for the analysis of pathway data. [Bioinformatics 2005 21(8):1596-1602]: Presents VitaPad, a cross-platform application that enables users to create and modify biological pathway diagrams and incorporate microarray data with them. Availability:

Kann M, Thiessen P, Panchenko A, Schäffer A, Altschul S, Bryant S. A structure-based method for protein sequence alignment. [Bioinformatics 2005 21(8):1451-1456]: Introduces SALTO (Structure-based Alignment Tool), which aligns protein query sequences to position-specific scoring matrices using rules for placing and scoring gaps that are consistent with the conserved regions of domain alignments from NCBI's Conserved Domain Database. Availability:

Kikuchi N, Kameyama A, Nakaya S, et al. The carbohydrate sequence markup language (CabosML): an XML description of carbohydrate structures. [Bioinformatics 2005 21(8):1717-1718]: Presents a carbohydrate sequence markup language (CabosML), an XML description of carbohydrate structures. Availability:

Liu J, Wang J, Hu J, Tian B. A method for aligning RNA secondary structures and its application to RNA motif detection. [BMC Bioinformatics 2005, 6:89]: Describes RSmatch, a tool for aligning RNA secondary structures and for motif detection. The method decomposes an RNA secondary structure into a set of atomic structure components that are further organized by a tree model to capture the structural particularities.

Marinescu V, Kohane I, Riva A. MAPPER: a search engine for the computational identification of putative transcription factor binding sites in multiple genomes. [BMC Bioinformatics 2005, 6:79]: Presents a search method for putative transcription factor binding sites based on hidden Markov models built from alignments of known sites. Availability:

Nikolsky Y, Ekins S, Nikolskaya T, Bugrim A. A novel method for generation of signature networks as biomarkers from complex high throughput data. [Toxicol Lett. 2005 Apr 30 (e-pub ahead of print)]: Discusses the application of "signature networks" in comparing the effect of differential drug treatment using 4-hydroxytamoxifen and estrogen on the MCF-7 breast cancer cell line from a previously published study. The authors show that the two compounds can be differentiated by the networks of interacting genes.

Pham T, Satou K, Ho T. Support vector machines for prediction and analysis of Beta and gamma-turns in proteins. [J Bioinform Comput Biol. 2005 Apr;3(2):343-58]: Presents two support vector machine-based methods, called BTSVM and GTSVM, which predict beta-turns and gamma-turns in a protein from its sequence. When compared with other methods, "BTSVM has a superior performance and GTSVM is competitive," according to the authors.

Plewczynski D, Tkacz A, Godzik A, Rychlewski L. A support vector machine approach to the identification of phosphorylation sites. [Cell Mol Biol Lett. 2005;10(1):73-89]: Discusses a bioinformatics tool that can be used to predict the position of phosphorylation sites in proteins based on sequence information using a support vector machine.

Sachs K, Perez O, Pe'er D, Lauffenburger D, Nolan G. Causal Protein-Signaling Networks Derived from Multiparameter Single-Cell Data. [Science. 2005 Apr 22;308(5721):523-9]: Describes a project in which machine learning was used to derive causal influences in cellular signaling networks. The derivation relied on the simultaneous measurement of multiple phosphorylated protein and phospholipid components in thousands of individual primary human immune system cells.

Snyder D, Montelione G. Clustering algorithms for identifying core atom sets and for assessing the precision of protein structure ensembles. [Proteins. 2005 Apr 8; (e-pub ahead of print)]: Discusses a method for identifying a set of core atoms to use in determining superimpositions for root-mean-square deviation calculations in nuclear magnetic resonance-based structural experiments.

Zhang Y, Skolnick J. TM-align: a protein structure alignment algorithm based on the TM-score. [Nucleic Acids Res. 2005 Apr 22;33(7):2302-9]: Describes TM-align, an algorithm to identify the best structural alignment between protein pairs, which combines the TM-score rotation matrix and dynamic programming. The authors used TM-align for an all-against-all structure comparison of 10,515 representative protein chains from the Protein Data Bank, and found 1,996 distinct folds when a TM-score threshold of 0.5 was used. Availability:

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