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At least 1,603 records · Page 89Linked to original sources
PubMed2004

Drawing phylogenetic trees in LATEX and Microsoft Word.

UNLABELLED: newicktree is a PSTricks-based LATEX package which enables phylogenetic trees described in the Newick format to be drawn directly into LATEX documents. mswordtree is a macro for producing phylogenetic trees using the drawing elements available in Microsoft Word. AVAILABILITY: Both programs are available free from the John Innes Centre's Bioinformatics Research Group website at http://jic-bioinfo.bbsrc.ac.uk/bioinformatics-research/software/index.html. SUPPLEMENTARY INFORMATION: A full user-guide for newicktree and installation and usage instructions for mswordtree and available at http://jic-bioinfo.bbsrc.ac.uk/bioinformatics-research/software/index.html

Computer Graphics↗
PubMed2004

Sfixem--graphical sequence feature display in Java.

UNLABELLED: Sfixem is an sequence feature series (SFS) visualization tool implemented in Java. It is designed to visualize data from sequence analysis programs, allowing the user to view multiple sets of computationally generated analysis to assist the analysis process. SFS is used as the data exchange format. AVAILABILITY: Sfixem is available for direct usage or download for local usage at http://sfixem.cgb.ki.se. A protein sequence analysis workbench using Sfixem is available at http://sfinx.cgb.ki.se.

Algorithms↗
PubMed2004

ProteoMix: an integrated and flexible system for interactively analyzing large numbers of protein sequences.

UNLABELLED: ProteoMix is a suite of JAVA programs for identifying, annotating and predicting regions of interest in large sets of amino acid sequences, according to systematic and consistent criteria. It is based on two concepts (1) the integration of results from different sequence analysis tools increases the prediction reliability; and (2) the integration protocol is critical and needs to be easily adaptable in a case-by-case manner. ProteoMix was designed to analyze simultaneously multiple protein sequences using several bioinformatics tools, merge the results of the analyses using logical functions and display them on an integrated viewer. In addition, new sequences can be added seamlessly to an analysis performed on an initial set of sequences. ProteoMix has a modular design, and bioinformatics tools are run on remote servers accessed using the Internet Simple Object Access Protocol (SOAP), ensuring the swift implementation of additional tools. ProteoMix has a user-friendly interactive graphical user interface environment and runs on PCs with Microsoft OS. AVAILABILITY: ProteoMix is freely available for academic users at http://bio.gsc.riken.jp/ProteoMix/

Database Management Systems↗
PubMed2004

GDPC: connecting researchers with multiple integrated data sources.

UNLABELLED: The goal of this project is to simplify access to genomic diversity and phenotype data, thereby encouraging reuse of this data. The Genomic Diversity and Phenotype Connection (GDPC) accomplishes this by retrieving data from one or more data sources and by allowing researchers to analyze integrated data in a standard format. GDPC is written in JAVA and provides (1) data sources available as web services that transfer XML formatted data via the SOAP protocol; (2) a JAVA API for programmatic access to data sources; and (3) a front-end application that allows users to manage data sources, retrieve data based on filters, sort/group data based on property values and save/open the data as XML files. AVAILABILITY: The source code, compiled code, documentation and GDPC Browser are freely available at: www.maizegenetics.net/gdpc/index.html the current release of GDPC is version 1.0, with updated releases planned for the future. Comments are welcome.

Database Management Systems↗
PubMed2004

TigrScan and GlimmerHMM: two open source ab initio eukaryotic gene-finders.

UNLABELLED: We describe two new Generalized Hidden Markov Model implementations for ab initio eukaryotic gene prediction. The C/C++ source code for both is available as open source and is highly reusable due to their modular and extensible architectures. Unlike most of the currently available gene-finders, the programs are re-trainable by the end user. They are also re-configurable and include several types of probabilistic submodels which can be independently combined, such as Maximal Dependence Decomposition trees and interpolated Markov models. Both programs have been used at TIGR for the annotation of the Aspergillus fumigatus and Toxoplasma gondii genomes. AVAILABILITY: Source code and documentation are available under the open source Artistic License from http://www.tigr.org/software/pirate

Algorithms↗
PubMed2004

A statistical framework for the design of microarray experiments and effective detection of differential gene expression.

MOTIVATION: Microarray experiments generate a high data volume. However, often due to financial or experimental considerations, e.g. lack of sample, there is little or no replication of the experiments or hybridizations. These factors combined with the intrinsic variability associated with the measurement of gene expression can result in an unsatisfactory detection rate of differential gene expression (DGE). Our motivation was to provide an easy to use measure of the success rate of DGE detection that could find routine use in the design of microarray experiments or in post-experiment assessment. RESULTS: In this study, we address the problem of both random errors and systematic biases in microarray experimentation. We propose a mathematical model for the measured data in microarray experiments and on the basis of this model present a t-based statistical procedure to determine DGE. We have derived a formula to determine the success rate of DGE detection that takes into account the number of microarrays, the number of genes, the magnitude of DGE, and the variance from biological and technical sources. The formula and look-up tables based on the formula, can be used to assist in the design of microarray experiments. We also propose an ad hoc method for estimating the fraction of non-differentially expressed genes within a set of genes being tested. This will help to increase the power of DGE detection. AVAILABILITY: The functions to calculate the success rate of DGE detection have been implemented as a Java application, which is accessible at http://www.le.ac.uk/mrctox/microarray_lab/Microarray_Softwares/Microarray_Softwares.htm

Algorithms↗
PubMed2004

Java Treeview--extensible visualization of microarray data.

Open source software encourages innovation by allowing users to extend the functionality of existing applications. Treeview is a popular application for the visualization of microarray data, but is closed-source and platform-specific, which limits both its current utility and suitability as a platform for further development. Java Treeview is an open-source, cross-platform rewrite that handles very large datasets well, and supports extensions to the file format that allow the results of additional analysis to be visualized and compared. The combination of a general file format and open source makes Java Treeview an attractive choice for solving a class of visualization problems. An applet version is also available that can be used on any website with no special server-side setup.

Color↗
PubMed2004

CTRD: a fast applet for computing signed translocation distance between genomes.

CTRD is a software for computing translocation distance between genomes. It takes two genomes as its input and tests whether one genome can be transformed into the other. If possible, it computes the translocation distance between two genomes, and gives the translocation operation serial. We adopt the fastest known O(n(2)log n) algorithm. Our contributions include (1) give a necessary and sufficient condition to ensure that one genome can be transformed into the other for translocation operations, and (2) develop a software using the fastest known O(n(2)log n) algorithm.

Algorithms↗
PubMed2004

BioNetGen: software for rule-based modeling of signal transduction based on the interactions of molecular domains.

BioNetGen allows a user to create a computational model that characterizes the dynamics of a signal transduction system, and that accounts comprehensively and precisely for specified enzymatic activities, potential post-translational modifications and interactions of the domains of signaling molecules. The output defines and parameterizes the network of molecular species that can arise during signaling and provides functions that relate model variables to experimental readouts of interest. Models that can be generated are relevant for rational drug discovery, analysis of proteomic data and mechanistic studies of signal transduction.

Algorithms↗
PubMed2004

A software program combining sequence motif searches with keywords for finding repeats containing DNA sequences.

MOTIVATION: One of the most interesting features of genomes (both coding and non-coding regions) is the presence of relatively short tandemly repeated DNA sequences known as tandem repeats (TRs). We developed a new PC-based stand-alone software analysis program, combining sequence motif searches with keywords such as organs, tissues, cell lines or development stages for finding exact, inexact and compound, TRs. Tandem Repeats Analyzer 1.5 (TRA) has several advanced repeat search parameters/options over other repeat finder programs as it does not only accept GenBank, FASTA and expressed sequence tag (EST) sequence files but also does analysis of multifiles with multisequences. Advanced user-defined parameters/options let the researchers use different motif lengths search criteria for varying motif lengths simultaneously. The outputs show statistical results to be evaluated by the user. The discovery of TRs in ESTs could be useful for both gene mapping and association studies and discovering TRs located in coding regions of important genes that are expressed under various conditions of environment, stress, organ, tissue and development stage. RESULTS: In this paper, we demonstrated applications of TRA using 175 899 ESTs sequences for three Arabidopsis spp. downloaded from GenBank. The EST-SSRs/ESTs ratios were found 43.1%, 15.3% and 2.34% in A.lyrata, A.thaliana and A.halleri, respectively. Analysis revealed that organs, tissues and development stages possessed different amounts of repeats and repeat compositions. This indicated that the distribution of TRs among the tissues or organs may not be random differing from the untranscribed repeats found in genomes. AVAILABILITY: The program can be obtained free by anonymous FTP from ftp.akdeniz.edu.tr/Araclar/TRA.

Arabidopsis↗
PubMed2004

CLANS: a Java application for visualizing protein families based on pairwise similarity.

SUMMARY: The main source of hypotheses on the structure and function of new proteins is their homology to proteins with known properties. Homologous relationships are typically established through sequence similarity searches, multiple alignments and phylogenetic reconstruction. In cases where the number of potential relationships is large, for example in P-loop NTPases with many thousands of members, alignments and phylogenies become computationally demanding, accumulate errors and lose resolution. In search of a better way to analyze relationships in large sequence datasets we have developed a Java application, CLANS (CLuster ANalysis of Sequences), which uses a version of the Fruchterman-Reingold graph layout algorithm to visualize pairwise sequence similarities in either two-dimensional or three-dimensional space. AVAILABILITY: CLANS can be downloaded at http://protevo.eb.tuebingen.mpg.de/download.

Algorithms↗
PubMed2004

Haploview: analysis and visualization of LD and haplotype maps.

UNLABELLED: Research over the last few years has revealed significant haplotype structure in the human genome. The characterization of these patterns, particularly in the context of medical genetic association studies, is becoming a routine research activity. Haploview is a software package that provides computation of linkage disequilibrium statistics and population haplotype patterns from primary genotype data in a visually appealing and interactive interface. AVAILABILITY: http://www.broad.mit.edu/mpg/haploview/ CONTACT: jcbarret@broad.mit.edu

Algorithms↗
PubMed2004

Modular, scriptable and automated analysis tools for high-throughput peptide mass fingerprinting.

UNLABELLED: A set of new algorithms and software tools for automatic protein identification using peptide mass fingerprinting is presented. The software is automatic, fast and modular to suit different laboratory needs, and it can be operated either via a Java user interface or called from within scripts. The software modules do peak extraction, peak filtering and protein database matching, and communicate via XML. Individual modules can therefore easily be replaced with other software if desired, and all intermediate results are available to the user. The algorithms are designed to operate without human intervention and contain several novel approaches. The performance and capabilities of the software is illustrated on spectra from different mass spectrometer manufacturers, and the factors influencing successful identification are discussed and quantified. MOTIVATION: Protein identification with mass spectrometric methods is a key step in modern proteomics studies. Some tools are available today for doing different steps in the analysis. Only a few commercial systems integrate all the steps in the analysis, often for only one vendor's hardware, and the details of these systems are not public. RESULTS: A complete system for doing protein identification with peptide mass fingerprints is presented, including everything from peak picking to matching the database protein. The details of the different algorithms are disclosed so that academic researchers can have full control of their tools. AVAILABILITY: The described software tools are available from the Halmstad University website www.hh.se/staff/bioinf/ SUPPLEMENTARY INFORMATION: Details of the algorithms are described in supporting information available from the Halmstad University website www.hh.se/staff/bioinf/

Algorithms↗
PubMed2004

Microarray data mining with visual programming.

UNLABELLED: Visual programming offers an intuitive means of combining known analysis and visualization methods into powerful applications. The system presented here enables users who are not programmers to manage microarray and genomic data flow and to customize their analyses by combining common data analysis tools to fit their needs. AVAILABILITY: http://www.ailab.si/supp/bi-visprog SUPPLEMENTARY INFORMATION: http://www.ailab.si/supp/bi-visprog.

Chromosome Mapping↗
PubMed2004

Simulating genetic networks made easy: network construction with simple building blocks.

UNLABELLED: We present SIM-plex, a genetic network simulator with a very intuitive interface in which a user can easily specify interactions as simple 'if-then' statements. The simulator is based on the mathematical model of Piecewise Linear Differential Equations (PLDEs). With PLDEs, genetic interactions are approximated as acting in a switch-like manner. AVAILABILITY: The Java program, examples and a tutorial are available at http://www.psb.ugent.be/cbd/ CONTACT: {stcru,makui}@psb.ugent.be

Algorithms↗
PubMed2004

RALEE--RNA ALignment editor in Emacs.

UNLABELLED: Production of high quality multiple sequence alignments of structured RNAs relies on an iterative combination of manual editing and structure prediction. An essential feature of an RNA alignment editor is the facility to mark-up the alignment based on how it matches a given secondary structure prediction, but few available alignment editors offer such a feature. The RALEE (RNA ALignment Editor in Emacs) tool provides a simple environment for RNA multiple sequence alignment editing, including structure-specific colour schemes, utilizing helper applications for structure prediction and many more conventional editing functions. This is accomplished by extending the commonly used text editor, Emacs, which is available for Linux, most UNIX systems, Windows and Mac OS. AVAILABILITY: The ELISP source code for RALEE is freely available from http://www.sanger.ac.uk/Users/sgj/ralee/ along with documentation and examples. CONTACT: sgj@sanger.ac.uk

Algorithms↗
PubMed2004

TraitMap: an XML-based genetic-map database combining multigenic loci and biomolecular networks.

MOTIVATION: Most ordinary traits are well described by multiple measurable parameters. Thus, in the course of elucidating the genes responsible for a given trait, it is necessary to conduct and integrate the genetic mapping of each parameter. However, the integration of multiple mapping results from different publications is prevented by the fact that they are conventionally published and accumulated in printed forms or graphics which are difficult for computers to reuse for further analyses. RESULTS: We have defined an XML-based schema as a container of genetic mapping results, and created a database named TraitMap containing curator-checked data records based on published papers of mapping results in Homosapiens, Mus musculus, and Arabidopsis thaliana. TraitMap is the first database of mapping charts in genetics, and is integrated in a web-based retrieval framework: termed Genome <--> Phenome Superhighway (GPS) system, where it is possible to combine and visualize multiple mapping records in a two-dimensional display. Since most traits are regulated by multiple genes, the system associates every combination of genetic loci to biomolecular networks, and thus helps us to estimate molecular-level candidate networks responsible for a given trait. It is demonstrated that a combined analysis of two diabetes-related traits (susceptibility to insulin resistance and non-HDL cholesterol level) suggests that molecular-level relationships such as the interaction among leptin receptor (Lepr), peroxisome proliferators-activated receptor-gamma (Pparg) and insulin receptor substrate 1 (Irs1), are candidate causal networks affecting the traits in a multigenic manner. AVAILABILITY: TraitMap database and GPS are accessible at http://omicspace.riken.jp/gps/

Chromosome Mapping↗