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Bioinformatics

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Articles 391 - 400 of 400

Full-Text Articles in Computational Biology

Reproducible Research: A Bioinformatics Case Study, Robert Gentleman May 2004

Reproducible Research: A Bioinformatics Case Study, Robert Gentleman

Bioconductor Project Working Papers

While scientific research and the methodologies involved have gone through substantial technological evolution the technology involved in the publication of the results of these endeavors has remained relatively stagnant. Publication is largely done in the same manner today as it was fifty years ago. Many journals have adopted electronic formats, however, their orientation and style is little different from a printed document. The documents tend to be static and take little advantage of computational resources that might be available. Recent work, Gentleman and Temple Lang (2004), suggests a methodology and basic infrastructure that can be used to publish documents in …

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Classification Using Generalized Partial Least Squares, Beiying Ding, Robert Gentleman May 2004

Classification Using Generalized Partial Least Squares, Beiying Ding, Robert Gentleman

Bioconductor Project Working Papers

The advances in computational biology have made simultaneous monitoring of thousands of features possible. The high throughput technologies not only bring about a much richer information context in which to study various aspects of gene functions but they also present challenge of analyzing data with large number of covariates and few samples. As an integral part of machine learning, classification of samples into two or more categories is almost always of interest to scientists. In this paper, we address the question of classification in this setting by extending partial least squares (PLS), a popular dimension reduction tool in chemometrics, in …

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Mixture Models For Assessing Differential Expression In Complex Tissues Using Microarray Data, Debashis Ghosh Feb 2004

Mixture Models For Assessing Differential Expression In Complex Tissues Using Microarray Data, Debashis Ghosh

The University of Michigan Department of Biostatistics Working Paper Series

The use of DNA microarrays has become quite popular in many scientific and medical disciplines, such as in cancer research. One common goal of these studies is to determine which genes are differentially expressed between cancer and healthy tissue, or more generally, between two experimental conditions. A major complication in the molecular profiling of tumors using gene expression data is that the data represent a combination of tumor and normal cells. Much of the methodology developed for assessing differential expression with microarray data has assumed that tissue samples are homogeneous. In this article, we outline a general framework for determining …

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Bioconductor: Open Software Development For Computational Biology And Bioinformatics, Robert C. Gentleman, Vincent J. Carey, Douglas J. Bates, Benjamin M. Bolstad, Marcel Dettling, Sandrine Dudoit, Byron Ellis, Laurent Gautier, Yongchao Ge, Jeff Gentry, Kurt Hornik, Torsten Hothorn, Wolfgang Huber, Stefano Iacus, Rafael Irizarry, Friedrich Leisch, Cheng Li, Martin Maechler, Anthony J. Rossini, Guenther Sawitzki, Colin Smith, Gordon K. Smyth, Luke Tierney, Yee Hwa Yang, Jianhua Zhang Jan 2004

Bioconductor: Open Software Development For Computational Biology And Bioinformatics, Robert C. Gentleman, Vincent J. Carey, Douglas J. Bates, Benjamin M. Bolstad, Marcel Dettling, Sandrine Dudoit, Byron Ellis, Laurent Gautier, Yongchao Ge, Jeff Gentry, Kurt Hornik, Torsten Hothorn, Wolfgang Huber, Stefano Iacus, Rafael Irizarry, Friedrich Leisch, Cheng Li, Martin Maechler, Anthony J. Rossini, Guenther Sawitzki, Colin Smith, Gordon K. Smyth, Luke Tierney, Yee Hwa Yang, Jianhua Zhang

Bioconductor Project Working Papers

The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. We detail some of the design decisions, software paradigms and operational strategies that have allowed a small number of researchers to provide a wide variety of innovative, extensible, software solutions in a relatively short time. The use of an object oriented programming paradigm, the adoption and development of a software package system, designing by contract, distributed development and collaboration with other projects are elements of this project's success. Individually, each of these concepts are useful and important but when combined they have …

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Cluster Stability Scores For Microarray Data In Cancer Studies, Mark Smolkin, Debashis Ghosh Jun 2003

Cluster Stability Scores For Microarray Data In Cancer Studies, Mark Smolkin, Debashis Ghosh

The University of Michigan Department of Biostatistics Working Paper Series

A potential benefit of profiling of tissue samples using microarrays is the generation of molecular fingerprints that will define subtypes of disease. Hierarchical clustering has been the primary analytical tool used to define disease subtypes from microarray experiments in cancer settings. Assessing cluster reliability poses a major complication in analyzing output from these procedures. While much work has been done on assessing the global question of number of clusters in a dataset, relatively little research exists on assessing stability of individual clusters. A potential benefit of profiling of tissue samples using microarrays is the generation of molecular fingerprints that will …

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Simple Parallel Statistical Computing In R, Anthony Rossini, Luke Tierney, Na Li Mar 2003

Simple Parallel Statistical Computing In R, Anthony Rossini, Luke Tierney, Na Li

UW Biostatistics Working Paper Series

Theoretically, many modern statistical procedures are trivial to parallelize. However, practical deployment of a parallelized implementation which is robust and reliably runs on different computational cluster configurations and environments is far from trivial. We present a framework for the R statistical computing language that provides a simple yet powerful programming interface to a computational cluster. This interface allows the development of R functions that distribute independent computations across the nodes of the computational cluster. The resulting framework allows statisticians to obtain significant speed-ups for some computations at little additional development cost. The particular implementation can be deployed in heterogeneous computing …

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Literate Statistical Practice, Anthony Rossini, Friedrich Leisch Mar 2003

Literate Statistical Practice, Anthony Rossini, Friedrich Leisch

UW Biostatistics Working Paper Series

Literate Statistical Practice (LSP, Rossini, 2001) describes an approach for creating self-documenting statistical results. It applies literate programming (Knuth, 1992) and related techniques in a natural fashion to the practice of statistics. In particular, documentation, specification, and descriptions of results are written concurrently with writing and evaluation of statistical programs. We discuss how and where LSP can be integrated into practice and illustrate this with an example derived from an actual statistical consulting project. The approach is simplified through the use of a comprehensive, open source toolset incorporating Noweb, Emacs Speaks Statistics (ESS), Sweave (Ramsey, 1994; Rossini, et al, 2002; …

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A Neural Network Method For Protein Classification, Arie D. Jones Dec 2002

A Neural Network Method For Protein Classification, Arie D. Jones

All-Inclusive List of Electronic Theses and Dissertations

The investigation detailed in this paper attempts to utilize a Leaming Vector Quantization network in order to classify a set of mitochondrial proteins based upon their amino acid sequence. The Learning Vector Quantization network uses a nearest neighbor approach to classification. Input vectors are fed into the network, which produces output vectors. Those output vectors are then matched by means of a distance bias to a corresponding classification vector. The learning and test sets consisted of thirteen similar mitochodrial proteins from seventy-two different species. This provided a pool of over nine hundred proteins to use. Half of the species were …

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A Broad Survey Of Web-Based Bioinformatics Research And Data Mining Using Blast, Wooi Keng Tan Jan 2002

A Broad Survey Of Web-Based Bioinformatics Research And Data Mining Using Blast, Wooi Keng Tan

Student Works (2000-2009)

This research covers a broad survey of bioinformatics resources and data mining tools available on the web. Bioinformatics is the field of science in which biology, computer science, and information technology merge to form a single discipline. The three main public domain bioinformatics resources covered here includes NCBI (National Center for Biotechnology Information), EBI (European Bioinformatics Institute) and Genome Net (Japanese Bioinfom1atics Servers). The technology now has enabled researchers to gain global access to these databases and software. These databases and tools will provide the research community with a wealth of information and computing tools followed with the vast data …

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Statistical Inference For Simultaneous Clustering Of Gene Expression Data, Katherine S. Pollard, Mark J. Van Der Laan Jul 2001

Statistical Inference For Simultaneous Clustering Of Gene Expression Data, Katherine S. Pollard, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Current methods for analysis of gene expression data are mostly based on clustering and classification of either genes or samples. We offer support for the idea that more complex patterns can be identified in the data if genes and samples are considered simultaneously. We formalize the approach and propose a statistical framework for two-way clustering. A simultaneous clustering parameter is defined as a function of the true data generating distribution, and an estimate is obtained by applying this function to the empirical distribution. We illustrate that a wide range of clustering procedures, including generalized hierarchical methods, can be defined as …

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