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Articles 1 - 6 of 6
Full-Text Articles in Life Sciences
Chemical Genomics In Yeast, Charles Brenner
Chemical Genomics In Yeast, Charles Brenner
Dartmouth Scholarship
Four recent 'chemical genomic' studies, using genome-scale collections of yeast gene deletions, have presented complementary approaches to identifying gene-drug and pathway-drug interactions.Many drugs have unknown, controversial or multiple mechanisms of action. Four recent 'chemical genomic' studies, using genome-scale collections of yeast gene deletions that were either arrayed or barcoded, have presented complementary approaches to identifying gene-drug and pathway-drug interactions.
Mixture Models For Assessing Differential Expression In Complex Tissues Using Microarray Data, Debashis Ghosh
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 …
Trials, Tribulations, And Trends In Tumor Modeling In Mice, Joann C. L. Schuh
Trials, Tribulations, And Trends In Tumor Modeling In Mice, Joann C. L. Schuh
Biomedicine and Animal Models in Research Collection
Selection of mouse models of cancer is often based simply on availability of a mouse strain and a known compatible tumor. Frequently this results in use of tumor models long on history but short on homology and quality control. Other factors including genetics, sex, immunological status, method and site of tumor implantation, technical competence, biological activity of the tumor, protocol sequence and timing, and selection of endpoints interact to produce outcomes in tumor models. Common reliance on survival and tumor burden data in a single mouse model often skews expectations towards high remission and cure rates; a finding seldom duplicated …
Trials, Tribulations, And Trends In Tumor Modeling In Mice, Joann C. L. Schuh
Trials, Tribulations, And Trends In Tumor Modeling In Mice, Joann C. L. Schuh
Toxicology and Animal Models in Research Collection
Selection of mouse models of cancer is often based simply on availability of a mouse strain and a known compatible tumor. Frequently this results in use of tumor models long on history but short on homology and quality control. Other factors including genetics, sex, immunological status, method and site of tumor implantation, technical competence, biological activity of the tumor, protocol sequence and timing, and selection of endpoints interact to produce outcomes in tumor models. Common reliance on survival and tumor burden data in a single mouse model often skews expectations towards high remission and cure rates; a finding seldom duplicated …
Identification Of Trace Element-Containing Proteins In Genomic Databases, Vadim N. Gladyshev, Gregory V. Kryukov, Dmitri E. Fomenko, Dolph L. Hatfield
Identification Of Trace Element-Containing Proteins In Genomic Databases, Vadim N. Gladyshev, Gregory V. Kryukov, Dmitri E. Fomenko, Dolph L. Hatfield
Vadim Gladyshev Publications
Development of bioinformatics tools provided researchers with the ability to identify full sets of trace element–containing proteins in organisms for which complete genomic sequences are available. Recently, independent bioinformatics methods were used to identify all, or almost all, genes encoding selenocysteine-containing proteins in human, mouse, and Drosophila genomes, characterizing entire selenoproteomes in these organisms. It also should be possible to search for entire sets of other trace element–associated proteins, such as metal-containing proteins, although methods for their identification are still in development.
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: 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 …