Literature DB >> 12209140

Treasures and traps in genome-wide data sets: case examples from yeast.

Björn Grünenfelder1, Elizabeth A Winzeler.   

Abstract

Since the publication of the Saccharomyces cerevisiae genome sequence, much effort has been dedicated to developing high-throughput techniques to generate comprehensive information about the function and dynamics of all genes in this yeast's genome. These techniques have generated data sets that typically contain large amounts of reliable and valuable biological information. Nevertheless, there are also uncertainties that are associated with such large-scale studies, which we discuss in this review. These uncertainties increase with the complexity of the organism under study. On the basis of the results from yeast, we should learn much from human and mouse genomic data sets. However, as with yeast data sets, they might also contain misleading results.

Entities:  

Mesh:

Year:  2002        PMID: 12209140     DOI: 10.1038/nrg886

Source DB:  PubMed          Journal:  Nat Rev Genet        ISSN: 1471-0056            Impact factor:   53.242


  23 in total

1.  Genetic diversity in yeast assessed with whole-genome oligonucleotide arrays.

Authors:  Elizabeth A Winzeler; Cristian I Castillo-Davis; Guy Oshiro; David Liang; Daniel R Richards; Yingyao Zhou; Daniel L Hartl
Journal:  Genetics       Date:  2003-01       Impact factor: 4.562

2.  Predicting protein functions from redundancies in large-scale protein interaction networks.

Authors:  Manoj Pratim Samanta; Shoudan Liang
Journal:  Proc Natl Acad Sci U S A       Date:  2003-10-17       Impact factor: 11.205

3.  Detection of homologous proteins by an intermediate sequence search.

Authors:  Bino John; Andrej Sali
Journal:  Protein Sci       Date:  2004-01       Impact factor: 6.725

4.  Comparative protein structure modeling by iterative alignment, model building and model assessment.

Authors:  Bino John; Andrej Sali
Journal:  Nucleic Acids Res       Date:  2003-07-15       Impact factor: 16.971

Review 5.  Charting gene regulatory networks: strategies, challenges and perspectives.

Authors:  Gong-Hong Wei; De-Pei Liu; Chih-Chuan Liang
Journal:  Biochem J       Date:  2004-07-01       Impact factor: 3.857

Review 6.  Single-cell and multivariate approaches in genetic perturbation screens.

Authors:  Prisca Liberali; Berend Snijder; Lucas Pelkmans
Journal:  Nat Rev Genet       Date:  2014-12-02       Impact factor: 53.242

7.  Integrated analysis of regulatory and metabolic networks reveals novel regulatory mechanisms in Saccharomyces cerevisiae.

Authors:  Markus J Herrgård; Baek-Seok Lee; Vasiliy Portnoy; Bernhard Ø Palsson
Journal:  Genome Res       Date:  2006-04-10       Impact factor: 9.043

8.  The preference for error-free or error-prone postreplication repair in Saccharomyces cerevisiae exposed to low-dose methyl methanesulfonate is cell cycle dependent.

Authors:  Dongqing Huang; Brian D Piening; Amanda G Paulovich
Journal:  Mol Cell Biol       Date:  2013-02-04       Impact factor: 4.272

9.  Identification of transcribed sequences in Arabidopsis thaliana by using high-resolution genome tiling arrays.

Authors:  Viktor Stolc; Manoj Pratim Samanta; Waraporn Tongprasit; Himanshu Sethi; Shoudan Liang; David C Nelson; Adrian Hegeman; Clark Nelson; David Rancour; Sebastian Bednarek; Eldon L Ulrich; Qin Zhao; Russell L Wrobel; Craig S Newman; Brian G Fox; George N Phillips; John L Markley; Michael R Sussman
Journal:  Proc Natl Acad Sci U S A       Date:  2005-03-08       Impact factor: 11.205

10.  Enhancing interdisciplinary mathematics and biology education: a microarray data analysis course bridging these disciplines.

Authors:  Yolande V Tra; Irene M Evans
Journal:  CBE Life Sci Educ       Date:  2010       Impact factor: 3.325

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.