✦ LIBER ✦

QUADRA @ Duke: A Platform For Reproducible Analysis Of Genome-Scale Data

✍ Scribed by J. Lucas; E.S. Huang

Book ID: 116707426
Publisher: Elsevier Science
Year: 2011
Tongue: English
Weight: 51 KB
Volume: 165
Category: Article
ISSN: 0022-4804
DOI: 10.1016/j.jss.2010.11.818

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Traitmill™: a functional genomics platfo

Traitmill™: a functional genomics platform for the phenotypic analysis of cereals

✍ Reuzeau, Christophe; Frankard, Valerie; Hatzfeld, Yves; Sanz, Anabel; Van Camp, 📂 Article 📅 2006 🏛 Cambridge University Press 🌐 English ⚖ 865 KB

2160 POSTER Coping With the Data Deluge:

2160 POSTER Coping With the Data Deluge: the Quartz Software Platform for the Management, Visualisation and Analysis of Large Scale, Multimodal Genomic and Bioimage Data

✍ A. Pitiot; F. Morvillier 📂 Article 📅 2011 🏛 Elsevier Science 🌐 English ⚖ 43 KB

StratomeX: Visual Analysis of Large-Scal

StratomeX: Visual Analysis of Large-Scale Heterogeneous Genomics Data for Cancer Subtype Characterization

✍ A. Lex; M. Streit; H.-J. Schulz; C. Partl; D. Schmalstieg; P.J. Park; N. Gehlenb 📂 Article 📅 2012 🏛 John Wiley and Sons 🌐 English ⚖ 377 KB

Gene expression analysis ofEscherichia c

Gene expression analysis ofEscherichia coligrown in miniaturized bioreactor platforms for high-throughput analysis of growth and genomic data

✍ Paolo Boccazzi; Andrea Zanzotto; Nicolas Szita; Sanchita Bhattacharya; Klavs F. 📂 Article 📅 2005 🏛 Springer 🌐 English ⚖ 309 KB

Analysis of Full-Scale Wind Forces on a

Analysis of Full-Scale Wind Forces on a Semisubmersible Platform Using Operator's Data

✍ Boonstra, H. 📂 Article 📅 1980 🏛 Society of Petroleum Engineers 🌐 English ⚖ 396 KB

Meta-analysis of heterogeneous data sour

Meta-analysis of heterogeneous data sources for genome-scale identification of risk genes in complex phenotypes

✍ Tune H. Pers; Niclas Tue Hansen; Kasper Lage; Pernille Koefoed; Piotr Dworzynski 📂 Article 📅 2011 🏛 John Wiley and Sons 🌐 English ⚖ 454 KB 👁 2 views

Meta-analyses of large-scale association studies typically proceed solely within one data type and do not exploit the potential complementarities in other sources of molecular evidence. Here, we present an approach to combine heterogeneous data from genome-wide association (GWA) studies, protein-pro