BMC Genomics

official impact factor 4.21
Search for
Advanced search
BMC Genomics
Tools
Share this article
Open Access

Deep analysis of cellular transcriptomes – LongSAGE versus classic MPSS

Lawrence Hene†, Vattipally B Sreenu†, Mai T Vuong, S Hussain I Abidi, Julian K Sutton, Sarah L Rowland-Jones, Simon J Davis* and Edward J Evans*

BMC Genomics 2007, 8:333 doi:10.1186/1471-2164-8-333

Accesses  

  • Last 30 days: 32 accesses
  • Last 365 days: 430 accesses
  • All time: 3375 accesses

Cited by

BioMed Central: 3 citations

Review   Free Highly Accessed

Linking genes to diseases: it's all in the data

Nicki Tiffin, Miguel A Andrade-Navarro, Carolina Perez-Iratxeta Genome Med 2009, 1:77 (7 August 2009)

Abstract | Full text | PDF | PubMed | Cited on BioMed Central |  Editor’s summary

Computational approaches to disease-gene associations, especially those that use phenotype ontologies, can help to prioritize the most likely candidate genes.

Research article   Open Access Highly Accessed

Measuring differential gene expression by short read sequencing: quantitative comparison to 2-channel gene expression microarrays

Joshua S Bloom, Zia Khan, Leonid Kruglyak, Mona Singh, Amy A Caudy BMC Genomics 2009, 10:221 (12 May 2009)

Abstract | Full text | PDF | PubMed | Cited on BioMed Central | 1 comment

Methodology article   Open Access Highly Accessed

A combination of LongSAGE with Solexa sequencing is well suited to explore the depth and the complexity of transcriptome

Lucie Hanriot, Céline Keime, Nadine Gay, Claudine Faure, Carole Dossat, Patrick Wincker, Céline Scoté-Blachon, Christelle Peyron, Olivier Gandrillon BMC Genomics 2008, 9:418 (16 September 2008)

Abstract | Full text | PDF | PubMed | Cited on BioMed Central

Google Scholar: View citations

ISI Web of Science: View citations

PubMed Central: View citations