Breast Cancer Research

official impact factor 5.79

Open Access Highly Access

A comprehensive analysis of prognostic signatures reveals the high predictive capacity of the Proliferation, Immune response and RNA splicing modules in breast cancer

Fabien Reyal, Martin H van Vliet, Nicola J Armstrong, Hugo M Horlings, Karin E de Visser, Marlen Kok, Andrew E Teschendorff, Stella Mook, Laura van 't Veer, Carlos Caldas, Remy J Salmon, Marc J Vijver and Lodewyk FA Wessels*

Breast Cancer Research 2008, 10:R93 doi:10.1186/bcr2192

Accesses  

  • Last 30 days: 141 accesses
  • Last year: 1100 accesses
  • All time: 5746 accesses

Cited by

BioMed Central: 5 citations

Research article   Open Access Highly Accessed

A clinically relevant gene signature in triple negative and basal-like breast cancer

Achim Rody, Thomas Karn, Cornelia Liedtke, Lajos Pusztai, Eugen Ruckhaeberle, Lars Hanker, Regine Gaetje, Christine Solbach, Andre Ahr, Dirk Metzler, Marcus Schmidt, Volkmar Müller, Uwe Holtrich, Manfred Kaufmann Breast Cancer Research 2011, 13:R97 (6 October 2011)

Section introduction   Free

Molecular profiling currently offers no more than tumour morphology and basic immunohistochemistry

Britta Weigelt, Jorge S Reis-Filho Breast Cancer Research 2010, 12(Suppl 4):S5 (20 December 2010)

Research article   Open Access Highly Accessed

Genomic subtypes of breast cancer identified by array-comparative genomic hybridization display distinct molecular and clinical characteristics

Göran Jönsson, Johan Staaf, Johan Vallon-Christersson, Markus Ringnér, Karolina Holm, Cecilia Hegardt, Haukur Gunnarsson, Rainer Fagerholm, Carina Strand, Bjarni A Agnarsson, Outi Kilpivaara, Lena Luts, Päivi Heikkilä, Kristiina Aittomäki, Carl Blomqvist, Niklas Loman, Per Malmström, Håkan Olsson, Oskar Th Johannsson, Adalgeir Arason, Heli Nevanlinna, Rosa B Barkardottir, Åke Borg Breast Cancer Research 2010, 12:R42 (24 June 2010)

The identification of six subtypes of breast cancer - differing in biology, genomic alterations and patient outcome - may prove useful for understanding tumor development and for prognostic and treatment prediction purposes.

Research article   Open Access Highly Accessed

Prediction of breast cancer prognosis using gene set statistics provides signature stability and biological context

Gad Abraham, Adam Kowalczyk, Sherene Loi, Izhak Haviv, Justin Zobel BMC Bioinformatics 2010, 11:277 (25 May 2010)

Research article   Open Access Highly Accessed

A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

Herman MJ Sontrop, Perry D Moerland, René van den Ham, Marcel JT Reinders, Wim FJ Verhaegh BMC Bioinformatics 2009, 10:389 (26 November 2009)