Institution
Université libre de Bruxelles
Education•Brussels, Belgium•
About: Université libre de Bruxelles is a education organization based out in Brussels, Belgium. It is known for research contribution in the topics: Population & Breast cancer. The organization has 24974 authors who have published 56969 publications receiving 2084303 citations. The organization is also known as: ULB.
Topics: Population, Breast cancer, Context (language use), Receptor, Cancer
Papers published on a yearly basis
Papers
More filters
••
TL;DR: In this paper, two bioassay procedures are proposed for determining biodegradable dissolved organic carbon (BDOC) in waters, which involve sterile filtration of the sample, reinoculation with a natural assemblage of bacteria from the same origin as the sample and incubation for at least 10 days in the dark at 20°C.
373 citations
•
30 Jun 1995TL;DR: This paper presents a meta-analyses of nonlinear behavior in the physical sciences and biology of Dynamical systems with a finite number of degrees of freedom and some typical examples.
Abstract: Preface 1. Nonlinear behavior in the physical sciences and biology: some typical examples 2. Quantitative formulation 3. Dynamical systems with a finite number of degrees of freedom 4. Linear stability analysis of fixed points 5. Nonlinear behavior around fixed points: bifurcation analysis 6. Spatially distributed systems, broken symmetries, pattern formation 7. Chaotic dynamics Appendices References Index.
372 citations
••
TL;DR: In this article, the authors consider Bayesian regression with normal and double-exponential priors as forecasting methods based on large panels of time series and show that these forecasts are highly correlated with principal component forecasts and that they perform equally well for a wide range of prior choices.
372 citations
••
TL;DR: A gene classifier that can predict clinical outcome in tamoxifen-treated ER+ BC patients is developed and other genes and pathways that may elucidate further mechanisms that influence clinical outcome and prediction of response to tamoxIFen are proposed.
Abstract: Estrogen receptor positive (ER+) breast cancers (BC) are heterogeneous with regard to their clinical behavior and response to therapies. The ER is currently the best predictor of response to the anti-estrogen agent tamoxifen, yet up to 30–40% of ER+BC will relapse despite tamoxifen treatment. New prognostic biomarkers and further biological understanding of tamoxifen resistance are required. We used gene expression profiling to develop an outcome-based predictor using a training set of 255 ER+ BC samples from women treated with adjuvant tamoxifen monotherapy. We used clusters of highly correlated genes to develop our predictor to facilitate both signature stability and biological interpretation. Independent validation was performed using 362 tamoxifen-treated ER+ BC samples obtained from multiple institutions and treated with tamoxifen only in the adjuvant and metastatic settings. We developed a gene classifier consisting of 181 genes belonging to 13 biological clusters. In the independent set of adjuvantly-treated samples, it was able to define two distinct prognostic groups (HR 2.01 95%CI: 1.29–3.13; p = 0.002). Six of the 13 gene clusters represented pathways involved in cell cycle and proliferation. In 112 metastatic breast cancer patients treated with tamoxifen, one of the classifier components suggesting a cellular inflammatory mechanism was significantly predictive of response. We have developed a gene classifier that can predict clinical outcome in tamoxifen-treated ER+ BC patients. Whilst our study emphasizes the important role of proliferation genes in prognosis, our approach proposes other genes and pathways that may elucidate further mechanisms that influence clinical outcome and prediction of response to tamoxifen.
372 citations
••
Washington University in St. Louis1, Max Planck Society2, Université libre de Bruxelles3, German Cancer Research Center4, Goethe University Frankfurt5, Université catholique de Louvain6, University of Liège7, John Radcliffe Hospital8, MediGene9, Vrije Universiteit Brussel10, Katholieke Universiteit Leuven11
TL;DR: No correlation was found between G+C content and gene density along the chromosome, and their variations are random, so accurate verification procedures demonstrate that there are less than two errors per 10,000 base pairs in the published sequence.
Abstract: Here we report the sequence of 569,202 base pairs of Saccharomyces cerevisiae chromosome V. Analysis of the sequence revealed a centromere, two telomeres and 271 open reading frames (ORFs) plus 13 tRNAs and four small nuclear RNAs. There are two Ty1 transposable elements, each of which contains an ORF (included in the count of 271). Of the ORFs, 78 (29%) are new, 81 (30%) have potential homologues in the public databases, and 112 (41%) are previously characterized yeast genes.
372 citations
Authors
Showing all 25206 results
Name | H-index | Papers | Citations |
---|---|---|---|
Karl J. Friston | 217 | 1267 | 217169 |
Yi Chen | 217 | 4342 | 293080 |
David Miller | 203 | 2573 | 204840 |
Jing Wang | 184 | 4046 | 202769 |
H. S. Chen | 179 | 2401 | 178529 |
Jie Zhang | 178 | 4857 | 221720 |
Jasvinder A. Singh | 176 | 2382 | 223370 |
D. M. Strom | 176 | 3167 | 194314 |
J. N. Butler | 172 | 2525 | 175561 |
Andrea Bocci | 172 | 2402 | 176461 |
Bradley Cox | 169 | 2150 | 156200 |
Marc Weber | 167 | 2716 | 153502 |
Hongfang Liu | 166 | 2356 | 156290 |
Guenakh Mitselmakher | 165 | 1951 | 164435 |
Yang Yang | 164 | 2704 | 144071 |