Analytical study of tunneling times in flat histogram Monte Carlo

We present a model for the dynamics in energy space of multicanonical simulation methods that lends itself to a rather complete analytic characterization. The dynamics is completely determined by the density of states. In the \pm J 2D spin glass the transitions between the ground state level and the first excited one control the long time dynamics. We are able to calculate the distribution of tunneling times and relate it to the equilibration time of a starting probability distribution. In this model, and possibly in any model in which entering and exiting regions with low density of states are the slowest processes in the simulations, tunneling time can be much larger (by a factor of O(N)) than the equilibration time of the probability distribution. We find that these features also hold for the energy projection of single spin flip dynamics.Comment: 7 pages, 4 figures, published in Europhysics Letters (2005

Robust Identification of Target Genes and Outliers in Triple-negative Breast Cancer Data

Correct classification of breast cancer sub-types is of high importance as it directly affects the therapeutic options. We focus on triple-negative breast cancer (TNBC) which has the worst prognosis among breast cancer types. Using cutting edge methods from the field of robust statistics, we analyze Breast Invasive Carcinoma (BRCA) transcriptomic data publicly available from The Cancer Genome Atlas (TCGA) data portal. Our analysis identifies statistical outliers that may correspond to misdiagnosed patients. Furthermore, it is illustrated that classical statistical methods may fail in the presence of these outliers, prompting the need for robust statistics. Using robust sparse logistic regression we obtain 36 relevant genes, of which ca. 60\% have been previously reported as biologically relevant to TNBC, reinforcing the validity of the method. The remaining 14 genes identified are new potential biomarkers for TNBC. Out of these, JAM3, SFT2D2 and PAPSS1 were previously associated to breast tumors or other types of cancer. The relevance of these genes is confirmed by the new DetectDeviatingCells (DDC) outlier detection technique. A comparison of gene networks on the selected genes showed significant differences between TNBC and non-TNBC data. The individual role of FOXA1 in TNBC and non-TNBC, and the strong FOXA1-AGR2 connection in TNBC stand out. Not only will our results contribute to the breast cancer/TNBC understanding and ultimately its management, they also show that robust regression and outlier detection constitute key strategies to cope with high-dimensional clinical data such as omics data

Bounds on the electromagnetic interactions of excited spin-3/2 leptons

We discuss possible deviations from QED produced by a virtual excited spin-3/2 lepton in the reaction $e^+e^- \longrightarrow 2\gamma$. Data recorded by the OPAL Collaboration at a c.m. energy $\sqrt{s} = 183 GeV$ are used to establish bounds on the nonstandard-lepton mass and coupling strengths.Comment: Latex, 5 pages, 7 ps figures. To be published in Phys. Rev.