Chen-Yi Gao, Hai-Jun Zhou1,3,5∗, and Erik Aurell2,4† Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, Beijing 100190, China Department of Computational Biology, KTH-Royal Institute of Technology, SE-10044 Stockholm, Sweden School of Physical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China Depts of Applied Physics an...

We provided a cross-tissue comparative analysis of between-subtype molecular commonality for ovarian cancer, breast cancer, hepatocellular carcinoma, glioma, lung squamous carcinoma and nasopharyngeal carcinoma. Our analysis showed that molecular subtypes with similar phenotype or similar clinical outcome could be correlated by their transcriptional profile and pathway profile. Pathway dysregul...

M.A. Lisa, for the E895 Collaboration N.N. Ajitanand, J. Alexander, D. Best, P. Brady, T. Case, B. Caskey, D. Cebra, J. Chance, I. Chemakin, P. Chung, V. Cianciolo, B. Cole, K. Crowe, A. Das, J. Draper, S. Gushue, M. Gilkes, M. Heffner, H. Hiejima, A. Hirsch, E. Hjort, L. Huo, M. Justice, M. Kaplan, D. Keane, J. Kintner, D. Krofcheck, R. Lacey, J. Lauret, E. LeBras, H. Liu, Y. Liu, R. McGrath, ...

J. Dj. Golić applied linear sequential circuit approximation (LSCA) method to analyze the summation generator with an arbitrary number of inputs. He conjectured that he could obtain all pairs of mutually correlated input and output linear functions with the maximum possible absolute value of the correlation coefficient by this method, but he did not give any proof. By using Walsh Transformation...

We present the methodology for correlation analysis of chemical bond operators (CACB) on ab initio wave functions. In CACB the wave function is analyzed in a hierarchy of quantities (charge, bond order, bondbond correlation), where each quantity is the expectation value of an operator related to the statistical covariance of the previous quantity. CACB does not require any preconceived notion o...

Compositional data need a special treatment prior to correlation analysis. In this paper we argue why standard transformations for compositional data are not suitable for computing correlations, and why the use of raw or log-transformed data is neither meaningful. As a solution, a procedure based on balances is outlined, leading to sensible correlation measures. The construction of the balances...

In generalized canonical correlation analysis several sets of variables are analyzed simultaneously. This makes the method suited for the analysis of various types of data. For example, in marketing research, subjects may be asked to rate a set of objects on a set of attributes. For each individual, a data matrix can then be constructed where the objects are represented row-wise and the attribu...

We introduce in this paper a technique in which we apply correlation analysis using only one execution power curve during an exponentiation to recover the whole secret exponent manipulated by the chip. As in the Big Mac attack from Walter, longer keys may facilitate this analysis and success will depend on the arithmetic coprocessor characteristics. We present the theory of the attack with some...

Partial canonical correlation analysis (partial CCA) is a statistical method that estimates a pair of linear projections onto a low dimensional space, where the correlation between two multidimensional variables is maximized after eliminating the influence of a third variable. Partial CCA is known to be closely related to a causality measure between two time series. However, partial CCA require...