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This essay highlights several examples of using mathematics and statistics to analyse problems involving Big Data. More often than not, mathematics is essential for extracting usable information from the data. However, it usually remains hidden under the bonnet, and the general public seems to take it for granted. With this paper Alessandro Di Bucchianico, Laura Iapichino, Nelly Litvak, Frank van der Meulen and Ron Wehrens want to show some essential contributions of the fields of mathematics to Big Data using successful real-life examples.

Supplementary File: Calcium Imaging of GPCR Activation Using Arrays of Reverse Transfected HEK293 Cells in a Microfluidic System

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This paper reviews literature from the past 5 years in the field of molecular chemometrics, which applies modeling and data analysis to molecular data. It discusses advances and standing challenges in the fields of molecular representation, similarity and diversity analysis, quantitative structure-activity and structure-property relationship modeling, and library searching.

The Levenberg-Marquardt algorithm is a flexible iterative procedure used to solve non-linear least squares problems. In this work we study how a class of possible adaptations of this procedure can be used to solve maximum likelihood problems when the underlying distributions are in the exponential family. We formally demonstrate a local convergence property and we discuss a possible implementation of the penalization involved in this class of algorithms. Applications to real and simulated compositional data show the stability and efficiency of this approach.

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Contains fulltext : 290576.pdf (Publisher’s version ) (Open Access) useR! 2006

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Contains fulltext : 83245.pdf (Publisher’s version ) (Open Access) Radboud Universiteit Nijmegen, 10 februari 2011 Promotor : Buydens, L.M.C. Co-promotores : Wehrens, Ron, Bauerschmidt, S. 164 p.

Contains fulltext : 72267.pdf (author's version ) (Open Access) RU Radboud Universiteit Nijmegen, 02 april 2008 Promotores : Buydens, L.M.C., Murray-Rust, P. Co-promotor : Wehrens, Ron