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Concept

Biostatistique

Publications associées (12)

Finding a vocation for validation: taking proteomics beyond association and location

Yimon Aye, Jinmin Liu

First established in the seventies, proteomics, chemoproteomics, and most recently, spatial/proximity-proteomics technologies have empowered researchers with new capabilities to illuminate cellular communication networks that govern sophisticated decision- ...

ROYAL SOC CHEMISTRY2022

Differentiation between benign and malignant vertebral compression fractures using qualitative and quantitative analysis of a single fast spin echo T2-weighted Dixon sequence

Tom Hilbert

Objectives To determine and compare the qualitative and quantitative diagnostic performance of a single sagittal fast spin echo (FSE) T2-weighted Dixon sequence in differentiating benign and malignant vertebral compression fractures (VCF), using multiple r ...

SPRINGER2021

Real-World Gait Bout Detection Using a Wrist Sensor: An Unsupervised Real-Life Validation

Kamiar Aminian, Anisoara Ionescu, Hooman Dejnabadi, Abolfazl Soltani

Gait bouts (GB), as a prominent indication of physical activity, contain valuable fundamental information closely associated with human & x2019;s health status. Therefore, objective assessment of the GB (e.g. detection, spatio-temporal analysis) during dai ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Large-scale variational inference for Bayesian joint regression modelling of high-dimensional genetic data

Hélène Ruffieux

Genetic association studies have become increasingly important in understanding the molecular bases of complex human traits. The specific analysis of intermediate molecular traits, via quantitative trait locus (QTL) studies, has recently received much atte ...

EPFL2019

Approximate maximum likelihood estimation for population genetic inference

In many population genetic problems, parameter estimation is obstructed by an intractable likelihood function. Therefore, approximate estimation methods have been developed, and with growing computational power, sampling-based methods became popular. Howev ...

De Gruyter2017

Efficient inference for genetic association studies with multiple outcomes

Anthony Christopher Davison, Jörg Hager, Hélène Ruffieux

Combined inference for heterogeneous high-dimensional data is critical in modern biology, where clinical and various kinds of molecular data may be available from a single study. Classical genetic association studies regress a single clinical outcome on ma ...

Oxford University Press2017

Detecting and Quantifying Changing Selection Intensities from Time-Sampled Polymorphism Data

Jeffrey David Jensen, Matthieu Foll, Stefan Jean Laurent, Sebastian Matuszewski, Hyunjin Shim

During his well-known debate with Fisher regarding the phenotypic dataset of Panaxia dominula, Wright suggested fluctuating selection as a potential explanation for the observed change in allele frequencies. This model has since been invoked in a number of ...

Genetics Society of America2016

Meta-analysis of incomplete microarray studies

Anthony Christopher Davison, Darlene Goldstein, Alix Corinne Josiane Colette Zollinger

Meta-analysis of microarray studies to produce an overall gene list is relatively straightforward when complete data are available. When some studies lack information, for example, having only a ranked list of genes instead of complete primary data, it is ...

Oxford University Press2015

Mapping molecular statistics with balanced super-resolution optical fluctuation imaging (bSOFI)

Theo Lasser, Marcel Leutenegger, Noelia Laura Bocchio, Claudio Dellagiacoma, Corinne Berclaz

Super-resolution optical fluctuation imaging (SOFI) achieves 3D super-resolution by computing temporal cumulants or spatio-temporal cross-cumulants of stochastically blinking fluorophores. In contrast to localization microscopy, SOFI is compatible with wea ...

2012

Constrained expectation-maximization algorithm for stochastic inertial error modeling: study of feasibility

Jan Skaloud, Stéphane Guerrier, Yannick Stebler

Stochastic modeling is a challenging task for low-cost sensors whose errors can have complex spectral structures. This makes the tuning process of the INS/GNSS Kalman filter often sensitive and difficult. For example, first-order Gauss–Markov processes are ...

IOP Publishing2011

Reliable confidence intervals in quantitative genetics: Narrow-sense heritability

Anthony Christopher Davison

Many quantitative genetic statistics are functions of variance components, for which a large number of replicates is needed for precise estimates and reliable measures of uncertainty, on which sound interpretation depends. Moreover, in large experiments th ...

2007

What can we learn by transposing the calibration – validation paradigm into a multi-objective context ?

André Musy, Bettina Schaefli

The classical single-objective model calibration and validation approach using different time periods for each of them is known not to be sufficient to judge whether the model predictions are consistent or to detect model structural deficiencies. It is how ...

2005