Zobrazeno 1 - 10
of 337
pro vyhledávání: '"Bertrand, Frédéric"'
Publikováno v:
Chion M, Carapito C, Bertrand F (2022) Accounting for multiple imputation-induced variability for differential analysis in mass spectrometry-based label-free quantitative proteomics. PLoS Comput Biol 18(8): e1010420
Imputing missing values is common practice in label-free quantitative proteomics. Imputation aims at replacing a missing value with a user-defined one. However, the imputation itself may not be optimally considered downstream of the imputation proces
Externí odkaz:
http://arxiv.org/abs/2108.07086
Publikováno v:
In Artificial Intelligence In Medicine January 2024 147
Publikováno v:
In Annals of Nuclear Energy 15 June 2023 186
Publikováno v:
Statistical Applications in Genetics and Molecular Biology, 2019
Partial least squares regression---or PLS---is a multivariate method in which models are estimated using either the SIMPLS or NIPALS algorithm. PLS regression has been extensively used in applied research because of its effectiveness in analysing rel
Externí odkaz:
http://arxiv.org/abs/1810.08104
Autor:
Alawieh, Hiba, Bertrand, Frédéric, Maumy-Bertrand, Myriam, Wicker, Nicolas, Ayoubi, Baydaa Al
Multidimensional fitting (MDF) method is a multivariate data analysis method recently developed and based on the fitting of distances. Two matrices are available: one contains the coordinates of the points and the second contains the distances betwee
Externí odkaz:
http://arxiv.org/abs/1810.05042
When cross-validating standard or extended Cox models, the commonly used criterion is the cross-validated partial loglikelihood using a naive or a van Houwelingen scheme -to make efficient use of the death times of the left out data in relation to th
Externí odkaz:
http://arxiv.org/abs/1810.02962
Autor:
Aouadi, Ismaïl, Jung, Nicolas, Carapito, Raphael, Vallat, Laurent, Bahram, Seiamak, Maumy-Bertrand, Myriam, Bertrand, Frédéric
Publikováno v:
Bioinformatics . 2021 May 5;37(5):659-668
Motivation: With the growth of big data, variable selection has become one of the major challenges in statistics. Although many methods have been proposed in the literature their performance in terms of recall and precision are limited in a context w
Externí odkaz:
http://arxiv.org/abs/1810.01670
Autor:
Cheviet, Alexis, Bonnefond, Anne, Bertrand, Frédéric, Maumy-Bertrand, Myriam, Doignon-Camus, Nadège
Publikováno v:
In Brain and Language November 2022 234
Publikováno v:
Front. Appl. Math. Stat. 7:693126 (2021)
Methods based on partial least squares (PLS) regression, which has recently gained much attention in the analysis of high-dimensional genomic datasets, have been developed since the early 2000s for performing variable selection. Most of these techniq
Externí odkaz:
http://arxiv.org/abs/1601.03281
Publikováno v:
Bioinformatics . 2021 May 5;37(5):659-668
With the emergence of high-throughput technologies, it is possible to measure large amounts of data relatively at low cost. Such situations arise in many fields from sciences to humanities, and variable selection may be of great help to answer challe
Externí odkaz:
http://arxiv.org/abs/1512.03307