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Motivated by recent research on quantifying bacterial growth dynamics based on genome assemblies, we consider a permuted monotone matrix model $Y=\Theta\Pi+Z$, where the rows represent different samples, the columns represent contigs in…

Statistics Theory · Mathematics 2020-07-15 Rong Ma , T. Tony Cai , Hongzhe Li

Metagenomics sequencing is routinely applied to quantify bacterial abundances in microbiome studies, where the bacterial composition is estimated based on the sequencing read counts. Due to limited sequencing depth and DNA dropouts, many…

Methodology · Statistics 2019-04-26 Yuanpei Cao , Anru Zhang , Hongzhe Li

In order to grow in any given environment, bacteria need to collect information about the medium composition and implement suitable growth strategies by adjusting their regulatory and metabolic degrees of freedom. In the standard sense,…

Biological Physics · Physics 2023-03-22 Anna Paola Muntoni , Andrea De Martino

Given a matrix the seriation problem consists in permuting its rows in such way that all its columns have the same shape, for example, they are monotone increasing. We propose a statistical approach to this problem where the matrix of…

Statistics Theory · Mathematics 2016-08-02 Nicolas Flammarion , Cheng Mao , Philippe Rigollet

Experimentalists have observed phenotypic variability in isogenic bacteria populations. We explore the hypothesis that in fluctuating environments this variability is tuned to maximize a bacterium's expected log growth rate, potentially…

Populations and Evolution · Quantitative Biology 2018-07-25 Sarah E. Marzen , James P. Crutchfield

Many applications, including rank aggregation, crowd-labeling, and graphon estimation, can be modeled in terms of a bivariate isotonic matrix with unknown permutations acting on its rows and/or columns. We consider the problem of estimating…

Machine Learning · Statistics 2019-10-29 Cheng Mao , Ashwin Pananjady , Martin J. Wainwright

Motivated by applications in single-cell biology and metagenomics, we investigate the problem of matrix reordering based on a noisy disordered monotone Toeplitz matrix model. We establish the fundamental statistical limit for this problem…

Statistics Theory · Mathematics 2023-08-15 T. Tony Cai , Rong Ma

There has been a recent surge of interest in studying permutation-based models for ranking from pairwise comparison data. Despite being structurally richer and more robust than parametric ranking models, permutation-based models are less…

Machine Learning · Statistics 2017-10-31 Cheng Mao , Jonathan Weed , Philippe Rigollet

We consider a ranking problem where we have noisy observations from a matrix with isotonic columns whose rows have been permuted by some permutation $\pi$ *. This encompasses many models, including crowd-labeling and ranking in tournaments…

Statistics Theory · Mathematics 2023-10-03 Emmanuel Pilliat , Alexandra Carpentier , Nicolas Verzelen

For a given finite set $\Sigma$ of matrices with nonnegative integer entries we study the growth of $$ \max_t(\Sigma) = \max\{\|A_{1}... A_{t}\|: A_i \in \Sigma\}.$$ We show how to determine in polynomial time whether the growth with $t$ is…

Computational Complexity · Computer Science 2007-05-23 Raphaël Jungers , Vladimir Protasov , Vincent D. Blondel

One important problem in microbiome analysis is to identify the bacterial taxa that are associated with a response, where the microbiome data are summarized as the composition of the bacterial taxa at different taxonomic levels. This paper…

Applications · Statistics 2016-03-04 Pixu Shi , Anru Zhang , Hongzhe Li

Linear regression studies the problem of estimating a model parameter $\beta^* \in \mathbb{R}^p$, from $n$ observations $\{(y_i,\mathbf{x}_i)\}_{i=1}^n$ from linear model $y_i = \langle \mathbf{x}_i,\beta^* \rangle + \epsilon_i$. We…

Machine Learning · Statistics 2015-05-14 Xinyang Yi , Zhaoran Wang , Constantine Caramanis , Han Liu

In this paper, by introducing two temporal-derivative-dependent auxiliary variables, a linearized and decoupled fourth-order compact finite difference method is developed and analyzed for the nonlinear coupled bacterial systems. The…

Numerical Analysis · Mathematics 2024-08-14 Jie Xu , Shusen Xie , Hongfei Fu

We introduce a new method for estimating the support size of an unknown distribution which provably matches the performance bounds of the state-of-the-art techniques in the area and outperforms them in practice. In particular, we present…

Machine Learning · Statistics 2019-10-22 I , Chien , Olgica Milenkovic

In this paper we develop and test algorithmic techniques to estimate genotypes fitnesses by analysis of observed daily frequency data monitoring the long-term evolution of bacterial populations. In particular, we develop a non-linear least…

Populations and Evolution · Quantitative Biology 2020-10-05 Sergey S. Sarkisov , Ilya Timofeyev , Robert Azencott

Bacterial growth models are commonly used for the prediction of microbial safety and the shelf life of perishable foods. Growth is affected by several environmental factors such as temperature, acidity level and salt concentration. In this…

Applications · Statistics 2014-11-24 A. Paula Palacios , J. Miguel Marín , Emiliano J. Quinto , Michael P. Wiper

The solution space of genome-scale models of cellular metabolism provides a map between physically viable flux configurations and cellular metabolic phenotypes described, at the most basic level, by the corresponding growth rates. By…

Molecular Networks · Quantitative Biology 2016-05-30 Daniele De Martino , Fabrizio Capuani , Andrea De Martino

Time-homogeneous Markov chains are often used as disease progression models in studies of cost-effectiveness and optimal decision-making. Maximum likelihood estimation of these models can be challenging when data are collected at a time…

Methodology · Statistics 2022-09-26 Duncan Ermini Leaf

High-throughput experimental techniques and bioinformatics tools make it possible to obtain reconstructions of the metabolism of microbial species. Combined with mathematical frameworks such as flux balance analysis, which assumes that…

We consider the problem of adaptive estimation of the regression function in a framework where we replace ergodicity assumptions (such as independence or mixing) by another structural assumption on the model. Namely, we propose adaptive…

Statistics Theory · Mathematics 2010-11-03 Sylvain Delattre , Stéphane Gaïffas
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