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Models for viral populations with high replication error rates (such as RNA viruses) rely on the quasispecies concept, in which mutational pressure beyond the so-called "Error Threshold" leads to a loss of essential genetic information and…

Biological Physics · Physics 2025-02-26 David A. Herrera-Martí

Mismatch repair is a critical step in DNA replication that occurs after base selection and proofreading, significantly increasing fidelity. However, the mechanism of mismatch recognition has not been established for any repair enzyme.…

Biological Physics · Physics 2024-04-09 Nianqin Zhang , Yongjun Zhang

A mathematical model of genome degradation is proposed that takes into account a variable rate of mutation and increasing number of cells in a developing human organism. The model explains known properties of cancer development, in…

Biological Physics · Physics 2007-05-23 V. N. Binhi

We put forward an adaptive alpha (Type I Error) that decreases as the information grows, for hypothesis tests in which nested linear models are compared. A less elaborate adaptation was already presented in \citet{PP2014} for comparing…

Methodology · Statistics 2021-01-06 D. Vélez , M. E. Pérez , L. R. Pericchi

To perform recognition, molecules must locate and specifically bind their targets within a noisy biochemical environment with many look-alikes. Molecular recognition processes, especially the induced-fit mechanism, are known to involve…

Biomolecules · Quantitative Biology 2010-07-27 Yonatan Savir , Tsvi Tlusty

The experimental verification of quantum features, such as entanglement, at large scales is extremely challenging because of environment-induced decoherence. Indeed, measurement techniques for demonstrating the quantumness of multiparticle…

Quantum Physics · Physics 2013-02-26 Enrico Pomarico , Bruno Sanguinetti , Pavel Sekatski , Hugo Zbinden , Nicolas Gisin

Generative probabilistic models have shown promise in designing artificial RNA and protein sequences but often suffer from high rates of false positives, where sequences predicted as functional fail experimental validation. To address this…

Biomolecules · Quantitative Biology 2025-04-03 Francesco Calvanese , Giovanni Peinetti , Polina Pavlinova , Philippe Nghe , Martin Weigt

In real data, missing values occur frequently, which affects the interpretation with interpretable machine learning (IML) methods. Recent work considers bias and shows that model explanations may differ between imputation methods, while…

Machine Learning · Statistics 2025-12-22 Pegah Golchian , Marvin N. Wright

This paper studies the propagation of finite-sample uncertainty under nonlinear transformations commonly used in statistical decision systems. In particular, we consider process capability indices, which are widely used in manufacturing…

Applications · Statistics 2026-05-11 Fei Jiang , Lei Yang

A common approach to quantifying DNA involves repeated cycles of DNA amplification. This approach, employed by the polymerase chain reaction (PCR), produces outputs that are corrupted by amplification noise, making it challenging to…

Quantitative Methods · Quantitative Biology 2023-01-06 Abdoelnaser M Degoot , Wilfred Ndifon

The sequence of amino acid monomers in the primary structure of a protein is decided by the corresponding sequence of codons (triplets of nucleic acid monomers) on the template messenger RNA (mRNA). The polymerization of a protein, by…

Biological Physics · Physics 2017-06-02 Annwesha Dutta , Debashish Chowdhury

A key initial step in several natural language processing (NLP) tasks involves embedding phrases of text to vectors of real numbers that preserve semantic meaning. To that end, several methods have been recently proposed with impressive…

Computation and Language · Computer Science 2019-04-26 Rohit Voleti , Julie M. Liss , Visar Berisha

This paper studies random-coding error exponents of randomised list decoding, in which the decoder randomly selects $L$ messages with probabilities proportional to the decoding metric of the codewords. The exponents (or bounds) are given…

Information Theory · Computer Science 2026-01-15 Henrique K. Miyamoto , Sheng Yang

RNA folding is a kinetic process governed by the competition of a large number of structures stabilized by the transient formation of base pairs that may induce complex folding pathways and the formation of misfolded structures. Despite of…

Biological Physics · Physics 2009-03-16 M. Manosas , I. Junier , F. Ritort

The throughput of a linear cellular uplink with a random number of users, different power control schemes, and cooperative base stations is considered in the large system limit where the number of cells is large for non fading Gaussian…

Information Theory · Computer Science 2016-11-18 Oren Somekh , Osvaldo Simeone , H. Vincent Poor , Shlomo Shamai

Entropy minimization (EM) is frequently used to increase the accuracy of classification models when they're faced with new data at test time. EM is a self-supervised learning method that optimizes classifiers to assign even higher…

Computer Vision and Pattern Recognition · Computer Science 2024-05-14 Ori Press , Ravid Shwartz-Ziv , Yann LeCun , Matthias Bethge

Protein molecules in cells are synthesized by macromolecular machines called ribosomes. According to recent experimental data, we reduce the complexity of the ribosome and propose a model to express its activity in six main states. Using…

Subcellular Processes · Quantitative Biology 2016-07-26 Bahareh Shakiba , Maryam Dayeri , Farshid Mohammad-Rafiee

The aim of this work is to revisit the phenomenological theory of the interaction between membrane inclusions, mediated by the membrane fluctuations. We consider the case where the inclusions are separated by distances larger than their…

Soft Condensed Matter · Physics 2022-12-28 E. S. Pikina , A. R. Muratov , E. I. Kats , V. V. Lebedev

Many processes in chemistry and physics take place on timescales that cannot be explored using standard molecular dynamics simulations. This renders the use of enhanced sampling mandatory. Here we introduce an enhanced sampling method that…

Chemical Physics · Physics 2020-06-12 Jayashrita Debnath , Michele Parrinello

An interpolation error is an integral of the squared error of a regression model over a domain of interest. We consider the interpolation error for the case of misspecified Gaussian process regression: used covariance function differs from…

Statistics Theory · Mathematics 2018-03-28 A. Zaytsev , E. Romanenkova , D. Ermilov
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