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Related papers: Inferring DNA sequences from mechanical unzipping:…

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The complementary strands of DNA molecules can be separated when stretched apart by a force; the unzipping signal is correlated to the base content of the sequence but is affected by thermal and instrumental noise. We consider here the…

Biomolecules · Quantitative Biology 2015-05-13 Valentina Baldazzi , Serena Bradde , Simona Cocco , Enzo Marinari , Remi Monasson

A study of the micromechanical unzipping of DNA in the framework of the Peyrard-Bishop-Dauxois model is presented. We introduce a Monte Carlo technique that allows accurate determination of the dependence of the unzipping forces on…

Soft Condensed Matter · Physics 2007-05-23 N. K. Voulgarakis , A. Redondo , A. R. Bishop , K. O. Rasmussen

In this paper we provide an alternative approach to the works of the physicists S. Cocco and R. Monasson about a model of DNA molecules. The aim is to predict the sequence of bases by mechanical stimulations. The model described by the…

Applications · Statistics 2012-02-10 Pierre Andreoletti , Roland Diel

The possibility of detecting mutations in a DNA from force measurements (as a first step towards sequence analysis) is discussed theoretically based on exact calculations. The force signal is associated with the domain wall separating the…

Statistical Mechanics · Physics 2009-11-07 Somendra M. Bhattacharjee , D. Marenduzzo

We present a dynamical model of DNA mechanical unzipping under the action of a force. The model includes the motion of the fork in the sequence-dependent landscape, the trap(s) acting on the bead(s), and the polymeric components of the…

Biomolecules · Quantitative Biology 2011-09-19 Carlo Barbieri , Simona Cocco , Remi Monasson , Francesco Zamponi

Rapid sequencing of individual human genome is prerequisite to genomic medicine, where diseases will be prevented by preemptive cures. Quantum-mechanical tunneling through single-stranded DNA in a solid-state nanopore has been proposed for…

We propose a probabilistic model for interpreting gene expression levels that are observed through single-cell RNA sequencing. In the model, each cell has a low-dimensional latent representation. Additional latent variables account for…

Machine Learning · Computer Science 2018-01-18 Romain Lopez , Jeffrey Regier , Michael Cole , Michael Jordan , Nir Yosef

Deoxyribonucleic acid (DNA) has shown great promise in enabling computational applications, most notably in the fields of DNA digital data storage and DNA computing. Information is encoded as DNA strands, which will naturally bind in…

Machine Learning · Computer Science 2021-10-22 David Buterez

A method for encoding information in DNA sequences is described. The method is based on the precision-resolution framework, and is aimed to work in conjunction with a recently suggested terminator-free template independent DNA synthesis…

Information Theory · Computer Science 2020-05-14 Siddharth Jain , Farzad Farnoud , Moshe Schwartz , Jehoshua Bruck

We propose a probabilistic model for interpreting gene expression levels that are observed through single-cell RNA sequencing. In the model, each cell has a low-dimensional latent representation. Additional latent variables account for…

Machine Learning · Computer Science 2017-10-18 Romain Lopez , Jeffrey Regier , Michael Cole , Michael Jordan , Nir Yosef

Splice sites play a crucial role in gene expression, and accurate prediction of these sites in DNA sequences is essential for diagnosing and treating genetic disorders. We address the challenge of splice site prediction by introducing…

Genomics · Quantitative Biology 2023-11-23 Asmita Poddar , Vladimir Uzun , Elizabeth Tunbridge , Wilfried Haerty , Alejo Nevado-Holgado

We study theoretically the mechanical failure of a simple model of double stranded DNA under an applied shear. Starting from a more microscopic Hamiltonian that describes a sheared DNA, we arrive at a nonlinear generalization of a ladder…

Soft Condensed Matter · Physics 2009-04-13 Buddhapriya Chakrabarti , David R. Nelson

The Viterbi algorithm, presented in 1967, allows a maximum likelihood decoding of partial response codes. This study focuses on the duobinary code which is the first member of this family and has been specified for the digital part of…

Information Theory · Computer Science 2022-09-07 Henri Mertens , Marc Van Droogenbroeck

We present a decoding algorithm for quantum convolutional codes that finds the class of degenerate errors with the largest probability conditioned on a given error syndrome. The algorithm runs in time linear with the number of qubits.…

Quantum Physics · Physics 2012-04-12 Emilie Pelchat , David Poulin

This paper presents a probabilistic approach for DNA sequence analysis. A DNA sequence consists of an arrangement of the four nucleotides A, C, T and G and different representation schemes are presented according to a probability measure…

Quantitative Methods · Quantitative Biology 2010-02-12 Amrita Priyam , B. M. Karan , G. Sahoo

Understanding how stochastic gene expression is regulated in biological systems using snapshots of single-cell transcripts requires state-of-the-art methods of computational analysis and statistical inference. A Bayesian approach to…

Quantitative Methods · Quantitative Biology 2018-12-10 Yen Ting Lin , Nicolas E. Buchler

Bayesian inference for complex models with an intractable likelihood can be tackled using algorithms performing many calls to computer simulators. These approaches are collectively known as "simulation-based inference" (SBI). Recent SBI…

The unzipping of a double stranded DNA whose ends are subjected to a time dependent periodic force with frequency $\omega$ and amplitude $G$ is studied using Monte Carlo simulations. We obtain the dynamical order parameter, $Q$, defined as…

Soft Condensed Matter · Physics 2019-06-17 M. Suman Kalyan , Rajeev Kapri

The opening of the Y-fork - the first step of DNA replication - is shown to be a critical phenomenon under an external force at one of its ends. From the results of an equivalent delocalization in a non-hermitian quantum-mechanics problem…

Statistical Mechanics · Physics 2009-10-31 Somendra M. Bhattacharjee

The characterization of drug-protein interactions is crucial in the high-throughput screening for drug discovery. The deep learning-based approaches have attracted attention because they can predict drug-protein interactions without…

Machine Learning · Computer Science 2020-12-22 QHwan Kim , Joon-Hyuk Ko , Sunghoon Kim , Nojun Park , Wonho Jhe
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