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Increasing evidence suggests that chromosome folding and genetic expression are intimately connected. For example, the co-expression of a large number of genes can benefit from their spatial co-localization in the cellular space.…

Soft Condensed Matter · Physics 2018-03-13 Guillaume Le Treut

While all the information required for the folding of a protein is contained in its amino acid sequence, one has not yet learnt how to extract this information so as to predict the detailed, biological active, three-dimensional structure of…

Condensed Matter · Physics 2007-05-23 R. A. Broglia , G. Tiana

We propose a novel approach to detect the binding between proteins making use of the anomalous diffraction of natively present heavy elements inside the molecule 3D structure. In particular, we suggest considering sulfur atoms contained in…

Several studies suggest strong correlation between different types of cancer and the relative concentration of short circulating RNA sequences (miRNA). Because of short length and low concentration, miRNA detection is not easy. Standard…

Mesoscale and Nanoscale Physics · Physics 2021-10-25 Luyan Yang , Christophe Cullin , Juan Elezgaray

Protein structure prediction can be shown to be an NP-hard problem; the number of conformations grows exponentially with the number of residues. The native conformations of proteins occupy a very small subset of these, hence an exploratory,…

Chemical Physics · Physics 2008-02-03 Mehul M. Khimasia , Peter V. Coveney

In recent years machine learning (ML) took bio- and cheminformatics fields by storm, providing new solutions for a vast repertoire of problems related to protein sequence, structure, and interactions analysis. ML techniques, deep neural…

Biomolecules · Quantitative Biology 2020-03-31 Marta M. Stepniewska-Dziubinska , Piotr Zielenkiewicz , Pawel Siedlecki

Much of the on-going statistical analysis of DNA sequences is focused on the estimation of characteristics of coding and non-coding regions that would possibly allow discrimination of these regions. In the current approach, we concentrate…

Genomics · Quantitative Biology 2009-11-10 D. Kugiumtzis , A. Provata

Fluorescence microscopy reveals that the contents of many (membrane-free) nuclear "bodies" exchange rapidly with the soluble pool whilst the underlying structure persists; such observations await a satisfactory biophysical explanation. To…

Biological Physics · Physics 2017-04-26 C. A. Brackley , B. Liebchen , D. Michieletto , F. Mouvet , P. R. Cook , D. Marenduzzo

Frameshift mutations in protein-coding DNA sequences produce a drastic change in the resulting protein sequence, which prevents classic protein alignment methods from revealing the proteins' common origin. Moreover, when a large number of…

Quantitative Methods · Quantitative Biology 2011-01-18 Marta L. Gîrdea , Laurent Noé , Gregory Kucherov

All living systems can function only far away from equilibrium, and for this reason chemical kinetic methods are critically important for uncovering the mechanisms of biological processes. Here we present a new theoretical method of…

Subcellular Processes · Quantitative Biology 2018-04-27 Maria P. Kochugaeva , Alexey A. Shvets , Anatoly B. Kolomeisky

The three dimensional structure of a protein is an outcome of the interactions of its constituent amino acids in 3D space. Considering the amino acids as nodes and the interactions among them as edges we have constructed and analyzed…

Biomolecules · Quantitative Biology 2010-07-26 Dhriti Sengupta , Sudip Kundu

The identification of novel drug-target (DT) interactions is a substantial part of the drug discovery process. Most of the computational methods that have been proposed to predict DT interactions have focused on binary classification, where…

Machine Learning · Statistics 2019-02-06 Hakime Öztürk , Elif Ozkirimli , Arzucan Özgür

Motivation Protein fold recognition is an important problem in structural bioinformatics. Almost all traditional fold recognition methods use sequence (homology) comparison to indirectly predict the fold of a tar get protein based on the…

Machine Learning · Computer Science 2017-06-06 Jie Hou , Badri Adhikari , Jianlin Cheng

Modern genomics experiments measure functional behaviors for many thousands of DNA sequences. We suggest that, especially when these sequences are chosen at random, it is natural to compute correlation functions between sequences and…

Biological Physics · Physics 2020-12-14 Yaojun Zhang , Aakash Basu , Taekjip Ha , William Bialek

This paper proposes small tree-width graph decomposition computational protein design CFN instances defined according to the model [1] with protocol defined by Simononcini et al [2] . The proteins used in the benchmark have been selected in…

Computational Engineering, Finance, and Science · Computer Science 2019-09-05 David Allouche

This paper introduces the use of cable dynamics models as a means to explore the mechanics of DNA on long-length scales. It is on these length scales that DNA forms twisted and curved three-dimensional shapes known as supercoils and loops.…

Biological Physics · Physics 2007-05-23 Sachin Goyal , Todd Lillian , Noel C. Perkins , Edgar Meyhofer

Motivation: Spliced alignment refers to the alignment of messenger RNA (mRNA) or protein sequences to eukaryotic genomes. It plays a critical role in gene annotation and the study of gene functions. Accurate spliced alignment demands…

Genomics · Quantitative Biology 2025-09-23 Siying Yang , Neng Huang , Heng Li

We examine the conformations of a model for a short segment of closed DNA. The molecule is represented as a cylindrically symmetric elastic rod with a constraint corresponding to a specification of the linking number. We obtain analytic…

Soft Condensed Matter · Physics 2009-10-31 Boris Fain , Joseph Rudnick

DNA regulation and repair processes require direct interactions between proteins and DNA at specific sites. Local fluctuations of the sugar-phosphate backbones and bases of DNA (a form of DNA "breathing") play a central role in such…

The goal of structure-based drug discovery is to find small molecules that bind to a given target protein. Deep learning has been used to generate drug-like molecules with certain cheminformatic properties, but has not yet been applied to…

Quantitative Methods · Quantitative Biology 2022-01-27 Matthew Ragoza , Tomohide Masuda , David Ryan Koes