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A multiscale approach is used to simulate the translocation of DNA through a nanopore. Within this scheme, the interactions of the molecule with the surrounding fluid (solvent) are explicitly taken into account. By generating polymers of…

Biological Physics · Physics 2009-11-13 Simone Melchionna , Maria Fyta , Efthimios Kaxiras , Sauro Succi

A core problem in machine learning is to learn expressive latent variables for model prediction on complex data that involves multiple sub-components in a flexible and interpretable fashion. Here, we develop an approach that improves…

Machine Learning · Computer Science 2024-02-13 Yi-Lin Tuan , Zih-Yun Chiu , William Yang Wang

We present a new skeletal representation along with a matching framework to address the deformable shape recognition problem. The disconnectedness arises as a result of excessive regularization that we use to describe a shape at an…

Computer Vision and Pattern Recognition · Computer Science 2011-04-15 C. Aslan , A. Erdem , E. Erdem , S. Tari

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

Biological sequence comparison is a key step in inferring the relatedness of various organisms and the functional similarity of their components. Thanks to the Next Generation Sequencing efforts, an abundance of sequence data is now…

Machine Learning · Computer Science 2016-09-13 Dhananjay Kimothi , Akshay Soni , Pravesh Biyani , James M. Hogan

Dimension reduction is often the first step in statistical modeling or prediction of multivariate spatial data. However, most existing dimension reduction techniques do not account for the spatial correlation between observations and do not…

Methodology · Statistics 2025-05-27 Si Cheng , Magali N. Blanco , Timothy V. Larson , Lianne Sheppard , Adam Szpiro , Ali Shojaie

In Transport Mode Detection, a great diversity of methodologies exist according to the choice made on sensors, preprocessing, model used, etc. In this domain, the comparisons between each option are not always complete. Experiments on a…

Machine Learning · Computer Science 2021-07-07 Hugues Moreau , Andréa Vassilev , Liming Chen

Thermal conductivity of isolated single molecule DNA fragments is of importance for nanotechnology, but has not yet been measured experimentally. Theoretical estimates based on simplified (1D) models predict anomalously high thermal…

Mesoscale and Nanoscale Physics · Physics 2015-05-20 Alexander V. Savin , Mikhail A. Mazo , Irina P. Kikot , Leonid I. Manevitch , Alexey V. Onufriev

Obtaining effective representations of DNA sequences is crucial for genome analysis. Metagenomic binning, for instance, relies on genome representations to cluster complex mixtures of DNA fragments from biological samples with the aim of…

Machine Learning · Computer Science 2024-11-05 Abdulkadir Celikkanat , Andres R. Masegosa , Thomas D. Nielsen

Achieving robust multi-person 2D body landmark localization and pose estimation is essential for human behavior and interaction understanding as encountered for instance in HRI settings. Accurate methods have been proposed recently, but…

Computer Vision and Pattern Recognition · Computer Science 2019-12-03 Angel Martínez-González , Michael Villamizar , Olivier Canévet , Jean-Marc Odobez

Segmentation of distinct bones plays a crucial role in diagnosis, planning, navigation, and the assessment of bone metastasis. It supplies semantic knowledge to visualisation tools for the planning of surgical interventions and the…

Image and Video Processing · Electrical Eng. & Systems 2020-10-15 Eva Schnider , Antal Horváth , Georg Rauter , Azhar Zam , Magdalena Müller-Gerbl , Philippe C. Cattin

Molecular representation learning has attracted much attention recently. A molecule can be viewed as a 2D graph with nodes/atoms connected by edges/bonds, and can also be represented by a 3D conformation with 3-dimensional coordinates of…

Machine Learning · Computer Science 2022-07-20 Jinhua Zhu , Yingce Xia , Lijun Wu , Shufang Xie , Tao Qin , Wengang Zhou , Houqiang Li , Tie-Yan Liu

In order to interpret recent experimental studies of the dependence of conductance of ds-DNA as the DNA is pulled from the 3'end1-3'end2 ends, which find a sharp conductance jump for a very short (4.5 %) stretching length, we carried out…

Soft Condensed Matter · Physics 2016-08-26 Saientan Bag , Santosh Mogurampelly , William A Goddard , Prabal K Maiti

Electronic properties of DNA are believed to play a crucial role in many phenomena in living organisms, for example the location of DNA lesions by base excision repair (BER) glycosylases and the regulation of tumor-suppressor genes such as…

Other Quantitative Biology · Quantitative Biology 2012-02-21 Chi-Tin Shih , Stephen A. Wells , Ching-Ling Hsu , Yun-Yin Cheng , Rudolf A. Römer

For medical volume visualization, one of the most important tasks is to reveal clinically relevant details from the 3D scan (CT, MRI ...), e.g. the coronary arteries, without obscuring them with less significant parts. These volume datasets…

Artificial Intelligence · Computer Science 2009-06-12 Dženan Zukić , Andreas Elsner , Zikrija Avdagić , Gitta Domik

Many-body physics of electron-electron correlations plays a central role in condensed mater physics, it governs a wide range of phenomena, stretching from superconductivity to magnetism, and is behind numerous technological applications. To…

Mesoscale and Nanoscale Physics · Physics 2023-06-09 Anupam Bhattacharya , Ivan Timokhin , Ratnamala Chatterjee , Qian Yang , Artem Mishchenko

DNA sequencing is revolutionising the field of medicine. DNA sequencers, the machines which perform DNA sequencing, have evolved from the size of a fridge to that of a mobile phone over the last two decades. The cost of sequencing a human…

Genomics · Quantitative Biology 2021-01-14 Hasindu Gamaarachchi

Machine learning has revolutionized materials discovery, but data scarcity remains a critical bottleneck for complex functional properties. As emerging systems, two-dimensional (2D) materials possess limited overall data volumes. Evaluating…

Materials Science · Physics 2026-05-26 Huiyang Zhang , Xinyu Chen , Qionghua Zhou , Jinlan Wang

Co-localization of networks of genes in the nucleus is thought to play an important role in determining gene expression patterns. Based upon experimental data, we built a dynamical model to test whether pure diffusion could account for the…

Molecular Networks · Quantitative Biology 2012-03-06 Jing Kang , Bing Xu , Ye Yao , Wei Lin , Conor Hennessy , Peter Fraser , Jianfeng Feng

In this work we propose a model that can manipulate individual visual attributes of objects in a real scene using examples of how respective attribute manipulations affect the output of a simulation. As an example, we train our model to…

Machine Learning · Computer Science 2019-04-04 Ben Usman , Nick Dufour , Kate Saenko , Chris Bregler
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