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Local feature matching aims at establishing sparse correspondences between a pair of images. Recently, detector-free methods present generally better performance but are not satisfactory in image pairs with large scale differences. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-01-24 Junjie Ni , Yijin Li , Zhaoyang Huang , Hongsheng Li , Hujun Bao , Zhaopeng Cui , Guofeng Zhang

Numerical simulations of plasma flows are crucial for advancing our understanding of microscopic processes that drive the global plasma dynamics in fusion devices, space, and astrophysical systems. Identifying and classifying particle…

Computational Physics · Physics 2020-10-13 Stefano Markidis , Ivy Peng , Artur Podobas , Itthinat Jongsuebchoke , Gabriel Bengtsson , Pawel Herman

Similarity measures are widely used to interpret the representational geometries used by neural networks to solve tasks. Yet, because existing methods compare the extrinsic geometry of representations in state space, rather than their…

Machine Learning · Computer Science 2026-04-03 N Alex Cayco-Gajic , Arthur Pellegrino

In this paper, we introduce a direction of arrival (DoA) estimation method based on a technique named phase spectrometry (PS) that is mainly suitable for mm-Wave and Tera-hertz applications as an alternative for DoA estimation using antenna…

Signal Processing · Electrical Eng. & Systems 2021-08-04 Farzam Hejazi , Nazanin Rahnavard

Initial protein structural comparisons were sequence-based. Since amino acids that are distant in the sequence can be close in the 3-dimensional (3D) structure, 3D contact approaches can complement sequence approaches. Traditional 3D…

Molecular Networks · Quantitative Biology 2017-03-01 Fazle E. Faisal , Julie L. Chaney , Khalique Newaz , Jun Li , Scott J. Emrich , Patricia L. Clark , Tijana Milenkovic

We consider the problem of identifying patterns in a data set that exhibit anomalous behavior, often referred to as anomaly detection. In most anomaly detection algorithms, the dissimilarity between data samples is calculated by a single…

Machine Learning · Computer Science 2013-01-08 Ko-Jen Hsiao , Kevin S. Xu , Jeff Calder , Alfred O. Hero

Network Meta-Analysis (NMA) plays a pivotal role in synthesizing evidence from various sources and comparing multiple interventions. At its core, NMA relies on integrating both direct evidence from head-to-head comparisons and indirect…

Direct-Coupling Analysis is a group of methods to harvest information about coevolving residues in a protein family by learning a generative model in an exponential family from data. In protein families of realistic size, this learning can…

Quantitative Methods · Quantitative Biology 2014-09-16 Magnus Ekeberg , Tuomo Hartonen , Erik Aurell

Multimodal aspect-based sentiment analysis (MABSA) aims to understand opinions in a granular manner, advancing human-computer interaction and other fields. Traditionally, MABSA methods use a joint prediction approach to identify aspects and…

Computation and Language · Computer Science 2024-06-14 Shezheng Song , Shasha Li , Shan Zhao , Chengyu Wang , Xiaopeng Li , Jie Yu , Qian Wan , Jun Ma , Tianwei Yan , Wentao Ma , Xiaoguang Mao

Despite the recent advances in various Structural Genomics Projects, a large gap remains between the number of sequenced and structurally characterized proteins. Some reasons for this discrepancy include technical difficulties, labor, and…

Computer Vision and Pattern Recognition · Computer Science 2023-04-07 Arjang Fahim , Stephanie Irausquin , Homayoun Valafar

We present a molecular simulation method to simultaneously find multiple transition pathways, and their associated free-energy profiles. The scheme extends path-metadynamics (PMD) [Phys. Rev. Lett. 109, 020601 (2012)] with multiple paths…

Statistical Mechanics · Physics 2025-06-23 Alberto Pérez de Alba Ortíz , Bernd Ensing

We present a simple and robust technique to extract kinetic rate models and thermodynamic quantities from single molecule time traces. SMACKS (Single Molecule Analysis of Complex Kinetic Sequences) is a maximum likelihood approach that…

Quantitative Methods · Quantitative Biology 2022-03-10 Sonja Schmid , Markus Götz , Thorsten Hugel

We performed "weighted ensemble" path-sampling simulations of adenylate kinase, using several semi-atomistic protein models. Our study investigated both the biophysics of conformational transitions as well as the possibility of increasing…

Biological Physics · Physics 2010-02-25 Divesh Bhatt , Daniel M. Zuckerman

A new method for the Automated Protein Structure Analysis (APSA) is derived, which simplifies the protein backbone to a smooth curve in 3-dimensional space. For the purpose of obtaining this smooth line each amino acid is represented by its…

Quantitative Methods · Quantitative Biology 2008-11-24 Sushilee Raganathan , Dmitry Izotov , Elfi Kraka , Dieter Cremer

Atomic-level simulations are widely used to study biomolecules and their dynamics. A common goal in such studies is to compare simulations of a molecular system under several conditions -- for example, with various mutations or bound…

Biomolecules · Quantitative Biology 2025-01-07 Martin Vögele , Neil J. Thomson , Sang T. Truong , Jasper McAvity , Ulrich Zachariae , Ron O. Dror

Much attention has been devoted to understanding the microscopic pathways of phase transition between two equilibrium condensed phases (such as liquids and solids). However, the microscopic pathways between non-equilibrium, non-diffusive…

Chemical Physics · Physics 2024-02-27 Gadha Ramesh , Ved Mahajan , Debasish Koner , Rakesh S. Singh

When modeling multivariate data, one might have an extra parameter of contextual information that could be used to treat some observations as more similar to others. For example, images of faces can vary by age, and one would expect the…

Computer Vision and Pattern Recognition · Computer Science 2018-02-06 Ajay Gupta , Adrian Barbu

We theorize that phylogenetic profiles provide a quantitative method that can relate the structural and functional properties of proteins, as well as their evolutionary relationships. A key feature of phylogenetic profiles is the…

Quantitative Methods · Quantitative Biology 2009-11-04 Yoojin Hong , Jaewoo Kang , Dongwon Lee , Randen L. Patterson , Damian B. van Rossum

Dimensionality reduction is a crucial step for pattern recognition and data mining tasks to overcome the curse of dimensionality. Principal component analysis (PCA) is a traditional technique for unsupervised dimensionality reduction, which…

Machine Learning · Computer Science 2017-05-04 Zan Gao , Guotai Zhang , Feiping Nie , Hua Zhang

Identifying and characterizing mutational paths is an important issue in evolutionary biology and in bioengineering. We here introduce a generic description of mutational paths in terms of the goodness of sequences and of the mutational…

Biomolecules · Quantitative Biology 2023-03-29 Eugenio Mauri , Simona Cocco , Rémi Monasson