English
Related papers

Related papers: A Roadmap for Improving Data Reliability and Shari…

200 papers

Computational protein design (CPD) offers transformative potential for bioengineering, but current deep CPD models, focused on universal domains, struggle with function-specific designs. This work introduces a novel CPD paradigm tailored…

Quantitative Methods · Quantitative Biology 2024-11-28 Jiangbin Zheng , Ge Wang , Han Zhang , Stan Z. Li

Intrinsically disordered proteins and regions are increasingly appreciated for their abundance in the proteome and the many functional roles they play in the cell. In this short review, we describe a variety of approaches used to obtain…

Biological Physics · Physics 2024-12-31 Zi Hao Liu , Maria Tsanai , Oufan Zhang , Teresa Head-Gordon , Julie Forman-Kay

End-to-end deep networks represent the state of the art for stereo matching. While excelling on images framing environments similar to the training set, major drops in accuracy occur in unseen domains (e.g., when moving from synthetic to…

Computer Vision and Pattern Recognition · Computer Science 2020-10-16 Changjiang Cai , Matteo Poggi , Stefano Mattoccia , Philippos Mordohai

Protein structure generative models excel at predicting single protein static structures from sequence, but routinely fail to capture the correct conformational state of protein complexes, critical for protein design and induced proximity…

Machine Learning · Computer Science 2026-05-27 Alon Shtrikman , Nitzan Simchi , Michal Ran Shchory , Sagie Brodsky , Eran Seger , Kirill Pevzner

Classification of proteins based on their structure provides a valuable resource for studying protein structure, function and evolutionary relationships. With the rapidly increasing number of known protein structures, manual and…

Computational Engineering, Finance, and Science · Computer Science 2009-07-14 Oktie Hassanzadeh

Empirical modelling often aims for the simplest model consistent with the data. A new technique is presented which quantifies the consistency of the model dynamics as a function of location in state space. As is well-known, traditional…

Chaotic Dynamics · Physics 2009-11-10 Patrick E. McSharry , Leonard A. Smith

Fueled by breakthrough technology developments, the biological, biomedical, and behavioral sciences are now collecting more data than ever before. There is a critical need for time- and cost-efficient strategies to analyze and interpret…

Small molecules in biological samples are studied to provide information about disease states, environmental toxins, natural product drug discovery, and many other applications. The primary window into the composition of small molecule…

Machine Learning · Computer Science 2023-05-08 Gennady Voronov , Rose Lightheart , Joe Davison , Christoph A. Krettler , David Healey , Thomas Butler

An applied problem facing all areas of data science is harmonizing data sources. Joining data from multiple origins with unmapped and only partially overlapping features is a prerequisite to developing and testing robust, generalizable…

Proteins play crucial roles in every cellular process by interacting with each other, with nucleic acids, metabolites, and other molecules. The resulting assemblies can be very large and intricate and pose challenges to experimental…

Biomolecules · Quantitative Biology 2021-03-16 Charlotte W. van Noort , Rodrigo V. Honorato , Alexandre M. J. J. Bonvin

In cancer therapeutics, protein-metal binding mechanisms critically govern the pharmacokinetics and targeting efficacy of drugs, thereby fundamentally shaping the rational design of anticancer metallodrugs. While conventional laboratory…

Proteins congregate into complexes to perform fundamental cellular functions. Phenotypic outcomes, in health and disease, are often mechanistically driven by the remodeling of protein complexes by protein coding mutations or cellular…

Spatially proximate amino acids in a protein tend to coevolve. A protein's three-dimensional (3D) structure hence leaves an echo of correlations in the evolutionary record. Reverse engineering 3D structures from such correlations is an open…

Quantitative Methods · Quantitative Biology 2013-01-15 Magnus Ekeberg , Cecilia Lövkvist , Yueheng Lan , Martin Weigt , Erik Aurell

Lossy compression is one of the most effective methods for reducing the size of scientific data containing multiple data fields. It reduces information density through prediction or transformation techniques to compress the data. Previous…

Machine Learning · Computer Science 2024-09-30 Youyuan Liu , Wenqi Jia , Taolue Yang , Miao Yin , Sian Jin

In systems biology, it is common to measure biochemical entities at different levels of the same biological system. One of the central problems for the data fusion of such data sets is the heterogeneity of the data. This thesis discusses…

Genomics · Quantitative Biology 2019-08-27 Yipeng Song

Medical ultrasound image segmentation faces significant challenges due to limited labeled data and characteristic imaging artifacts including speckle noise and low-contrast boundaries. While semi-supervised learning (SSL) approaches have…

Computer Vision and Pattern Recognition · Computer Science 2026-03-20 Jingguo Qu , Xinyang Han , Yao Pu , Man-Lik Chui , Simon Takadiyi Gunda , Ziman Chen , Jing Qin , Ann Dorothy King , Winnie Chiu-Wing Chu , Jing Cai , Michael Tin-Cheung Ying

Proteins are central to biological systems, participating as building blocks across all forms of life. Despite advancements in understanding protein functions through protein sequence analysis, there remains potential for further…

Machine Learning · Computer Science 2025-08-29 Yunqing Liu , Wenqi Fan , Xiaoyong Wei , Qing Li

The evolution, regulation and sustenance of biological complexity is determined by protein-protein interaction network that is filled with dynamic events. Recent experimental evidences point out that clustering of proteins has a vital role…

Tissues and Organs · Quantitative Biology 2007-05-23 RV Krishnan

The proliferation of artificial intelligence has enabled a diversity of applications that bridge the gap between digital and physical worlds. As physical environments are too complex to model through a single information acquisition…

Machine Learning · Computer Science 2025-08-11 Yu Zheng

Motivated by the increasing demand for multi-source data integration in various scientific fields, in this paper we study matrix completion in scenarios where the data exhibits certain block-wise missing structures -- specifically, where…

Methodology · Statistics 2025-08-19 Runbing Zheng , Minh Tang