Results 151 to 160 of about 2,051,541 (361)

Parameterized Complexity of Manipulating Sequential Allocation [PDF]

, 2019
Michele Flammini, Hugo Gilbert
openalex   +1 more source

Parameterized Complexity of Binary CSP: Vertex Cover, Treedepth, and Related Parameters

, 2023
Hans L. Bodlaender, Carla Groenland, Michał Pilipczuk   +2 more
openalex   +2 more sources

Learned Conformational Space and Pharmacophore Into Molecular Foundational Model

Advanced Science, EarlyView.
The Ouroboros model introduces two orthogonal modules within a unified framework that independently learn molecular representations and generate chemical structures. This design enables flexible optimization strategies for each module and faithful structure reconstruction without prompts or noise.
Lin Wang, Yifan Wu, Hao Luo, Minglong Liang, Yihang Zhou, Cheng Chen, Chris Liu, Jun Zhang, Yang Zhang   +8 more
wiley   +1 more source

Enhanced natural parameterized quantum circuit

Physical Review Research
The classical-quantum interface for loading classical data into quantum systems is an indispensable component of quantum information processing, and the parameterized quantum circuit (PQC) represents significant methodology in this area.
Yuquan Chen, Yanjun Hou, Zeyuan Wang, Tianyun Wang, Ze Wu, Zhaokai Li, Xinhua Peng   +6 more
doaj   +1 more source

A Quantum Framework for Protein Binding‐Site Structure Prediction on Utility‐Level Quantum Processors

Advanced Science, EarlyView.
This study presents a hybrid quantum‐classical framework for accurate prediction of protein structures on utility‐level quantum processors. We evaluate the practical application of the Variational Quantum Eigen‐solver (VQE) in protein structure prediction and demonstrate its superiority over state‐of‐the‐art deep learning methods in molecular docking ...
Yuqi Zhang, Yuxin Yang, William Martin, Kingsten Lin, Zixu Wang, Cheng‐Chang Lu, Weiwen Jiang, Ruth Nussinov, Joseph Loscalzo, Qiang Guan, Feixiong Cheng   +10 more
wiley   +1 more source

Quantum Computing Meets Deep Learning: A QCNN Model for Accurate and Efficient Image Classification

Mathematics
In deep learning, Convolutional Neural Networks (CNNs) serve as fundamental models, leveraging the correlational structure of data for tasks such as image classification and processing.
Sunil Prajapat, Manish Tomar, Pankaj Kumar, Rajesh Kumar, Athanasios V. Vasilakos   +4 more
doaj   +1 more source

Parameterized Complexity of Paired Domination

The Paired Domination problem is one of the well-studied variants of the classical Dominating Set problem. In a graph G on nvertices, a dominating set D (set of vertices such that N[D] = V (G)) is called a paired dominating set of G, if G[D] has perfect matching. In the Paired Domination problem, given a graph G and a positive integer k, the task is to
Andreev, Nikita, Bliznets, Ivan, Kundu, Madhumita, Saurabh, Saket, Tripathi, Vikash, Verma, Shaily   +5 more
openaire   +2 more sources

HSP70 Interactome‐Mediated Proteolysis Targeting Chimera (HSP70‐PROTAC) for Ferroptosis‐Driven Cancer Treatment

Advanced Science, EarlyView.
This study reports a novel targeted protein degradation strategy termed “HSP70‐PROTAC” that recruits Hsc70 complex to a target protein for inducing degradation. Among them, GDAz‐3 exhibits effective GPX4 degradation activity via UPS/CMA processes, triggering ferroptosis‐driven anticancer activity in vitro and in vivo.
Jinyun Dong, Yulong Li, Hui Liang, Zumei Wu, Shiqun Wang, Yichao Wang, Jieyu Xu, Yanning Lan, Maohua Cai, Guangzhao Pan, Haiyan Yang, Kai Miao, Zhe‐Sheng Chen, Fangfang Tao, Xuelei Ma, Jiang‐Jiang Qin   +15 more
wiley   +1 more source

Mapping Charge Interactions in Intrinsically Disordered Proteins

Advanced Science, EarlyView.
This study presents analytical models to predict intrachain distances in intrinsically disordered proteins (IDPs), accounting for charge patterning, salt concentration, and electrostatic effects. Validated against single‐molecule FRET data, a minimal‐parameter polymer model is identified that captures key interactions and chain dimensions. These models
Michael Phillips, Andrea Holla, Magdalena Wojtas, Aritra Chowdhury, Andrea Sottini, Sebastian L. B. König, Natalie Mutter, Nick Lamb, Jonathan Huihui, Monika Lopko, Andrea Soranno, Daniel Nettels, Andrzej Ożyhar, Benjamin Schuler, Kingshuk Ghosh   +14 more
wiley   +1 more source

Parameterized Complexity in Cognitive Modeling: Foundations, Applications and Opportunities [PDF]

, 2007
Iris van Rooij, Todd Wareham
openalex   +1 more source