Evidence map›Paper›PMID 40838040›Full record

ArticleAIMS mathematics2025

Multi-scale Jones polynomial and persistent Jones polynomial for knot data analysis.

Ruzhi Song, Fengling Li, Jie Wu, Fengchun Lei, Guo-Wei Wei

Abstract read
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Article in AIMS mathematics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Persistent Topological Laplacians-A Survey.Mathematics (Basel, Switzerland) · 2025
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Ruzhi SongSchool of Mathematical Sciences, Dalian University of Technology, Dalian 116024, Liaoning, China.
Fengling LiSchool of Mathematical Sciences, Dalian University of Technology, Dalian 116024, Liaoning, China.
Jie WuSchool of Mathematical Sciences, Hebei Normal University, Shijiazhuang 050024, Hebei, China.
Fengchun LeiSchool of Mathematical Sciences, Dalian University of Technology, Dalian 116024, Liaoning, China.
Guo-Wei WeiDepartment of Mathematics, Michigan State University, 426 Auditorium Road, East Lansing, MI 48824, USA.

Funding

AI-based platform for predicting emerging vaccine-escape variants and designing mutation-proof antibodiesR01AI164266 · NIAID · UNIVERSITY OF GEORGIA · PI Guowei Wei, YONG-HUI ZHENG · 2022 to 2026
$2.7M
Discovery-Driven Mathematics and Artificial Intelligence for Biosciences and Drug DiscoveryR35GM148196 · NIGMS · UNIVERSITY OF GEORGIA · PI Guowei Wei · 2023 to 2026
$1.5M
Synergistic integration of topology and machine learning for the predictions of protein-ligand binding affinities and mutation impactsR01GM126189 · NIGMS · MICHIGAN STATE UNIVERSITY · PI WEI, GUOWEI · 2018 to 2021
$1.4M
NIAID NIH HHS R01 AI164266NIGMS NIH HHS R01 GM126189NIGMS NIH HHS R35 GM148196
6 · The paper itself

Abstract

Many structures in science, engineering, and art can be viewed as curves in 3-space. The entanglement of these curves plays a crucial role in determining the functionality and physical properties of materials. Many concepts in knot theory provide theoretical tools to explore the complexity and entanglement of curves in 3-space. However, classical knot theory focuses on global topological properties and lacks the consideration of local structural information, which is critical in practical applications. In this work, two localized models based on the Jones polynomial were proposed, namely, the multi-scale Jones polynomial and the persistent Jones polynomial. The stability of these models, especially the insensitivity of the multi-scale and persistent Jones polynomial models to small perturbations in curve collections, was analyzed, thus ensuring their robustness for real-world applications.

Indexed as

57K1092C10curve data analysisJones polynomialknot data analysislocalizationprotein flexibilitystability

Identifiers

PMID40838040
PMCPMC12363994

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.