Evidence map›Paper›PMID 39429974›Full record

ArticleJournal of physics. Complexity2024

Persistent Mayer Dirac.

Faisal Suwayyid, Guo-Wei Wei

Abstract read
In one paragraph

Article in Journal of physics. Complexity, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Persistent Stanley-Reisner Theory.Foundations of data science (Springfield, Mo.) · 2026
    Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Persistent Topological Laplacians-A Survey.Mathematics (Basel, Switzerland) · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Faisal SuwayyidDepartment of Mathematics, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia.
Guo-Wei WeiDepartment of Mathematics, Michigan State University, East Lansing, MI 48824, United States of America.ORCID https://orcid.org/0000-0001-8132-5998

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

Topological data analysis (TDA) has made significant progress in developing a new class of fundamental operators known as the Dirac operator, particularly in topological signals and molecular representations. However, the current approaches being used are based on the classical case of chain complexes. The present study establishes Mayer Dirac operators based on

Indexed as

biology modelingMayer DiracMayer homologyMayer LaplacianN-chain complexpersistent homologytopological signals

Identifiers

PMID39429974
PMCPMC11488505

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.