Topological indices based on 2- or 3-eccentricity to predict anti-HIV activity

DOI10.1016/j.amc.2021.126748OpenAlexW3210823988MaRDI QIDQ2060204

Xingfu Li, Guihai Yu, Deyan He

Publication date: 13 December 2021

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2021.126748

zbMATH Keywords

machine learning predicting modelspredicting anti-HIV activitytopological index based on \(k\)-eccentricity

Mathematics Subject Classification ID

Mathematical programming (90Cxx) Graph theory (05Cxx) Chemistry (92Exx)

Related Items (2)

Enumeration of subtrees of planar two-tree networks ⋮ New transmission irregular chemical graphs

Cites Work

• A computational approach to construct a multivariate complete graph invariant
• Eccentric distance sum: A novel graph invariant for predicting biological and physical properties
• Graph Energy
• Steiner problem in networks: A survey
• The steiner problem in graphs
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