ArticleHeliyon2024
A QSPR analysis of physical properties of antituberculosis drugs using neighbourhood degree-based topological indices and support vector regression.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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.
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.
Who cites it
12 citing papers in PubMed.
- Topological indices and QSPR analysis of drug molecules from different therapeutic classes.Scientific reports · 2026Article
- Predicting properties of antifungal drug molecules using neighborhood degree topological indices.Scientific reports · 2026Article
- Multi criterion decision making analysis of hematologic cancer drugs via topological indices and physicochemical properties.Scientific reports · 2025Article
- Quantitative structure property relationship and multiattribute decision analysis of antianginal drugs using topological indices.Scientific reports · 2025Article
- Topological information entropy and spectral energy analysis in aminal-linked covalent organic frameworks.Scientific reports · 2025Article
- Predictive analysis of vitiligo treatment drugs using degree and neighborhood degree-based topological descriptors.Scientific reports · 2025Article
- Article
- M-polynomial driven machine learning models for predicting physicochemical properties of antibiotics.PloS one · 2025Article
- Hydrogen-centric machine learning approach for analyzing properties of tricyclic anti-depressant drugs.Frontiers in chemistry · 2025Article
- QSPR graph model to explore physicochemical properties of potential antiviral drugs of dengue disease through novel coloring-based topological indices.Frontiers in chemistry · 2025Article
- Article
- A comparative study of topological entropy characterization and graph energy prediction for Marta variants of covalent organic frameworks.Frontiers in chemistry · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Topological indices are molecular descriptors used in QSPR modelling to predict the physicochemical properties of molecules. Topological indices are used in numerous applications in drug design. In this work, we compute the neighbourhood degree-based topological indices of 15 antituberculosis drugs, we studied the QSPR analysis of these drugs using support vector regression. The efficiency of support vector regression is determined by comparing it with the classical linear regression. Our QSPR model further shows the superiority of the SVR model as a better predictive model in QSPR analysis of the physical properties of antituberculosis drugs. The findings in this study are a further contribution to the field of chemical graph theory and drug design, providing a deeper understanding of neighbourhood degree-based topological indices and their predictive capabilities in QSPR model.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.