ArticleJournal of chemical information and modeling2022
Prediction of Antileishmanial Compounds: General Model, Preparation, and Evaluation of 2-Acylpyrrole Derivatives.
Article in Journal of chemical information and modeling, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Computational Phenotypic Drug Discovery for Anticancer Chemotherapy: PTML Modeling of Multi-Cell Inhibitors of Colorectal Cancer Cell Lines.International journal of molecular sciences · 2025Article
- Ensemble techniques for predictive modeling of leishmanial activity via molecular fingerprints.BMC medical informatics and decision making · 2025Article
- In Silico Approach for Early Antimalarial Drug Discovery: De Novo Design of Virtual Multi-Strain Antiplasmodial Inhibitors.Microorganisms · 2025Article
- Perturbation-Theory Machine Learning for Multi-Target Drug Discovery in Modern Anticancer Research.Current issues in molecular biology · 2025Review
- In Silico Approach for Antibacterial Discovery: PTML Modeling of Virtual Multi-Strain Inhibitors AgainstPharmaceuticals (Basel, Switzerland) · 2025Article
- Artificial Intelligence-Driven Modeling for Hydrogel Three-Dimensional Printing: Computational and Experimental Cases of Study.Polymers · 2025Article
- From molecular mechanisms of prostate cancer to translational applications: based on multi-omics fusion analysis and intelligent medicine.Health information science and systems · 2024Review
- Easy one-pot synthesis of multifunctionalized indole-pyrrole hybrids as a new class of antileishmanial agents.RSC advances · 2024Article
- Anti-leishmanial effect of the hydroalcoholic extract of the leaves, roots and seeds ofAvicenna journal of phytomedicineArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this work, the SOFT.PTML tool has been used to pre-process a ChEMBL dataset of pre-clinical assays of antileishmanial compound candidates. A comparative study of different ML algorithms, such as logistic regression (LOGR), support vector machine (SVM), and random forests (RF), has shown that the IFPTML-LOGR model presents excellent values of specificity and sensitivity (81-98%) in training and validation series. The use of this software has been illustrated with a practical case study focused on a series of 28 derivatives of 2-acylpyrroles
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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.