ArticleACS omega2021
Using Bibliometric Analysis and Machine Learning to Identify Compounds Binding to Sialidase-1.
Article in ACS omega, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 10 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
10 citing papers in PubMed, 14 citations in OpenAlex.
- Neuraminidase-1 (NEU1): Biological Roles and Therapeutic Relevance in Human Disease.Current issues in molecular biology · 2024Review
- Machine learning combines atomistic simulations to predict SARS-CoV-2 Mpro inhibitors from natural compounds.Molecular diversity · 2024Article
- Developing Treatments for Rare Diseases on a Shoestring.GEN biotechnology · 2023Article
- Learning from COVID-19: How drug hunters can prepare for the next pandemic.Drug discovery today · 2023Article
- The Impact of Artificial Intelligence in the Odyssey of Rare Diseases.Biomedicines · 2023Review
- The Commoditization of AI for Molecule Design.Artificial intelligence in the life sciences · 2022Article
- MegaSyn: Integrating Generative Molecular Design, Automated Analog Designer, and Synthetic Viability Prediction.ACS omega · 2022Article
- Phase-In to Phase-Out-Targeted, Inclusive Strategies Are Needed to Enable Full Replacement of Animal Use in the European Union.Animals : an open access journal from MDPI · 2022Article
- Berberine Alleviates Gastroesophageal Reflux-Induced Airway Hyperresponsiveness in a Transient Receptor Potential A1-Dependent Manner.Evidence-based complementary and alternative medicine : eCAM · 2022Article
- Exploring machine learning: a scientometrics approach using bibliometrix and VOSviewer.SN applied sciences · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
Rare diseases impact hundreds of millions of individuals worldwide. However, few therapies exist to treat the rare disease population because financial resources are limited, the number of patients affected is low, bioactivity data is often nonexistent, and very few animal models exist to support preclinical development efforts. Sialidosis is an ultrarare lysosomal storage disorder in which mutations in the NEU1 gene result in the deficiency of the lysosomal enzyme sialidase-1. This enzyme catalyzes the removal of sialic acid moieties from glycoproteins and glycolipids. Therefore, the defective or deficient protein leads to the buildup of sialylated glycoproteins as well as several characteristic symptoms of sialidosis including visual impairment, ataxia, hepatomegaly, dysostosis multiplex, and developmental delay. In this study, we used a bibliometric tool to generate links between lysosomal storage disease (LSD) targets and existing bioactivity data that could be curated in order to build machine learning models and screen compounds
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.