ArticleBioMed research international2016
Identifying the Types of Ion Channel-Targeted Conotoxins by Incorporating New Properties of Residues into Pseudo Amino Acid Composition.
Article in BioMed research international, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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.
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Who cites it
11 citing papers in PubMed, 16 citations in OpenAlex.
- Prediction of Specificity of α-Conotoxins to Subtypes of Human Nicotinic Acetylcholine Receptors with Semi-supervised Machine Learning.ACS chemical neuroscience · 2025Article
- Review
- In Silico Conotoxin Studies: Progress and Prospects.Molecules (Basel, Switzerland) · 2024Review
- Identification of Novel Conotoxin Precursors from the Cone SnailMarine drugs · 2021Article
- Snails In Silico: A Review of Computational Studies on the Conopeptides.Marine drugs · 2019Review
- Review
- Machine learning in pain research.Pain · 2018Review
- Computational Studies of Snake Venom Toxins.Toxins · 2017Review
- A Transcriptomic Survey of Ion Channel-Based Conotoxins in the Chinese Tubular Cone Snail (Conus betulinus).Marine drugs · 2017Article
- Recent Advances in Conotoxin Classification by Using Machine Learning Methods.Molecules (Basel, Switzerland) · 2017Review
- Predicting the Types of Ion Channel-Targeted Conotoxins Based on AVC-SVM Model.BioMed research international · 2017Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Conotoxins are a kind of neurotoxin which can specifically interact with potassium, sodium type, and calcium channels. They have become potential drug candidates to treat diseases such as chronic pain, epilepsy, and cardiovascular diseases. Thus, correctly identifying the types of ion channel-targeted conotoxins will provide important clue to understand their function and find potential drugs. Based on this consideration, we developed a new computational method to rapidly and accurately predict the types of ion-targeted conotoxins. Three kinds of new properties of residues were proposed to use in pseudo amino acid composition to formulate conotoxins samples. The support vector machine was utilized as classifier. A feature selection technique based on F-score was used to optimize features. Jackknife cross-validated results showed that the overall accuracy of 94.6% was achieved, which is higher than other published results, demonstrating that the proposed method is superior to published methods. Hence the current method may play a complementary role to other existing methods for recognizing the types of ion-target conotoxins.
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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.