ArticleBioMed research international2014
iCTX-type: a sequence-based predictor for identifying the types of conotoxins in targeting ion channels.
Article in BioMed research international, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers.
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Who cites it
68 citing papers in PubMed, 225 citations in OpenAlex.
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- In Silico Conotoxin Studies: Progress and Prospects.Molecules (Basel, Switzerland) · 2024Review
- Protein subcellular localization prediction tools.Computational and structural biotechnology journal · 2024Review
- AMPActiPred: A three-stage framework for predicting antibacterial peptides and activity levels with deep forest.Protein science : a publication of the Protein Society · 2024Article
- Peptide Toxins as Biothreats and the Potential for AI Systems to Enhance Biosecurity.Frontiers in bioengineering and biotechnology · 2022Article
- Article
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- A bioinformatic study of antimicrobial peptides identified in the Black Soldier Fly (BSF) Hermetia illucens (Diptera: Stratiomyidae).Scientific reports · 2020Article
- A Brief Survey for MicroRNA Precursor Identification Using Machine Learning Methods.Current genomics · 2020Review
- Bigram-PGK: phosphoglycerylation prediction using the technique of bigram probabilities of position specific scoring matrix.BMC molecular and cell biology · 2019Article
- Identify Lysine Neddylation Sites Using Bi-profile Bayes Feature ExtractionCurrent genomics · 2019Article
- iMethylK_pseAAC: Improving Accuracy of Lysine Methylation Sites Identification by Incorporating Statistical Moments and Position Relative Features into General PseAACCurrent genomics · 2019Article
- iSulfoTyr-PseAAC: Identify Tyrosine Sulfation Sites by Incorporating Statistical MomentsCurrent genomics · 2019Article
- EvolStruct-Phogly: incorporating structural properties and evolutionary information from profile bigrams for the phosphoglycerylation prediction.BMC genomics · 2019Article
- Snails In Silico: A Review of Computational Studies on the Conopeptides.Marine drugs · 2019Review
- HRGPred: Prediction of herbicide resistant genes with k-mer nucleotide compositional features and support vector machine.Scientific reports · 2019Article
- RAACBook: a web server of reduced amino acid alphabet for sequence-dependent inference by using Chou's five-step rule.Database : the journal of biological databases and curation · 2019Article
- Structural Variability in the RLR-MAVS Pathway and Sensitive Detection of Viral RNAs.Medicinal chemistry (Shariqah (United Arab Emirates)) · 2019Review
- Using a Classifier Fusion Strategy to Identify Anti-angiogenic Peptides.Scientific reports · 2018Article
8 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Conotoxins are small disulfide-rich neurotoxic peptides, which can bind to ion channels with very high specificity and modulate their activities. Over the last few decades, conotoxins have been the drug candidates for treating chronic pain, epilepsy, spasticity, and cardiovascular diseases. According to their functions and targets, conotoxins are generally categorized into three types: potassium-channel type, sodium-channel type, and calcium-channel types. With the avalanche of peptide sequences generated in the postgenomic age, it is urgent and challenging to develop an automated method for rapidly and accurately identifying the types of conotoxins based on their sequence information alone. To address this challenge, a new predictor, called iCTX-Type, was developed by incorporating the dipeptide occurrence frequencies of a conotoxin sequence into a 400-D (dimensional) general pseudoamino acid composition, followed by the feature optimization procedure to reduce the sample representation from 400-D to 50-D vector. The overall success rate achieved by iCTX-Type via a rigorous cross-validation was over 91%, outperforming its counterpart (RBF network). Besides, iCTX-Type is so far the only predictor in this area with its web-server available, and hence is particularly useful for most experimental scientists to get their desired results without the need to follow the complicated mathematics involved.
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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.