ArticleFrontiers in genetics2021
iCDI-W2vCom: Identifying the Ion Channel-Drug Interaction in Cellular Networking Based on word2vec and node2vec.
Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
- Enhancing Drug Response Prediction in Epilepsy with Emerging Multimodal Models: Focus on Clinical, Pharmacologic, and Genomic Factors.CNS drugs · 2026Review
- A Robust Drug-Target Interaction Prediction Framework with Capsule Network and Transfer Learning.International journal of molecular sciences · 2023Article
- Stacking-ac4C: an ensemble model using mixed features for identifying n4-acetylcytidine in mRNA.Frontiers in immunology · 2023Article
- Learning to discover medicines.International journal of data science and analytics · 2022Review
- DTI-BERT: Identifying Drug-Target Interactions in Cellular Networking Based on BERT and Deep Learning Method.Frontiers in genetics · 2022Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ion channels are the second largest drug target family. Ion channel dysfunction may lead to a number of diseases such as Alzheimer's disease, epilepsy, cephalagra, and type II diabetes. In the research work for predicting ion channel-drug, computational approaches are effective and efficient compared with the costly, labor-intensive, and time-consuming experimental methods. Most of the existing methods can only be used to deal with the ion channels of knowing 3D structures; however, the 3D structures of most ion channels are still unknown. Many predictors based on protein sequence were developed to address the challenge, while most of their results need to be improved, or predicting web servers are missing. In this paper, a sequence-based classifier, called "iCDI-W2vCom," was developed to identify the interactions between ion channels and drugs. In the predictor, the drug compound was formulated by SMILES-word2vec, FP2-word2vec, SMILES-node2vec, and ECFPs
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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.