ArticleScientific reports2015
VaccineDA: Prediction, design and genome-wide screening of oligodeoxynucleotide-based vaccine adjuvants.
Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 39 citations in OpenAlex.
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- Vaccines Targeting Numerous Coronavirus Antigens, Ensuring Broader Global Population Coverage: Multi-epitope and Multi-patch Vaccines.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Artificial Intelligence in Vaccine and Drug Design.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Prediction of novel mouse TLR9 agonists using a random forest approach.BMC molecular and cell biology · 2019Article
- PRRDB 2.0: a comprehensive database of pattern-recognition receptors and their ligands.Database : the journal of biological databases and curation · 2019Article
- Computer-aided prediction of antigen presenting cell modulators for designing peptide-based vaccine adjuvants.Journal of translational medicine · 2018Article
- Prediction of Antimicrobial Potential of a Chemically Modified Peptide From Its Tertiary Structure.Frontiers in microbiology · 2018Article
- Structural basis of development of multi-epitope vaccine against Middle East respiratory syndrome using in silico approach.Infection and drug resistance · 2018Article
- Automated screening for Fragile X premutation carriers based on linguistic and cognitive computational phenotypes.Scientific reports · 2017Article
- MAHMI database: a comprehensive MetaHit-based resource for the study of the mechanism of action of the human microbiota.Database : the journal of biological databases and curation · 2017Article
- Mucosal adjuvants: Opportunities and challenges.Human vaccines & immunotherapeutics · 2016Article
- Structural Basis for Designing Multiepitope Vaccines Against COVID-19 Infection: In Silico Vaccine Design and Validation.JMIR bioinformatics and biotechnologyArticle
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Immunomodulatory oligodeoxynucleotides (IMODNs) are the short DNA sequences that activate the innate immune system via toll-like receptor 9. These sequences predominantly contain unmethylated CpG motifs. In this work, we describe VaccineDA (Vaccine DNA adjuvants), a web-based resource developed to design IMODN-based vaccine adjuvants. We collected and analyzed 2193 experimentally validated IMODNs obtained from the literature. Certain types of nucleotides (e.g., T, GT, TC, TT, CGT, TCG, TTT) are dominant in IMODNs. Based on these observations, we developed support vector machine-based models to predict IMODNs using various compositions. The developed models achieved the maximum Matthews Correlation Coefficient (MCC) of 0.75 with an accuracy of 87.57% using the pentanucleotide composition. The integration of motif information further improved the performance of our model from the MCC of 0.75 to 0.77. Similarly, models were developed to predict palindromic IMODNs and attained a maximum MCC of 0.84 with the accuracy of 91.94%. These models were evaluated using a five-fold cross-validation technique as well as validated on an independent dataset. The models developed in this study were integrated into VaccineDA to provide a wide range of services that facilitate the design of DNA-based vaccine adjuvants (http://crdd.osdd.net/raghava/vaccineda/).
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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.