10.46243/jst.2022.v7.i02.pp112-120 registered
STUDY OF COVID-19 AND PREDICTION OF FUTURE MODEL USING MACHINE LEARNING
Resolves to https://www.jst.org.in/index.php/pub/article/view/395
Held by Longman Publishers (India) · prefix 10.46243 live · DOI address https://doi.org/10.46243/jst.2022.v7.i02.pp112-120
Registered 29 Sep 2026 via crossref · record version 2 · last change 29 Sep 2026, 11:59 PM · record sha256 4e9c35b728c8b999…
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What the DOI identifies
JournalArticle — an article in a journal · Digital · Visual · en
STUDY OF COVID-19 AND PREDICTION OF FUTURE MODEL USING MACHINE LEARNING (PrincipalTitle)
Published 2022-07-03
Part of Journal of Science & Technology · ISSN 2456-5660 · volume 7 · issue 2 · pages 112–120
Agents
- Ravindra Nath Ravindra Nath (author)
- Longman Publishers (publisher)
Identifiers DOI 10.46243/jst.2022.v7.i02.pp112-120
Abstract
SARS-CoV-2, a novel coronavirus mostly known as COVID -19 has created a global pandemic. The world is now immobilized by this infectious RNA virus. This RNA virus has the ability to do the mutation in the human body. This study explores the mutation rate of the whole genomic sequence gathered from the patient's dataset of different countries. The collected dataset is processed to determine the nucleotide mutation and codon mutation separately. It has been found that a huge amount of Thymine (T) and Adenine (A) are mutated to other nucleotides for all regions, but codons are not frequently muta ting like nucleotides. Using this training and testing process, the nucleotide mutation rate of 400th patient in future time has been predicted. About 0.1% increment in mutation rate is found for mutating of nucleotides from T to C and G, C to G and G to T . While a decrement of 0.1% is seen for mutating of T to A, and A to C. It is found that this model can be used to predict day basis mutation rates if more patient data is available in updated time
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Each element by the standard's name (Annex B: reference elements, then administrative) and the Handbook's (in grey), read off the record above.
| Element | Value | In the record |
|---|---|---|
| DOI Name DOI name | 10.46243/jst.2022.v7.i02.pp112-120 | doi |
| Referent Type referentType | Creation | referent |
| Referent Sub-Type referentSubType | JournalArticle — an article in a journal | type |
| Referent Name(s) referentName(s) | STUDY OF COVID-19 AND PREDICTION OF FUTURE MODEL USING MACHINE LEARNING (PrincipalTitle, en) | titles |
| Basic Metadata basicMetadata | author: Ravindra Nath Ravindra Nath publisher: Longman Publishers published: 2022-07-03 part of: Journal of Science & Technology · ISSN 2456-5660 · vol. 7 · no. 2 · pp. 112–120 language: en form: Digital · Visual · Language | agents, dates, container, language, structural_type, modes, characters |
| Referent Identifier(s) alternateIdentifier(s) | none besides the DOI | identifiers, relations (IsSameAs) |
| Registration Authority registrationAuthorityCode | Crossref — issued by Crossref (member 25296); held here as a copy | record.source_agency (our code, ra_doi_name, for names issued here once appointed) |
| Created Date issueDate | 2024-02-16 | record.registered (when the DOI name was first registered) |
| relatedIdentifiers | none needed — the descriptive metadata is in this record | container, relations (only where the descriptive metadata lives at another identifier) |
complete Every System Metadata element is here, with the basic metadata a journal article needs.
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Every change to this DOI, in order, as it was recorded. Entries are only ever added, never changed or removed.
| # | When | What | By | Changes |
|---|---|---|---|---|
| 1 | 29 Sep 2026, 10:00 PM | register registered at Crossref; record read from api.crossref.org | Administrator (admin) | 121 fields set · sha256 803641617898… |
| 2 | 29 Sep 2026, 11:59 PM | update record re-read from api.crossref.org | Administrator (admin) | container.titles.0.value: |
Machine-readable: the history as JSON, with the full record after each change.
