INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
This research paper presents an in-depth investigation into the
prediction of protein-protein interactions (PPIs) using a combination of
traditional machine learning and advanced deep learning methods. The study
explores the development and evaluation of predictive models, assesses their
performance, and discusses potential applications in biological research and
drug discovery
Keywords:
Protein-Protein Interaction (PPI) Prediction, SARS-CoV-2 Interactions, Machine Learning Models, Deep Learning Approaches, Data Preprocessing, Feature Engineering, Random Forest Classifier, Support Vector Machine (SVM), ROC Curve Analysis, Confusion Matrix, Precision-Recall Curve, Biological Data Integration, Research on SARS-CoV-2, Computational Biology, Bioinformatics, Data Visualization
Cite Article:
"Predicting SARS-CoV-2 Protein Interactions: Insights from Machine Learning ", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 11, page no.c804-c812, November-2023, Available :http://www.ijnrd.org/papers/IJNRD2311298.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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