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Research Article
Finding Prediction of Interaction between SARS-CoV-2 and Human Protein: A Data Driven Approach
Kartick Chandra Mondal
Jadavpur University
Corresponding Author
ORCiD: https://orcid.org/0000-0003-3647-5799
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This work is licensed under a CC BY 4.0 License. Read Full License
Declarations:
Declarations
- This study involved human subjects.
- The author confirmed that all appropriate ethical guidelines for the use of human subjects have been followed, any necessary IRB and/or ethics committee review has been obtained, and information about the IRB/ethics committee is included in the manuscript.
- The author has confirmed that all necessary patient/participant consent or assent has been obtained and the appropriate institutional forms have been archived. If the IRB/ethics committee waived the requirement for patient/participant consent or assent, an explanation for the waiver is included in the text.
- The author has confirmed that a statement listing potential conflicts of interest or lack thereof is included in the text.
COVID-19 pandemic defined a worldwide health crisis into a humanitarian crisis. Amid this global emergency, human civilization is under enormous strain since no proper therapeutic method is discovered yet. A wave of research effort has been put towards the invention of therapeutics and vaccines against COVID-19. Contrarily, the spread of this fatal virus has already infected millions of people and claimed many lives all over the world. Computational biology can attempt to understand the protein-protein interactions between the viral protein and host protein. Therefore potential viral-host protein interactions can be identified which is known as crucial information towards the discovery of drugs. In this paper, we have presented an approach for predicting novel interactions from maximal biclusters. Additionally, the predicted interactions are verified from biological perspectives. For this, we conduct a study on the gene ontology and KEGG pathway in relation to the newly predicted interactions.
Keywords
Biclusters, Association Rule, Protein-Protein Interactions, COVID-19
Figure 1
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This is a list of supplementary files associated with this preprint. Click to download.
- PPICOVIDHUMAN.csv
COVID-Human protein- protein interaction database
- PPICOVIDHUMANT.csv
Transposed COVID-Human protei-protein interaction database
- FinalPredictedInteractions.xlsx
Predicted list of interactions found
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This is a preprint. It has not completed peer review.
Research Article
Finding Prediction of Interaction between SARS-CoV-2 and Human Protein: A Data Driven Approach
Kartick Chandra Mondal
Jadavpur University
Corresponding Author
ORCiD: https://orcid.org/0000-0003-3647-5799
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 17 Sep, 2020
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Declarations:
Declarations
- This study involved human subjects.
- The author confirmed that all appropriate ethical guidelines for the use of human subjects have been followed, any necessary IRB and/or ethics committee review has been obtained, and information about the IRB/ethics committee is included in the manuscript.
- The author has confirmed that all necessary patient/participant consent or assent has been obtained and the appropriate institutional forms have been archived. If the IRB/ethics committee waived the requirement for patient/participant consent or assent, an explanation for the waiver is included in the text.
- The author has confirmed that a statement listing potential conflicts of interest or lack thereof is included in the text.
COVID-19 pandemic defined a worldwide health crisis into a humanitarian crisis. Amid this global emergency, human civilization is under enormous strain since no proper therapeutic method is discovered yet. A wave of research effort has been put towards the invention of therapeutics and vaccines against COVID-19. Contrarily, the spread of this fatal virus has already infected millions of people and claimed many lives all over the world. Computational biology can attempt to understand the protein-protein interactions between the viral protein and host protein. Therefore potential viral-host protein interactions can be identified which is known as crucial information towards the discovery of drugs. In this paper, we have presented an approach for predicting novel interactions from maximal biclusters. Additionally, the predicted interactions are verified from biological perspectives. For this, we conduct a study on the gene ontology and KEGG pathway in relation to the newly predicted interactions.
Figure 1
Figure 2