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Up-Regulated Proteins Have More Protein–Protein Interactions than Down-Regulated Proteins
Microarray technology has been successfully used in many biology studies to solve the protein–protein interaction (PPI) prediction computationally. For normal tissue, the cell regulation process begins with transcription and ends with the translation process. However, when cell regulation activity g...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9552713/ https://www.ncbi.nlm.nih.gov/pubmed/36221012 http://dx.doi.org/10.1007/s10930-022-10081-6 |
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author | Dey, Lopamudra Chakraborty, Sanjay Pandey, Saroj Kumar |
author_facet | Dey, Lopamudra Chakraborty, Sanjay Pandey, Saroj Kumar |
author_sort | Dey, Lopamudra |
collection | PubMed |
description | Microarray technology has been successfully used in many biology studies to solve the protein–protein interaction (PPI) prediction computationally. For normal tissue, the cell regulation process begins with transcription and ends with the translation process. However, when cell regulation activity goes wrong, cancer occurs. Microarray data can precisely give high accuracy expression levels at normal and cancer-affected cells, which can be useful for the identification of disease-related genes. First, the differentially expressed genes (DEGs) are extracted from the cancer microarray dataset in order to identify the genes that are up-regulated and down-regulated during cancer progression in the human body. Then, proteins corresponding to these genes are collected from NCBI, and then the STRING web server is used to build the PPI network of these proteins. Interestingly, up-regulated proteins have always a higher number of PPIs compared to down-regulated proteins, although, in most of the datasets, the majority of these DEGs are down-regulated. We hope this study will help to build a relevant model to analyze the process of cancer progression in the human body. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10930-022-10081-6. |
format | Online Article Text |
id | pubmed-9552713 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-95527132022-10-11 Up-Regulated Proteins Have More Protein–Protein Interactions than Down-Regulated Proteins Dey, Lopamudra Chakraborty, Sanjay Pandey, Saroj Kumar Protein J Article Microarray technology has been successfully used in many biology studies to solve the protein–protein interaction (PPI) prediction computationally. For normal tissue, the cell regulation process begins with transcription and ends with the translation process. However, when cell regulation activity goes wrong, cancer occurs. Microarray data can precisely give high accuracy expression levels at normal and cancer-affected cells, which can be useful for the identification of disease-related genes. First, the differentially expressed genes (DEGs) are extracted from the cancer microarray dataset in order to identify the genes that are up-regulated and down-regulated during cancer progression in the human body. Then, proteins corresponding to these genes are collected from NCBI, and then the STRING web server is used to build the PPI network of these proteins. Interestingly, up-regulated proteins have always a higher number of PPIs compared to down-regulated proteins, although, in most of the datasets, the majority of these DEGs are down-regulated. We hope this study will help to build a relevant model to analyze the process of cancer progression in the human body. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10930-022-10081-6. Springer US 2022-10-11 2022 /pmc/articles/PMC9552713/ /pubmed/36221012 http://dx.doi.org/10.1007/s10930-022-10081-6 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Dey, Lopamudra Chakraborty, Sanjay Pandey, Saroj Kumar Up-Regulated Proteins Have More Protein–Protein Interactions than Down-Regulated Proteins |
title | Up-Regulated Proteins Have More Protein–Protein Interactions than Down-Regulated Proteins |
title_full | Up-Regulated Proteins Have More Protein–Protein Interactions than Down-Regulated Proteins |
title_fullStr | Up-Regulated Proteins Have More Protein–Protein Interactions than Down-Regulated Proteins |
title_full_unstemmed | Up-Regulated Proteins Have More Protein–Protein Interactions than Down-Regulated Proteins |
title_short | Up-Regulated Proteins Have More Protein–Protein Interactions than Down-Regulated Proteins |
title_sort | up-regulated proteins have more protein–protein interactions than down-regulated proteins |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9552713/ https://www.ncbi.nlm.nih.gov/pubmed/36221012 http://dx.doi.org/10.1007/s10930-022-10081-6 |
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