Finding the association of mRNA and miRNA using Next Generation Sequencing data of Kidney renal cell carcinoma
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10174/22983 |
Resumo: | MicroRNAs (miRNAs) are a class of 22-nucleotide endogenous noncod- ing RNAs, plays important role in regulating target gene expression via repress- ing translation or promoting messenger RNAs (mRNA) degradation. Numerous re- searchers have found that miRNAs have serious effects on cancer. Therefore, study of mRNAs and miRNAs together through the integrated analysis of mRNA and miRNA expression profiling could help us in getting a deeper insight into the can- cer research. In this regards, High-Throughput Sequencing data of Kidney renal cell carcinoma is used here. The proposed method focuses on identifying mRNA- miRNA pair that has a signature in kidney tumor sample. For this analysis, Ran- dom Forests, Particle Swarm Optimization and Support Vector Machine classifier is used to have best sets of mRNAs-miRNA pairs. Additionally, the significance of selected mRNA-miRNA pairs is tested using gene ontology and pathway analysis tools. Moreover, the selected mRNA-miRNA pairs are searched based on changes in expression values of the used mRNA and miRNA dataset. |
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Finding the association of mRNA and miRNA using Next Generation Sequencing data of Kidney renal cell carcinomamRNAmiRNANext Generation SequencingParticle Swarm OptimizationRandom ForestMicroRNAs (miRNAs) are a class of 22-nucleotide endogenous noncod- ing RNAs, plays important role in regulating target gene expression via repress- ing translation or promoting messenger RNAs (mRNA) degradation. Numerous re- searchers have found that miRNAs have serious effects on cancer. Therefore, study of mRNAs and miRNAs together through the integrated analysis of mRNA and miRNA expression profiling could help us in getting a deeper insight into the can- cer research. In this regards, High-Throughput Sequencing data of Kidney renal cell carcinoma is used here. The proposed method focuses on identifying mRNA- miRNA pair that has a signature in kidney tumor sample. For this analysis, Ran- dom Forests, Particle Swarm Optimization and Support Vector Machine classifier is used to have best sets of mRNAs-miRNA pairs. Additionally, the significance of selected mRNA-miRNA pairs is tested using gene ontology and pathway analysis tools. Moreover, the selected mRNA-miRNA pairs are searched based on changes in expression values of the used mRNA and miRNA dataset.Sikkim Manipal Institute of Technology2018-03-14T12:30:56Z2018-03-142017-09-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjecthttp://hdl.handle.net/10174/22983http://hdl.handle.net/10174/22983engBhowmick, Shib Sankar, Rato, L. and Bhattacharjee, D. “Finding the association of mRNA and miRNA using Next Generation Sequencing data of Kidney renal cell carcinoma”, First International Conference onsimnaonaondlmr@uevora.ptnd498Bhowmick, Shib SankarRato, LuisBhattacharjee, Debotoshinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-03T19:14:43Zoai:dspace.uevora.pt:10174/22983Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:13:54.038015Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Finding the association of mRNA and miRNA using Next Generation Sequencing data of Kidney renal cell carcinoma |
title |
Finding the association of mRNA and miRNA using Next Generation Sequencing data of Kidney renal cell carcinoma |
spellingShingle |
Finding the association of mRNA and miRNA using Next Generation Sequencing data of Kidney renal cell carcinoma Bhowmick, Shib Sankar mRNA miRNA Next Generation Sequencing Particle Swarm Optimization Random Forest |
title_short |
Finding the association of mRNA and miRNA using Next Generation Sequencing data of Kidney renal cell carcinoma |
title_full |
Finding the association of mRNA and miRNA using Next Generation Sequencing data of Kidney renal cell carcinoma |
title_fullStr |
Finding the association of mRNA and miRNA using Next Generation Sequencing data of Kidney renal cell carcinoma |
title_full_unstemmed |
Finding the association of mRNA and miRNA using Next Generation Sequencing data of Kidney renal cell carcinoma |
title_sort |
Finding the association of mRNA and miRNA using Next Generation Sequencing data of Kidney renal cell carcinoma |
author |
Bhowmick, Shib Sankar |
author_facet |
Bhowmick, Shib Sankar Rato, Luis Bhattacharjee, Debotosh |
author_role |
author |
author2 |
Rato, Luis Bhattacharjee, Debotosh |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Bhowmick, Shib Sankar Rato, Luis Bhattacharjee, Debotosh |
dc.subject.por.fl_str_mv |
mRNA miRNA Next Generation Sequencing Particle Swarm Optimization Random Forest |
topic |
mRNA miRNA Next Generation Sequencing Particle Swarm Optimization Random Forest |
description |
MicroRNAs (miRNAs) are a class of 22-nucleotide endogenous noncod- ing RNAs, plays important role in regulating target gene expression via repress- ing translation or promoting messenger RNAs (mRNA) degradation. Numerous re- searchers have found that miRNAs have serious effects on cancer. Therefore, study of mRNAs and miRNAs together through the integrated analysis of mRNA and miRNA expression profiling could help us in getting a deeper insight into the can- cer research. In this regards, High-Throughput Sequencing data of Kidney renal cell carcinoma is used here. The proposed method focuses on identifying mRNA- miRNA pair that has a signature in kidney tumor sample. For this analysis, Ran- dom Forests, Particle Swarm Optimization and Support Vector Machine classifier is used to have best sets of mRNAs-miRNA pairs. Additionally, the significance of selected mRNA-miRNA pairs is tested using gene ontology and pathway analysis tools. Moreover, the selected mRNA-miRNA pairs are searched based on changes in expression values of the used mRNA and miRNA dataset. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-09-01T00:00:00Z 2018-03-14T12:30:56Z 2018-03-14 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10174/22983 http://hdl.handle.net/10174/22983 |
url |
http://hdl.handle.net/10174/22983 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Bhowmick, Shib Sankar, Rato, L. and Bhattacharjee, D. “Finding the association of mRNA and miRNA using Next Generation Sequencing data of Kidney renal cell carcinoma”, First International Conference on sim nao nao nd lmr@uevora.pt nd 498 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Sikkim Manipal Institute of Technology |
publisher.none.fl_str_mv |
Sikkim Manipal Institute of Technology |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799136621155581952 |