Identification of Crucial lncRNAs, miRNAs, mRNAs, and Potential Therapeutic Compounds for Polycystic Ovary Syndrome by Bioinformatics Analysis
Background. This study was aimed at mining crucial long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) for the development of polycystic ovary syndrome (PCOS) based on the coexpression and the competitive endogenous RNA (ceRNA) theories and investigating the underlying ther...
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| description | Background. This study was aimed at mining crucial long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) for the development of polycystic ovary syndrome (PCOS) based on the coexpression and the competitive endogenous RNA (ceRNA) theories and investigating the underlying therapeutic drugs that may function by reversing the expression of lncRNAs, miRNAs, and mRNAs. Methods. RNA (GSE106724, GSE114419, GSE137684, and GSE138518) or miRNA (GSE84376 and GSE138572) expression profile datasets of PCOS patients were downloaded from the Gene Expression Omnibus database. The weighted gene coexpression network analysis (WGCNA) using four RNA datasets was conducted to construct the lncRNA-mRNA coexpression networks, while the common differentially expressed miRNAs in two miRNA datasets and module RNAs were used to establish the ceRNA network. A protein-protein interaction (PPI) network was created to explore the potential interactions between genes. Gene Ontology and KEGG pathway enrichment analyses were performed to explore the functions of genes in networks. Connectivity Map (CMap) and Comparative Toxicogenomics Database (CTD) analyses were performed to identify potential therapeutic agents for PCOS. Results. Three modules (black, magenta, and yellow) were identified to be PCOS-related after WGCNA analysis, in which KLF3-AS1-PLCG2, MAPKAPK5-AS1-MAP3K14, and WWC2-AS2-TXNIP were important coexpression relationship pairs. WWC2-AS2-hsa-miR-382-PLCG2 was a crucial ceRNA loop in the ceRNA network. The PPI network showed that MAP3K14 and TXNIP could interact with hub genes PLK1 (degree=21) and TLR1 (degree=18), respectively. These genes were enriched into mitosis (PLK1), immune response (PLCG2 and TLR1), and cell cycle (TXNIP and PLK1) biological processes. Ten small molecule drugs (especially quercetin) were considered to be therapeutical for PCOS. Conclusion. Our study may provide a novel insight into the mechanisms and therapy for PCOS. |
| doi_str_mv | 10.1155/2020/1817094 |
| format | Article |
| fullrecord | <record><control><sourceid>gale_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7666708</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A697007592</galeid><sourcerecordid>A697007592</sourcerecordid><originalsourceid>FETCH-LOGICAL-c499t-bb61239374e11e7cec12614a9e00eb16540c2017a6050c65814ab6c669e0d953</originalsourceid><addsrcrecordid>eNqNkUFv3CAUhFHVqonS3HqukHpstnmADeZSabtK2khRErV7RxjjLJENW7BT-U_kNwdrt5v2Vi4PaT6GNxqE3hP4TEhZnlOgcE4qIkAWr9AxZaRYcFKQ14c7Y0foNKUHyKciHCR_i44Yo7SQgh2jp6vG-sG1zujBBY9Di1dxNE53uPPmx80yneHe7eduaN_guzDMzzK13tiot3YcnMGr0G_D6JuE2xAz001mSrNw-6jjhH9Ovomht7ie8FcXnM9Un781CS-97qbk0jv0ptVdsqf7eYLWlxfr1ffF9e23q9XyemEKKYdFXXNCmWSisIRYYawhNMfW0gLYmvCyAEOBCM2hBMPLKms1N5xnoJElO0Ffdrbbse5tY3KWqDu1ja7Pi6qgnfpX8W6j7sOjEpxzAVU2-Lg3iOHXaNOgHsIYc4ikaMGBlyAEf6HudWfVnDebmd4lo5ZcCgBRSpqpsx1lYkgp2vawBwE1t6zmltW-5Yx_-Hv3A_yn0wx82gEb5xv92_2nnc2MbfULTRiRvGLPuke42Q</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2460650776</pqid></control><display><type>article</type><title>Identification of Crucial lncRNAs, miRNAs, mRNAs, and Potential Therapeutic Compounds for Polycystic Ovary Syndrome by Bioinformatics Analysis</title><source>MEDLINE</source><source>PubMed Central Open Access</source><source>Wiley Online Library Open Access</source><source>PubMed Central</source><source>Alma/SFX Local Collection</source><creator>Tian, Xiaohui ; Liu, Wenxiu ; Xia, Tingting ; Lin, Xia ; Zeng, Zhi ; Li, Manchao</creator><contributor>Hamdy, Nadia M. ; Nadia M Hamdy</contributor><creatorcontrib>Tian, Xiaohui ; Liu, Wenxiu ; Xia, Tingting ; Lin, Xia ; Zeng, Zhi ; Li, Manchao ; Hamdy, Nadia M. ; Nadia M Hamdy</creatorcontrib><description>Background. This study was aimed at mining crucial long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) for the development of polycystic ovary syndrome (PCOS) based on the coexpression and the competitive endogenous RNA (ceRNA) theories and investigating the underlying therapeutic drugs that may function by reversing the expression of lncRNAs, miRNAs, and mRNAs. Methods. RNA (GSE106724, GSE114419, GSE137684, and GSE138518) or miRNA (GSE84376 and GSE138572) expression profile datasets of PCOS patients were downloaded from the Gene Expression Omnibus database. The weighted gene coexpression network analysis (WGCNA) using four RNA datasets was conducted to construct the lncRNA-mRNA coexpression networks, while the common differentially expressed miRNAs in two miRNA datasets and module RNAs were used to establish the ceRNA network. A protein-protein interaction (PPI) network was created to explore the potential interactions between genes. Gene Ontology and KEGG pathway enrichment analyses were performed to explore the functions of genes in networks. Connectivity Map (CMap) and Comparative Toxicogenomics Database (CTD) analyses were performed to identify potential therapeutic agents for PCOS. Results. Three modules (black, magenta, and yellow) were identified to be PCOS-related after WGCNA analysis, in which KLF3-AS1-PLCG2, MAPKAPK5-AS1-MAP3K14, and WWC2-AS2-TXNIP were important coexpression relationship pairs. WWC2-AS2-hsa-miR-382-PLCG2 was a crucial ceRNA loop in the ceRNA network. The PPI network showed that MAP3K14 and TXNIP could interact with hub genes PLK1 (degree=21) and TLR1 (degree=18), respectively. These genes were enriched into mitosis (PLK1), immune response (PLCG2 and TLR1), and cell cycle (TXNIP and PLK1) biological processes. Ten small molecule drugs (especially quercetin) were considered to be therapeutical for PCOS. Conclusion. Our study may provide a novel insight into the mechanisms and therapy for PCOS.</description><identifier>ISSN: 2314-6133</identifier><identifier>EISSN: 2314-6141</identifier><identifier>DOI: 10.1155/2020/1817094</identifier><identifier>PMID: 33224973</identifier><language>eng</language><publisher>Cairo, Egypt: Hindawi Publishing Corporation</publisher><subject>Apoptosis ; Bioinformatics ; Biological activity ; Biomedical research ; Care and treatment ; Cell cycle ; Cell Cycle Proteins - genetics ; Chemical compounds ; Computational Biology ; Databases, Pharmaceutical ; Datasets ; Drug discovery ; Drugs ; Female ; Gene expression ; Gene Expression Regulation ; Gene Regulatory Networks ; Genes ; Genetic aspects ; Genetic Markers ; Health aspects ; High-Throughput Nucleotide Sequencing ; Humans ; Identification and classification ; Immune response ; Immunosuppressive agents ; MicroRNAs ; MicroRNAs - genetics ; miRNA ; Mitosis ; Modules ; Network analysis ; Ovaries ; Pharmacology ; Polo-Like Kinase 1 ; Polycystic ovary syndrome ; Polycystic Ovary Syndrome - drug therapy ; Polycystic Ovary Syndrome - genetics ; Protein interaction ; Protein Interaction Maps ; Protein Serine-Threonine Kinases - genetics ; Proteins ; Proto-Oncogene Proteins - genetics ; Quercetin ; Quercetin - pharmacology ; Ribonucleic acid ; RNA ; RNA, Long Noncoding - genetics ; RNA, Messenger - genetics ; Small Molecule Libraries - pharmacology ; Stein-Leventhal syndrome ; TLR1 protein ; Toll-like receptors ; Toxicogenetics</subject><ispartof>BioMed research international, 2020, Vol.2020 (2020), p.1-16</ispartof><rights>Copyright © 2020 Zhi Zeng et al.</rights><rights>COPYRIGHT 2020 John Wiley & Sons, Inc.</rights><rights>Copyright © 2020 Zhi Zeng et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0</rights><rights>Copyright © 2020 Zhi Zeng et al. 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c499t-bb61239374e11e7cec12614a9e00eb16540c2017a6050c65814ab6c669e0d953</citedby><cites>FETCH-LOGICAL-c499t-bb61239374e11e7cec12614a9e00eb16540c2017a6050c65814ab6c669e0d953</cites><orcidid>0000-0002-7999-6108 ; 0000-0001-5405-0116</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7666708/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7666708/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,4009,27902,27903,27904,53769,53771</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33224973$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Hamdy, Nadia M.</contributor><contributor>Nadia M Hamdy</contributor><creatorcontrib>Tian, Xiaohui</creatorcontrib><creatorcontrib>Liu, Wenxiu</creatorcontrib><creatorcontrib>Xia, Tingting</creatorcontrib><creatorcontrib>Lin, Xia</creatorcontrib><creatorcontrib>Zeng, Zhi</creatorcontrib><creatorcontrib>Li, Manchao</creatorcontrib><title>Identification of Crucial lncRNAs, miRNAs, mRNAs, and Potential Therapeutic Compounds for Polycystic Ovary Syndrome by Bioinformatics Analysis</title><title>BioMed research international</title><addtitle>Biomed Res Int</addtitle><description>Background. This study was aimed at mining crucial long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) for the development of polycystic ovary syndrome (PCOS) based on the coexpression and the competitive endogenous RNA (ceRNA) theories and investigating the underlying therapeutic drugs that may function by reversing the expression of lncRNAs, miRNAs, and mRNAs. Methods. RNA (GSE106724, GSE114419, GSE137684, and GSE138518) or miRNA (GSE84376 and GSE138572) expression profile datasets of PCOS patients were downloaded from the Gene Expression Omnibus database. The weighted gene coexpression network analysis (WGCNA) using four RNA datasets was conducted to construct the lncRNA-mRNA coexpression networks, while the common differentially expressed miRNAs in two miRNA datasets and module RNAs were used to establish the ceRNA network. A protein-protein interaction (PPI) network was created to explore the potential interactions between genes. Gene Ontology and KEGG pathway enrichment analyses were performed to explore the functions of genes in networks. Connectivity Map (CMap) and Comparative Toxicogenomics Database (CTD) analyses were performed to identify potential therapeutic agents for PCOS. Results. Three modules (black, magenta, and yellow) were identified to be PCOS-related after WGCNA analysis, in which KLF3-AS1-PLCG2, MAPKAPK5-AS1-MAP3K14, and WWC2-AS2-TXNIP were important coexpression relationship pairs. WWC2-AS2-hsa-miR-382-PLCG2 was a crucial ceRNA loop in the ceRNA network. The PPI network showed that MAP3K14 and TXNIP could interact with hub genes PLK1 (degree=21) and TLR1 (degree=18), respectively. These genes were enriched into mitosis (PLK1), immune response (PLCG2 and TLR1), and cell cycle (TXNIP and PLK1) biological processes. Ten small molecule drugs (especially quercetin) were considered to be therapeutical for PCOS. Conclusion. Our study may provide a novel insight into the mechanisms and therapy for PCOS.</description><subject>Apoptosis</subject><subject>Bioinformatics</subject><subject>Biological activity</subject><subject>Biomedical research</subject><subject>Care and treatment</subject><subject>Cell cycle</subject><subject>Cell Cycle Proteins - genetics</subject><subject>Chemical compounds</subject><subject>Computational Biology</subject><subject>Databases, Pharmaceutical</subject><subject>Datasets</subject><subject>Drug discovery</subject><subject>Drugs</subject><subject>Female</subject><subject>Gene expression</subject><subject>Gene Expression Regulation</subject><subject>Gene Regulatory Networks</subject><subject>Genes</subject><subject>Genetic aspects</subject><subject>Genetic Markers</subject><subject>Health aspects</subject><subject>High-Throughput Nucleotide Sequencing</subject><subject>Humans</subject><subject>Identification and classification</subject><subject>Immune response</subject><subject>Immunosuppressive agents</subject><subject>MicroRNAs</subject><subject>MicroRNAs - genetics</subject><subject>miRNA</subject><subject>Mitosis</subject><subject>Modules</subject><subject>Network analysis</subject><subject>Ovaries</subject><subject>Pharmacology</subject><subject>Polo-Like Kinase 1</subject><subject>Polycystic ovary syndrome</subject><subject>Polycystic Ovary Syndrome - drug therapy</subject><subject>Polycystic Ovary Syndrome - genetics</subject><subject>Protein interaction</subject><subject>Protein Interaction Maps</subject><subject>Protein Serine-Threonine Kinases - genetics</subject><subject>Proteins</subject><subject>Proto-Oncogene Proteins - genetics</subject><subject>Quercetin</subject><subject>Quercetin - pharmacology</subject><subject>Ribonucleic acid</subject><subject>RNA</subject><subject>RNA, Long Noncoding - genetics</subject><subject>RNA, Messenger - genetics</subject><subject>Small Molecule Libraries - pharmacology</subject><subject>Stein-Leventhal syndrome</subject><subject>TLR1 protein</subject><subject>Toll-like 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Xiaohui</creator><creator>Liu, Wenxiu</creator><creator>Xia, Tingting</creator><creator>Lin, Xia</creator><creator>Zeng, Zhi</creator><creator>Li, Manchao</creator><general>Hindawi Publishing Corporation</general><general>Hindawi</general><general>John Wiley & Sons, Inc</general><general>Hindawi 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of Crucial lncRNAs, miRNAs, mRNAs, and Potential Therapeutic Compounds for Polycystic Ovary Syndrome by Bioinformatics Analysis</title><author>Tian, Xiaohui ; Liu, Wenxiu ; Xia, Tingting ; Lin, Xia ; Zeng, Zhi ; Li, Manchao</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c499t-bb61239374e11e7cec12614a9e00eb16540c2017a6050c65814ab6c669e0d953</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Apoptosis</topic><topic>Bioinformatics</topic><topic>Biological activity</topic><topic>Biomedical research</topic><topic>Care and treatment</topic><topic>Cell cycle</topic><topic>Cell Cycle Proteins - genetics</topic><topic>Chemical compounds</topic><topic>Computational Biology</topic><topic>Databases, Pharmaceutical</topic><topic>Datasets</topic><topic>Drug discovery</topic><topic>Drugs</topic><topic>Female</topic><topic>Gene expression</topic><topic>Gene Expression Regulation</topic><topic>Gene Regulatory Networks</topic><topic>Genes</topic><topic>Genetic aspects</topic><topic>Genetic Markers</topic><topic>Health aspects</topic><topic>High-Throughput Nucleotide Sequencing</topic><topic>Humans</topic><topic>Identification and classification</topic><topic>Immune response</topic><topic>Immunosuppressive agents</topic><topic>MicroRNAs</topic><topic>MicroRNAs - genetics</topic><topic>miRNA</topic><topic>Mitosis</topic><topic>Modules</topic><topic>Network analysis</topic><topic>Ovaries</topic><topic>Pharmacology</topic><topic>Polo-Like Kinase 1</topic><topic>Polycystic ovary syndrome</topic><topic>Polycystic Ovary Syndrome - drug therapy</topic><topic>Polycystic Ovary Syndrome - genetics</topic><topic>Protein interaction</topic><topic>Protein Interaction Maps</topic><topic>Protein Serine-Threonine Kinases - genetics</topic><topic>Proteins</topic><topic>Proto-Oncogene Proteins - genetics</topic><topic>Quercetin</topic><topic>Quercetin - pharmacology</topic><topic>Ribonucleic acid</topic><topic>RNA</topic><topic>RNA, Long Noncoding - genetics</topic><topic>RNA, Messenger - genetics</topic><topic>Small Molecule Libraries - pharmacology</topic><topic>Stein-Leventhal syndrome</topic><topic>TLR1 protein</topic><topic>Toll-like receptors</topic><topic>Toxicogenetics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tian, Xiaohui</creatorcontrib><creatorcontrib>Liu, Wenxiu</creatorcontrib><creatorcontrib>Xia, Tingting</creatorcontrib><creatorcontrib>Lin, Xia</creatorcontrib><creatorcontrib>Zeng, Zhi</creatorcontrib><creatorcontrib>Li, Manchao</creatorcontrib><collection>الدوريات العلمية والإحصائية - e-Marefa Academic and Statistical Periodicals</collection><collection>معرفة - المحتوى العربي الأكاديمي المتكامل - e-Marefa Academic Complete</collection><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription 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Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>BioMed research international</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Tian, Xiaohui</au><au>Liu, Wenxiu</au><au>Xia, Tingting</au><au>Lin, Xia</au><au>Zeng, Zhi</au><au>Li, Manchao</au><au>Hamdy, Nadia M.</au><au>Nadia M Hamdy</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identification of Crucial lncRNAs, miRNAs, mRNAs, and Potential Therapeutic Compounds for Polycystic Ovary Syndrome by Bioinformatics Analysis</atitle><jtitle>BioMed research international</jtitle><addtitle>Biomed Res Int</addtitle><date>2020</date><risdate>2020</risdate><volume>2020</volume><issue>2020</issue><spage>1</spage><epage>16</epage><pages>1-16</pages><issn>2314-6133</issn><eissn>2314-6141</eissn><abstract>Background. This study was aimed at mining crucial long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) for the development of polycystic ovary syndrome (PCOS) based on the coexpression and the competitive endogenous RNA (ceRNA) theories and investigating the underlying therapeutic drugs that may function by reversing the expression of lncRNAs, miRNAs, and mRNAs. Methods. RNA (GSE106724, GSE114419, GSE137684, and GSE138518) or miRNA (GSE84376 and GSE138572) expression profile datasets of PCOS patients were downloaded from the Gene Expression Omnibus database. The weighted gene coexpression network analysis (WGCNA) using four RNA datasets was conducted to construct the lncRNA-mRNA coexpression networks, while the common differentially expressed miRNAs in two miRNA datasets and module RNAs were used to establish the ceRNA network. A protein-protein interaction (PPI) network was created to explore the potential interactions between genes. Gene Ontology and KEGG pathway enrichment analyses were performed to explore the functions of genes in networks. Connectivity Map (CMap) and Comparative Toxicogenomics Database (CTD) analyses were performed to identify potential therapeutic agents for PCOS. Results. Three modules (black, magenta, and yellow) were identified to be PCOS-related after WGCNA analysis, in which KLF3-AS1-PLCG2, MAPKAPK5-AS1-MAP3K14, and WWC2-AS2-TXNIP were important coexpression relationship pairs. WWC2-AS2-hsa-miR-382-PLCG2 was a crucial ceRNA loop in the ceRNA network. The PPI network showed that MAP3K14 and TXNIP could interact with hub genes PLK1 (degree=21) and TLR1 (degree=18), respectively. These genes were enriched into mitosis (PLK1), immune response (PLCG2 and TLR1), and cell cycle (TXNIP and PLK1) biological processes. Ten small molecule drugs (especially quercetin) were considered to be therapeutical for PCOS. Conclusion. Our study may provide a novel insight into the mechanisms and therapy for PCOS.</abstract><cop>Cairo, Egypt</cop><pub>Hindawi Publishing Corporation</pub><pmid>33224973</pmid><doi>10.1155/2020/1817094</doi><tpages>16</tpages><orcidid>https://orcid.org/0000-0002-7999-6108</orcidid><orcidid>https://orcid.org/0000-0001-5405-0116</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | BioMed research international, 2020, Vol.2020 (2020), p.1-16 |
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| source | MEDLINE; PubMed Central Open Access; Wiley Online Library Open Access; PubMed Central; Alma/SFX Local Collection |
| subjects | Apoptosis Bioinformatics Biological activity Biomedical research Care and treatment Cell cycle Cell Cycle Proteins - genetics Chemical compounds Computational Biology Databases, Pharmaceutical Datasets Drug discovery Drugs Female Gene expression Gene Expression Regulation Gene Regulatory Networks Genes Genetic aspects Genetic Markers Health aspects High-Throughput Nucleotide Sequencing Humans Identification and classification Immune response Immunosuppressive agents MicroRNAs MicroRNAs - genetics miRNA Mitosis Modules Network analysis Ovaries Pharmacology Polo-Like Kinase 1 Polycystic ovary syndrome Polycystic Ovary Syndrome - drug therapy Polycystic Ovary Syndrome - genetics Protein interaction Protein Interaction Maps Protein Serine-Threonine Kinases - genetics Proteins Proto-Oncogene Proteins - genetics Quercetin Quercetin - pharmacology Ribonucleic acid RNA RNA, Long Noncoding - genetics RNA, Messenger - genetics Small Molecule Libraries - pharmacology Stein-Leventhal syndrome TLR1 protein Toll-like receptors Toxicogenetics |
| title | Identification of Crucial lncRNAs, miRNAs, mRNAs, and Potential Therapeutic Compounds for Polycystic Ovary Syndrome by Bioinformatics Analysis |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-25T15%3A54%3A26IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Identification%20of%20Crucial%20lncRNAs,%20miRNAs,%20mRNAs,%20and%20Potential%20Therapeutic%20Compounds%20for%20Polycystic%20Ovary%20Syndrome%20by%20Bioinformatics%20Analysis&rft.jtitle=BioMed%20research%20international&rft.au=Tian,%20Xiaohui&rft.date=2020&rft.volume=2020&rft.issue=2020&rft.spage=1&rft.epage=16&rft.pages=1-16&rft.issn=2314-6133&rft.eissn=2314-6141&rft_id=info:doi/10.1155/2020/1817094&rft_dat=%3Cgale_pubme%3EA697007592%3C/gale_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2460650776&rft_id=info:pmid/33224973&rft_galeid=A697007592&rfr_iscdi=true |