SPMLMI: predicting lncRNA–miRNA interactions in humans using a structural perturbation method Article Swipe
Mingmin Xu
,
Yuanyuan Chen
,
Wei Lü
,
Lingpeng Kong
,
Jingya Fang
,
Zutan Li
,
Liangyun Zhang
,
Cong Pian
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.7717/peerj.11426
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.7717/peerj.11426
Long non-coding RNA (lncRNA)–microRNA (miRNA) interactions are quickly emerging as important mechanisms underlying the functions of non-coding RNAs. Accordingly, predicting lncRNA–miRNA interactions provides an important basis for understanding the mechanisms of action of ncRNAs. However, the accuracy of the established prediction methods is still limited. In this study, we used structural consistency to measure the predictability of interactive links based on a bilayer network by integrating information for known lncRNA–miRNA interactions, an lncRNA similarity network, and an miRNA similarity network. In particular, by using the structural perturbation method, we proposed a framework called SPMLMI to predict potential lncRNA–miRNA interactions based on the bilayer network. We found that the structural consistency of the bilayer network was higher than that of any single network, supporting the utility of bilayer network construction for the prediction of lncRNA–miRNA interactions. Applying SPMLMI to three real datasets, we obtained areas under the curves of 0.9512 ± 0.0034, 0.8767 ± 0.0033, and 0.8653 ± 0.0021 based on 5-fold cross-validation, suggesting good model performance. In addition, the generalizability of SPMLMI was better than that of the previously established methods. Case studies of two lncRNAs (i.e., SNHG14 and MALAT1) further demonstrated the feasibility and effectiveness of the method. Therefore, SPMLMI is a feasible approach to identify novel lncRNA–miRNA interactions underlying complex biological processes.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.7717/peerj.11426
- OA Status
- gold
- Cited By
- 11
- References
- 52
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3163354774
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3163354774Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.7717/peerj.11426Digital Object Identifier
- Title
-
SPMLMI: predicting lncRNA–miRNA interactions in humans using a structural perturbation methodWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-05-19Full publication date if available
- Authors
-
Mingmin Xu, Yuanyuan Chen, Wei Lü, Lingpeng Kong, Jingya Fang, Zutan Li, Liangyun Zhang, Cong PianList of authors in order
- Landing page
-
https://doi.org/10.7717/peerj.11426Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.7717/peerj.11426Direct OA link when available
- Concepts
-
Computer science, Generalizability theory, Computational biology, Predictability, Data mining, Artificial intelligence, Machine learning, Biology, Mathematics, StatisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
11Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 2, 2023: 6, 2022: 2Per-year citation counts (last 5 years)
- References (count)
-
52Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W3163354774 |
|---|---|
| doi | https://doi.org/10.7717/peerj.11426 |
| ids.doi | https://doi.org/10.7717/peerj.11426 |
| ids.mag | 3163354774 |
| ids.openalex | https://openalex.org/W3163354774 |
| fwci | 1.06767593 |
| type | article |
| title | SPMLMI: predicting lncRNA–miRNA interactions in humans using a structural perturbation method |
| awards[0].id | https://openalex.org/G1461284978 |
| awards[0].funder_id | https://openalex.org/F4320325211 |
| awards[0].display_name | |
| awards[0].funder_award_id | 050/804009 |
| awards[0].funder_display_name | Nanjing Agricultural University |
| awards[1].id | https://openalex.org/G2792815973 |
| awards[1].funder_id | https://openalex.org/F4320321001 |
| awards[1].display_name | |
| awards[1].funder_award_id | 11571173 |
| awards[1].funder_display_name | National Natural Science Foundation of China |
| biblio.issue | |
| biblio.volume | 9 |
| biblio.last_page | e11426 |
| biblio.first_page | e11426 |
| topics[0].id | https://openalex.org/T10515 |
| topics[0].field.id | https://openalex.org/fields/13 |
| topics[0].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[0].score | 1.0 |
| topics[0].domain.id | https://openalex.org/domains/1 |
| topics[0].domain.display_name | Life Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1306 |
| topics[0].subfield.display_name | Cancer Research |
| topics[0].display_name | Cancer-related molecular mechanisms research |
| topics[1].id | https://openalex.org/T11482 |
| topics[1].field.id | https://openalex.org/fields/13 |
| topics[1].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[1].score | 0.9922000169754028 |
| topics[1].domain.id | https://openalex.org/domains/1 |
| topics[1].domain.display_name | Life Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1312 |
| topics[1].subfield.display_name | Molecular Biology |
| topics[1].display_name | RNA modifications and cancer |
| topics[2].id | https://openalex.org/T10604 |
| topics[2].field.id | https://openalex.org/fields/13 |
| topics[2].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[2].score | 0.9909999966621399 |
| topics[2].domain.id | https://openalex.org/domains/1 |
| topics[2].domain.display_name | Life Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1312 |
| topics[2].subfield.display_name | Molecular Biology |
| topics[2].display_name | RNA Research and Splicing |
| funders[0].id | https://openalex.org/F4320321001 |
| funders[0].ror | https://ror.org/01h0zpd94 |
| funders[0].display_name | National Natural Science Foundation of China |
| funders[1].id | https://openalex.org/F4320325211 |
| funders[1].ror | https://ror.org/05td3s095 |
| funders[1].display_name | Nanjing Agricultural University |
| is_xpac | False |
| apc_list.value | 1395 |
| apc_list.currency | USD |
| apc_list.value_usd | 1395 |
| apc_paid.value | 1395 |
| apc_paid.currency | USD |
| apc_paid.value_usd | 1395 |
| concepts[0].id | https://openalex.org/C41008148 |
| concepts[0].level | 0 |
| concepts[0].score | 0.6477994918823242 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[0].display_name | Computer science |
| concepts[1].id | https://openalex.org/C27158222 |
| concepts[1].level | 2 |
| concepts[1].score | 0.5982677340507507 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q5532422 |
| concepts[1].display_name | Generalizability theory |
| concepts[2].id | https://openalex.org/C70721500 |
| concepts[2].level | 1 |
| concepts[2].score | 0.4867441654205322 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q177005 |
| concepts[2].display_name | Computational biology |
| concepts[3].id | https://openalex.org/C197640229 |
| concepts[3].level | 2 |
| concepts[3].score | 0.4668130874633789 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q2534066 |
| concepts[3].display_name | Predictability |
| concepts[4].id | https://openalex.org/C124101348 |
| concepts[4].level | 1 |
| concepts[4].score | 0.4614746570587158 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q172491 |
| concepts[4].display_name | Data mining |
| concepts[5].id | https://openalex.org/C154945302 |
| concepts[5].level | 1 |
| concepts[5].score | 0.35675257444381714 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[5].display_name | Artificial intelligence |
| concepts[6].id | https://openalex.org/C119857082 |
| concepts[6].level | 1 |
| concepts[6].score | 0.3278973698616028 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q2539 |
| concepts[6].display_name | Machine learning |
| concepts[7].id | https://openalex.org/C86803240 |
| concepts[7].level | 0 |
| concepts[7].score | 0.24343809485435486 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[7].display_name | Biology |
| concepts[8].id | https://openalex.org/C33923547 |
| concepts[8].level | 0 |
| concepts[8].score | 0.16746580600738525 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[8].display_name | Mathematics |
| concepts[9].id | https://openalex.org/C105795698 |
| concepts[9].level | 1 |
| concepts[9].score | 0.0 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q12483 |
| concepts[9].display_name | Statistics |
| keywords[0].id | https://openalex.org/keywords/computer-science |
| keywords[0].score | 0.6477994918823242 |
| keywords[0].display_name | Computer science |
| keywords[1].id | https://openalex.org/keywords/generalizability-theory |
| keywords[1].score | 0.5982677340507507 |
| keywords[1].display_name | Generalizability theory |
| keywords[2].id | https://openalex.org/keywords/computational-biology |
| keywords[2].score | 0.4867441654205322 |
| keywords[2].display_name | Computational biology |
| keywords[3].id | https://openalex.org/keywords/predictability |
| keywords[3].score | 0.4668130874633789 |
| keywords[3].display_name | Predictability |
| keywords[4].id | https://openalex.org/keywords/data-mining |
| keywords[4].score | 0.4614746570587158 |
| keywords[4].display_name | Data mining |
| keywords[5].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[5].score | 0.35675257444381714 |
| keywords[5].display_name | Artificial intelligence |
| keywords[6].id | https://openalex.org/keywords/machine-learning |
| keywords[6].score | 0.3278973698616028 |
| keywords[6].display_name | Machine learning |
| keywords[7].id | https://openalex.org/keywords/biology |
| keywords[7].score | 0.24343809485435486 |
| keywords[7].display_name | Biology |
| keywords[8].id | https://openalex.org/keywords/mathematics |
| keywords[8].score | 0.16746580600738525 |
| keywords[8].display_name | Mathematics |
| language | en |
| locations[0].id | doi:10.7717/peerj.11426 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S1983995261 |
| locations[0].source.issn | 2167-8359 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2167-8359 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | PeerJ |
| locations[0].source.host_organization | https://openalex.org/P4310320104 |
| locations[0].source.host_organization_name | PeerJ, Inc. |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310320104 |
| locations[0].source.host_organization_lineage_names | PeerJ, Inc. |
| locations[0].license | cc-by |
| locations[0].pdf_url | |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | PeerJ |
| locations[0].landing_page_url | https://doi.org/10.7717/peerj.11426 |
| locations[1].id | pmh:oai:doaj.org/article:5eb889de82e74bd19bca4b71a6205a44 |
| locations[1].is_oa | True |
| locations[1].source.id | https://openalex.org/S4306401280 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[1].source.host_organization | |
| locations[1].source.host_organization_name | |
| locations[1].license | cc-by-sa |
| locations[1].pdf_url | |
| locations[1].version | submittedVersion |
| locations[1].raw_type | article |
| locations[1].license_id | https://openalex.org/licenses/cc-by-sa |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | PeerJ, Vol 9, p e11426 (2021) |
| locations[1].landing_page_url | https://doaj.org/article/5eb889de82e74bd19bca4b71a6205a44 |
| locations[2].id | pmh:oai:pubmedcentral.nih.gov:8140594 |
| locations[2].is_oa | True |
| locations[2].source.id | https://openalex.org/S2764455111 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | False |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | PubMed Central |
| locations[2].source.host_organization | https://openalex.org/I1299303238 |
| locations[2].source.host_organization_name | National Institutes of Health |
| locations[2].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[2].license | other-oa |
| locations[2].pdf_url | |
| locations[2].version | submittedVersion |
| locations[2].raw_type | Text |
| locations[2].license_id | https://openalex.org/licenses/other-oa |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | PeerJ |
| locations[2].landing_page_url | https://www.ncbi.nlm.nih.gov/pmc/articles/8140594 |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A5102950229 |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | Mingmin Xu |
| authorships[0].countries | CN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I119454577 |
| authorships[0].affiliations[0].raw_affiliation_string | College of Agriculture, Nanjing Agricultural University, Nanjing, Jiangsu, China |
| authorships[0].institutions[0].id | https://openalex.org/I119454577 |
| authorships[0].institutions[0].ror | https://ror.org/05td3s095 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I119454577 |
| authorships[0].institutions[0].country_code | CN |
| authorships[0].institutions[0].display_name | Nanjing Agricultural University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Mingmin Xu |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | College of Agriculture, Nanjing Agricultural University, Nanjing, Jiangsu, China |
| authorships[1].author.id | https://openalex.org/A5100437877 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-7953-1845 |
| authorships[1].author.display_name | Yuanyuan Chen |
| authorships[1].countries | CN |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I119454577 |
| authorships[1].affiliations[0].raw_affiliation_string | College of Sciences, Nanjing Agricultural University, Nanjing, Jiangsu, China |
| authorships[1].institutions[0].id | https://openalex.org/I119454577 |
| authorships[1].institutions[0].ror | https://ror.org/05td3s095 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I119454577 |
| authorships[1].institutions[0].country_code | CN |
| authorships[1].institutions[0].display_name | Nanjing Agricultural University |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Yuanyuan Chen |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | College of Sciences, Nanjing Agricultural University, Nanjing, Jiangsu, China |
| authorships[2].author.id | https://openalex.org/A5101664461 |
| authorships[2].author.orcid | https://orcid.org/0000-0001-6922-0130 |
| authorships[2].author.display_name | Wei Lü |
| authorships[2].countries | CN |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I119454577 |
| authorships[2].affiliations[0].raw_affiliation_string | College of Life Sciences, Nanjing Agricultural University, Nanjing, Jiangsu, China |
| authorships[2].institutions[0].id | https://openalex.org/I119454577 |
| authorships[2].institutions[0].ror | https://ror.org/05td3s095 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I119454577 |
| authorships[2].institutions[0].country_code | CN |
| authorships[2].institutions[0].display_name | Nanjing Agricultural University |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Wei Lu |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | College of Life Sciences, Nanjing Agricultural University, Nanjing, Jiangsu, China |
| authorships[3].author.id | https://openalex.org/A5101497114 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-9407-7193 |
| authorships[3].author.display_name | Lingpeng Kong |
| authorships[3].countries | CN |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I119454577 |
| authorships[3].affiliations[0].raw_affiliation_string | College of Agriculture, Nanjing Agricultural University, Nanjing, Jiangsu, China |
| authorships[3].institutions[0].id | https://openalex.org/I119454577 |
| authorships[3].institutions[0].ror | https://ror.org/05td3s095 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I119454577 |
| authorships[3].institutions[0].country_code | CN |
| authorships[3].institutions[0].display_name | Nanjing Agricultural University |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Lingpeng Kong |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | College of Agriculture, Nanjing Agricultural University, Nanjing, Jiangsu, China |
| authorships[4].author.id | https://openalex.org/A5073474817 |
| authorships[4].author.orcid | |
| authorships[4].author.display_name | Jingya Fang |
| authorships[4].countries | CN |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I119454577 |
| authorships[4].affiliations[0].raw_affiliation_string | College of Agriculture, Nanjing Agricultural University, Nanjing, Jiangsu, China |
| authorships[4].institutions[0].id | https://openalex.org/I119454577 |
| authorships[4].institutions[0].ror | https://ror.org/05td3s095 |
| authorships[4].institutions[0].type | education |
| authorships[4].institutions[0].lineage | https://openalex.org/I119454577 |
| authorships[4].institutions[0].country_code | CN |
| authorships[4].institutions[0].display_name | Nanjing Agricultural University |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Jingya Fang |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | College of Agriculture, Nanjing Agricultural University, Nanjing, Jiangsu, China |
| authorships[5].author.id | https://openalex.org/A5014863730 |
| authorships[5].author.orcid | |
| authorships[5].author.display_name | Zutan Li |
| authorships[5].countries | CN |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I119454577 |
| authorships[5].affiliations[0].raw_affiliation_string | College of Agriculture, Nanjing Agricultural University, Nanjing, Jiangsu, China |
| authorships[5].institutions[0].id | https://openalex.org/I119454577 |
| authorships[5].institutions[0].ror | https://ror.org/05td3s095 |
| authorships[5].institutions[0].type | education |
| authorships[5].institutions[0].lineage | https://openalex.org/I119454577 |
| authorships[5].institutions[0].country_code | CN |
| authorships[5].institutions[0].display_name | Nanjing Agricultural University |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Zutan Li |
| authorships[5].is_corresponding | False |
| authorships[5].raw_affiliation_strings | College of Agriculture, Nanjing Agricultural University, Nanjing, Jiangsu, China |
| authorships[6].author.id | https://openalex.org/A5028884115 |
| authorships[6].author.orcid | https://orcid.org/0000-0003-2425-9650 |
| authorships[6].author.display_name | Liangyun Zhang |
| authorships[6].countries | CN |
| authorships[6].affiliations[0].institution_ids | https://openalex.org/I119454577 |
| authorships[6].affiliations[0].raw_affiliation_string | College of Sciences, Nanjing Agricultural University, Nanjing, Jiangsu, China |
| authorships[6].institutions[0].id | https://openalex.org/I119454577 |
| authorships[6].institutions[0].ror | https://ror.org/05td3s095 |
| authorships[6].institutions[0].type | education |
| authorships[6].institutions[0].lineage | https://openalex.org/I119454577 |
| authorships[6].institutions[0].country_code | CN |
| authorships[6].institutions[0].display_name | Nanjing Agricultural University |
| authorships[6].author_position | middle |
| authorships[6].raw_author_name | Liangyun Zhang |
| authorships[6].is_corresponding | False |
| authorships[6].raw_affiliation_strings | College of Sciences, Nanjing Agricultural University, Nanjing, Jiangsu, China |
| authorships[7].author.id | https://openalex.org/A5024796378 |
| authorships[7].author.orcid | https://orcid.org/0000-0001-7401-2926 |
| authorships[7].author.display_name | Cong Pian |
| authorships[7].countries | CN |
| authorships[7].affiliations[0].institution_ids | https://openalex.org/I119454577 |
| authorships[7].affiliations[0].raw_affiliation_string | College of Sciences, Nanjing Agricultural University, Nanjing, Jiangsu, China |
| authorships[7].institutions[0].id | https://openalex.org/I119454577 |
| authorships[7].institutions[0].ror | https://ror.org/05td3s095 |
| authorships[7].institutions[0].type | education |
| authorships[7].institutions[0].lineage | https://openalex.org/I119454577 |
| authorships[7].institutions[0].country_code | CN |
| authorships[7].institutions[0].display_name | Nanjing Agricultural University |
| authorships[7].author_position | last |
| authorships[7].raw_author_name | Cong Pian |
| authorships[7].is_corresponding | False |
| authorships[7].raw_affiliation_strings | College of Sciences, Nanjing Agricultural University, Nanjing, Jiangsu, China |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.7717/peerj.11426 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | SPMLMI: predicting lncRNA–miRNA interactions in humans using a structural perturbation method |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10515 |
| primary_topic.field.id | https://openalex.org/fields/13 |
| primary_topic.field.display_name | Biochemistry, Genetics and Molecular Biology |
| primary_topic.score | 1.0 |
| primary_topic.domain.id | https://openalex.org/domains/1 |
| primary_topic.domain.display_name | Life Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1306 |
| primary_topic.subfield.display_name | Cancer Research |
| primary_topic.display_name | Cancer-related molecular mechanisms research |
| related_works | https://openalex.org/W2726467123, https://openalex.org/W2064726690, https://openalex.org/W2118717649, https://openalex.org/W4252678288, https://openalex.org/W4254065731, https://openalex.org/W2413243053, https://openalex.org/W410723623, https://openalex.org/W2015341305, https://openalex.org/W2035068594, https://openalex.org/W4225593417 |
| cited_by_count | 11 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 1 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 2 |
| counts_by_year[2].year | 2023 |
| counts_by_year[2].cited_by_count | 6 |
| counts_by_year[3].year | 2022 |
| counts_by_year[3].cited_by_count | 2 |
| locations_count | 3 |
| best_oa_location.id | doi:10.7717/peerj.11426 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S1983995261 |
| best_oa_location.source.issn | 2167-8359 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2167-8359 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | PeerJ |
| best_oa_location.source.host_organization | https://openalex.org/P4310320104 |
| best_oa_location.source.host_organization_name | PeerJ, Inc. |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310320104 |
| best_oa_location.source.host_organization_lineage_names | PeerJ, Inc. |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | PeerJ |
| best_oa_location.landing_page_url | https://doi.org/10.7717/peerj.11426 |
| primary_location.id | doi:10.7717/peerj.11426 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S1983995261 |
| primary_location.source.issn | 2167-8359 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2167-8359 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | PeerJ |
| primary_location.source.host_organization | https://openalex.org/P4310320104 |
| primary_location.source.host_organization_name | PeerJ, Inc. |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310320104 |
| primary_location.source.host_organization_lineage_names | PeerJ, Inc. |
| primary_location.license | cc-by |
| primary_location.pdf_url | |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | PeerJ |
| primary_location.landing_page_url | https://doi.org/10.7717/peerj.11426 |
| publication_date | 2021-05-19 |
| publication_year | 2021 |
| referenced_works | https://openalex.org/W1965514608, https://openalex.org/W1518330963, https://openalex.org/W2021499743, https://openalex.org/W1965173359, https://openalex.org/W2203596196, https://openalex.org/W2068205741, https://openalex.org/W2891866117, https://openalex.org/W2765950793, https://openalex.org/W2152970345, https://openalex.org/W2462108616, https://openalex.org/W2157082398, https://openalex.org/W2155769759, https://openalex.org/W3012935077, https://openalex.org/W2767918570, https://openalex.org/W2056705783, https://openalex.org/W2048724765, https://openalex.org/W2766950760, https://openalex.org/W2010461414, https://openalex.org/W1879996757, https://openalex.org/W2128619556, https://openalex.org/W2983877246, https://openalex.org/W2059357290, https://openalex.org/W1998274884, https://openalex.org/W2341424800, https://openalex.org/W2138664009, https://openalex.org/W2117977572, https://openalex.org/W2094292925, https://openalex.org/W2525370412, https://openalex.org/W1981629946, https://openalex.org/W2580790464, https://openalex.org/W1977382765, https://openalex.org/W1979104937, https://openalex.org/W3011727606, https://openalex.org/W2767061187, https://openalex.org/W2058615001, https://openalex.org/W2575293459, https://openalex.org/W2198153867, https://openalex.org/W2105349784, https://openalex.org/W2037912573, https://openalex.org/W2080236356, https://openalex.org/W2046387002, https://openalex.org/W2505475666, https://openalex.org/W2341291028, https://openalex.org/W2135015580, https://openalex.org/W2160467221, https://openalex.org/W1998857348, https://openalex.org/W2466688850, https://openalex.org/W2106030955, https://openalex.org/W1989057528, https://openalex.org/W2780584018, https://openalex.org/W2150912425, https://openalex.org/W2055425879 |
| referenced_works_count | 52 |
| abstract_inverted_index.a | 61, 90, 202 |
| abstract_inverted_index.In | 45, 80, 166 |
| abstract_inverted_index.We | 104 |
| abstract_inverted_index.an | 23, 71, 76 |
| abstract_inverted_index.as | 9 |
| abstract_inverted_index.by | 64, 82 |
| abstract_inverted_index.is | 42, 201 |
| abstract_inverted_index.of | 15, 30, 32, 37, 56, 110, 118, 125, 132, 147, 170, 176, 183, 196 |
| abstract_inverted_index.on | 60, 100, 159 |
| abstract_inverted_index.to | 52, 94, 137, 205 |
| abstract_inverted_index.we | 48, 88, 141 |
| abstract_inverted_index.± | 149, 152, 156 |
| abstract_inverted_index.RNA | 2 |
| abstract_inverted_index.and | 75, 154, 188, 194 |
| abstract_inverted_index.any | 119 |
| abstract_inverted_index.are | 6 |
| abstract_inverted_index.for | 26, 67, 129 |
| abstract_inverted_index.the | 13, 28, 35, 38, 54, 84, 101, 107, 111, 123, 130, 145, 168, 177, 192, 197 |
| abstract_inverted_index.two | 184 |
| abstract_inverted_index.was | 114, 172 |
| abstract_inverted_index.Case | 181 |
| abstract_inverted_index.Long | 0 |
| abstract_inverted_index.good | 163 |
| abstract_inverted_index.real | 139 |
| abstract_inverted_index.than | 116, 174 |
| abstract_inverted_index.that | 106, 117, 175 |
| abstract_inverted_index.this | 46 |
| abstract_inverted_index.used | 49 |
| abstract_inverted_index.RNAs. | 17 |
| abstract_inverted_index.areas | 143 |
| abstract_inverted_index.based | 59, 99, 158 |
| abstract_inverted_index.basis | 25 |
| abstract_inverted_index.found | 105 |
| abstract_inverted_index.known | 68 |
| abstract_inverted_index.links | 58 |
| abstract_inverted_index.miRNA | 77 |
| abstract_inverted_index.model | 164 |
| abstract_inverted_index.novel | 207 |
| abstract_inverted_index.still | 43 |
| abstract_inverted_index.three | 138 |
| abstract_inverted_index.under | 144 |
| abstract_inverted_index.using | 83 |
| abstract_inverted_index.(i.e., | 186 |
| abstract_inverted_index.0.0021 | 157 |
| abstract_inverted_index.0.8653 | 155 |
| abstract_inverted_index.0.8767 | 151 |
| abstract_inverted_index.0.9512 | 148 |
| abstract_inverted_index.5-fold | 160 |
| abstract_inverted_index.SNHG14 | 187 |
| abstract_inverted_index.SPMLMI | 93, 136, 171, 200 |
| abstract_inverted_index.action | 31 |
| abstract_inverted_index.better | 173 |
| abstract_inverted_index.called | 92 |
| abstract_inverted_index.curves | 146 |
| abstract_inverted_index.higher | 115 |
| abstract_inverted_index.lncRNA | 72 |
| abstract_inverted_index.single | 120 |
| abstract_inverted_index.study, | 47 |
| abstract_inverted_index.(miRNA) | 4 |
| abstract_inverted_index.0.0033, | 153 |
| abstract_inverted_index.0.0034, | 150 |
| abstract_inverted_index.MALAT1) | 189 |
| abstract_inverted_index.bilayer | 62, 102, 112, 126 |
| abstract_inverted_index.complex | 211 |
| abstract_inverted_index.further | 190 |
| abstract_inverted_index.lncRNAs | 185 |
| abstract_inverted_index.measure | 53 |
| abstract_inverted_index.method, | 87 |
| abstract_inverted_index.method. | 198 |
| abstract_inverted_index.methods | 41 |
| abstract_inverted_index.ncRNAs. | 33 |
| abstract_inverted_index.network | 63, 113, 127 |
| abstract_inverted_index.predict | 95 |
| abstract_inverted_index.quickly | 7 |
| abstract_inverted_index.studies | 182 |
| abstract_inverted_index.utility | 124 |
| abstract_inverted_index.Applying | 135 |
| abstract_inverted_index.However, | 34 |
| abstract_inverted_index.accuracy | 36 |
| abstract_inverted_index.approach | 204 |
| abstract_inverted_index.emerging | 8 |
| abstract_inverted_index.feasible | 203 |
| abstract_inverted_index.identify | 206 |
| abstract_inverted_index.limited. | 44 |
| abstract_inverted_index.methods. | 180 |
| abstract_inverted_index.network, | 74, 121 |
| abstract_inverted_index.network. | 79, 103 |
| abstract_inverted_index.obtained | 142 |
| abstract_inverted_index.proposed | 89 |
| abstract_inverted_index.provides | 22 |
| abstract_inverted_index.addition, | 167 |
| abstract_inverted_index.datasets, | 140 |
| abstract_inverted_index.framework | 91 |
| abstract_inverted_index.functions | 14 |
| abstract_inverted_index.important | 10, 24 |
| abstract_inverted_index.potential | 96 |
| abstract_inverted_index.Therefore, | 199 |
| abstract_inverted_index.biological | 212 |
| abstract_inverted_index.mechanisms | 11, 29 |
| abstract_inverted_index.non-coding | 1, 16 |
| abstract_inverted_index.predicting | 19 |
| abstract_inverted_index.prediction | 40, 131 |
| abstract_inverted_index.previously | 178 |
| abstract_inverted_index.processes. | 213 |
| abstract_inverted_index.similarity | 73, 78 |
| abstract_inverted_index.structural | 50, 85, 108 |
| abstract_inverted_index.suggesting | 162 |
| abstract_inverted_index.supporting | 122 |
| abstract_inverted_index.underlying | 12, 210 |
| abstract_inverted_index.consistency | 51, 109 |
| abstract_inverted_index.established | 39, 179 |
| abstract_inverted_index.feasibility | 193 |
| abstract_inverted_index.information | 66 |
| abstract_inverted_index.integrating | 65 |
| abstract_inverted_index.interactive | 57 |
| abstract_inverted_index.particular, | 81 |
| abstract_inverted_index.Accordingly, | 18 |
| abstract_inverted_index.construction | 128 |
| abstract_inverted_index.demonstrated | 191 |
| abstract_inverted_index.interactions | 5, 21, 98, 209 |
| abstract_inverted_index.performance. | 165 |
| abstract_inverted_index.perturbation | 86 |
| abstract_inverted_index.effectiveness | 195 |
| abstract_inverted_index.interactions, | 70 |
| abstract_inverted_index.interactions. | 134 |
| abstract_inverted_index.understanding | 27 |
| abstract_inverted_index.lncRNA–miRNA | 20, 69, 97, 133, 208 |
| abstract_inverted_index.predictability | 55 |
| abstract_inverted_index.generalizability | 169 |
| abstract_inverted_index.cross-validation, | 161 |
| abstract_inverted_index.(lncRNA)–microRNA | 3 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 91 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 8 |
| citation_normalized_percentile.value | 0.69943098 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |