Found: 31
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Unraveling phenotypic variance in metabolic syndrome through multi-omics.
- Published in:
- Human Genetics, 2024, v. 143, n. 1, p. 35, doi. 10.1007/s00439-023-02619-0
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- Article
Pan-cancer characterization of ncRNA synergistic competition uncovers potential carcinogenic biomarkers.
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- PLoS Computational Biology, 2023, v. 19, n. 10, p. 1, doi. 10.1371/journal.pcbi.1011308
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- Article
Dynamic cancer drivers: a causal approach for cancer driver discovery based on bio-pathological trajectories.
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- Briefings in Functional Genomics, 2022, v. 21, n. 6, p. 455, doi. 10.1093/bfgp/elac030
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- Article
How do the existing fairness metrics and unfairness mitigation algorithms contribute to ethical learning analytics?
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- British Journal of Educational Technology, 2022, v. 53, n. 4, p. 822, doi. 10.1111/bjet.13217
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- Article
Sufficient dimension reduction for average causal effect estimation.
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- Data Mining & Knowledge Discovery, 2022, v. 36, n. 3, p. 1174, doi. 10.1007/s10618-022-00832-5
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- Article
Time to infer miRNA sponge modules.
- Published in:
- Wiley Interdisciplinary Reviews: RNA, 2022, v. 13, n. 2, p. 1, doi. 10.1002/wrna.1686
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- Article
miRspongeR 2.0: an enhanced R package for exploring miRNA sponge regulation.
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- Bioinformatics Advances, 2022, v. 2, n. 1, p. 1, doi. 10.1093/bioadv/vbac063
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- Article
Exploring cell-specific miRNA regulation with single-cell miRNA-mRNA co-sequencing data.
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- BMC Bioinformatics, 2021, v. 22, n. 1, p. 1, doi. 10.1186/s12859-021-04498-6
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- Article
Computational methods for cancer driver discovery: A survey.
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- Theranostics, 2021, v. 11, n. 11, p. 5553, doi. 10.7150/thno.52670
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- Article
GraphDTA: predicting drug–target binding affinity with graph neural networks.
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- Bioinformatics, 2021, v. 37, n. 8, p. 1140, doi. 10.1093/bioinformatics/btaa921
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- Article
A pseudotemporal causality approach to identifying miRNA–mRNA interactions during biological processes.
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- Bioinformatics, 2021, v. 37, n. 6, p. 807, doi. 10.1093/bioinformatics/btaa899
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- Article
LMSM: A modular approach for identifying lncRNA related miRNA sponge modules in breast cancer.
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- PLoS Computational Biology, 2020, v. 16, n. 4, p. 1, doi. 10.1371/journal.pcbi.1007851
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- Article
Correction to: Identifying miRNA synergism using multiple-intervention causal inference.
- Published in:
- 2020
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- Publication type:
- Correction Notice
Identifying miRNA synergism using multiple-intervention causal inference.
- Published in:
- BMC Bioinformatics, 2019, v. 20, n. 1, p. 1, doi. 10.1186/s12859-019-3215-5
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- Article
Inferring and analyzing module-specific lncRNA–mRNA causal regulatory networks in human cancer.
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- Briefings in Bioinformatics, 2019, p. 1403, doi. 10.1093/bib/bby008
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- Publication type:
- Article
miRspongeR: an R/Bioconductor package for the identification and analysis of miRNA sponge interaction networks and modules.
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- BMC Bioinformatics, 2019, v. 20, n. 1, p. 1, doi. 10.1186/s12859-019-2861-y
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- Article
Estimating heterogeneous treatment effect by balancing heterogeneity and fitness.
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- BMC Bioinformatics, 2018, v. 19, n. 19, p. 61, doi. 10.1186/s12859-018-2521-7
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- Publication type:
- Article
miRBaseConverter: an R/Bioconductor package for converting and retrieving miRNA name, accession, sequence and family information in different versions of miRBase.
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- BMC Bioinformatics, 2018, v. 19, n. 19, p. 179, doi. 10.1186/s12859-018-2531-5
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- Publication type:
- Article
LncmiRSRN: identification and analysis of long non-coding RNA related miRNA sponge regulatory network in human cancer.
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- Bioinformatics, 2018, v. 34, n. 24, p. 4232, doi. 10.1093/bioinformatics/bty525
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- Article
CancerSubtypes: an R/Bioconductor package for molecular cancer subtype identification, validation and visualization.
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- Bioinformatics, 2017, v. 33, n. 19, p. 3131, doi. 10.1093/bioinformatics/btx378
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- Article
Mining heterogeneous causal effects for personalized cancer treatment.
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- Bioinformatics, 2017, v. 33, n. 15, p. 2372, doi. 10.1093/bioinformatics/btx174
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- Article
Computational methods for identifying miRNA sponge interactions.
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- Briefings in Bioinformatics, 2017, v. 18, n. 4, p. 577, doi. 10.1093/bib/bbw042
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- Article
Inferring miRNA sponge co-regulation of protein-protein interactions in human breast cancer.
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- BMC Bioinformatics, 2017, v. 18, p. 1, doi. 10.1186/s12859-017-1672-2
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- Article
Predicting miRNA Targets by Integrating Gene Regulatory Knowledge with Expression Profiles.
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- PLoS ONE, 2016, v. 11, n. 4, p. 1, doi. 10.1371/journal.pone.0152860
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- Article
Identifying Cancer Subtypes from miRNA-TF-mRNA Regulatory Networks and Expression Data.
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- PLoS ONE, 2016, v. 11, n. 4, p. 1, doi. 10.1371/journal.pone.0152792
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- Article
Identification of miRNA-mRNA regulatory modules by exploring collective group relationships.
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- BMC Genomics, 2016, v. 17, p. 71, doi. 10.1186/s12864-015-2300-z
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- Article
miRLAB: An R Based Dry Lab for Exploring miRNA-mRNA Regulatory Relationships.
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- PLoS ONE, 2015, v. 10, n. 12, p. 1, doi. 10.1371/journal.pone.0145386
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- Article
Ensemble Methods for MiRNA Target Prediction from Expression Data.
- Published in:
- PLoS ONE, 2015, v. 10, n. 6, p. 1, doi. 10.1371/journal.pone.0131627
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- Article
From miRNA regulation to miRNA-TF co-regulation: computational approaches and challenges.
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- Briefings in Bioinformatics, 2015, v. 16, n. 3, p. 475, doi. 10.1093/bib/bbu023
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- Article
Inferring condition-specific miRNA activity from matched miRNA and mRNA expression data.
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- Bioinformatics, 2014, v. 30, n. 21, p. 3070, doi. 10.1093/bioinformatics/btu489
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- Article
Inferring microRNA–mRNA causal regulatory relationships from expression data.
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- Bioinformatics, 2013, v. 29, n. 6, p. 765, doi. 10.1093/bioinformatics/btt048
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- Publication type:
- Article