Knowledge-guided Learning Methods for Integrative Analysis of Multi-omics Data
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2024/04/01
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Indian UGC (journal)
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Refrences48
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Wenrui Li ORCID (unauthenticated)
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Jenna Ballard ORCID (unauthenticated)
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Yize Zhao
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Qi Long ORCID (unauthenticated)
Cite
Li, Wenrui, et al. “Knowledge-Guided Learning Methods for Integrative Analysis of Multi-Omics Data”. Computational and Structural Biotechnology Journal, 2024, https://doi.org/10.1016/j.csbj.2024.04.053.
Li, W., Ballard, J., Zhao, Y., & Long, Q. (2024). Knowledge-guided Learning Methods for Integrative Analysis of Multi-omics Data. Computational and Structural Biotechnology Journal. https://doi.org/10.1016/j.csbj.2024.04.053
Li, Wenrui, Jenna Ballard, Yize Zhao, and Qi Long. “Knowledge-Guided Learning Methods for Integrative Analysis of Multi-Omics Data”. Computational and Structural Biotechnology Journal, 2024. https://doi.org/10.1016/j.csbj.2024.04.053.
Li W, Ballard J, Zhao Y, Long Q. Knowledge-guided Learning Methods for Integrative Analysis of Multi-omics Data. Computational and Structural Biotechnology Journal. 2024;.
Journal Categories
Science
Biology (General)
Science
Chemistry
Organic chemistry
Biochemistry
Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Hierarchical Feature Selection Incorporating Known and Novel Biological Information: Identifying Genomic Features Related to Prostate Cancer Recurrence | Journal of the American Statistical Association |
| 14 | 2016 |
| 10.1200/PO.19.00018 | ||||
| DeepOmix: A scalable and interpretable multi-omics deep learning framework and application in cancer survival analysis | Computational and Structural Biotechnology Journal |
| 33 | 2021 |
Robust knowledge-guided biclustering for multi-omics data | Briefings in Bioinformatics |
| 1 | 2023 |
Incorporating graph information in Bayesian factor analysis with robust and adaptive shrinkage priors | Biometrics |
| 1 | 2024 |