Detalhe da pesquisa
1.
Comparison of five supervised feature selection algorithms leading to top features and gene signatures from multi-omics data in cancer.
BMC Bioinformatics
; 23(Suppl 3): 153, 2022 Apr 28.
Artigo
Inglês
| MEDLINE | ID: mdl-35484501
2.
MicroRNA transcription start site prediction with multi-objective feature selection.
Stat Appl Genet Mol Biol
; 11(1): Article 6, 2012 Jan 06.
Artigo
Inglês
| MEDLINE | ID: mdl-22499686
3.
Optimal ranking and directional signature classification using the integral strategy of multi-objective optimization-based association rule mining of multi-omics data.
Front Bioinform
; 3: 1182176, 2023.
Artigo
Inglês
| MEDLINE | ID: mdl-37576714
4.
Dimensionality Reduction and Louvain Agglomerative Hierarchical Clustering for Cluster-Specified Frequent Biomarker Discovery in Single-Cell Sequencing Data.
Front Genet
; 13: 828479, 2022.
Artigo
Inglês
| MEDLINE | ID: mdl-35198011
5.
Unsupervised Feature Selection Using an Integrated Strategy of Hierarchical Clustering With Singular Value Decomposition: An Integrative Biomarker Discovery Method With Application to Acute Myeloid Leukemia.
IEEE/ACM Trans Comput Biol Bioinform
; 19(3): 1354-1364, 2022.
Artigo
Inglês
| MEDLINE | ID: mdl-34495838
6.
A Linear Regression and Deep Learning Approach for Detecting Reliable Genetic Alterations in Cancer Using DNA Methylation and Gene Expression Data.
Genes (Basel)
; 11(8)2020 08 12.
Artigo
Inglês
| MEDLINE | ID: mdl-32806782
7.
DTFP-Growth: Dynamic Threshold-Based FP-Growth Rule Mining Algorithm Through Integrating Gene Expression, Methylation, and Protein-Protein Interaction Profiles.
IEEE Trans Nanobioscience
; 17(2): 117-125, 2018 04.
Artigo
Inglês
| MEDLINE | ID: mdl-29870335
8.
Identifying Epigenetic Biomarkers using Maximal Relevance and Minimal Redundancy Based Feature Selection for Multi-Omics Data.
IEEE Trans Nanobioscience
; 16(1): 3-10, 2017 01.
Artigo
Inglês
| MEDLINE | ID: mdl-28092570
9.
DNA methylation patterns facilitate the identification of microRNA transcription start sites: a brain-specific study.
PLoS One
; 8(6): e66722, 2013.
Artigo
Inglês
| MEDLINE | ID: mdl-23826117