138 related articles for article (PubMed ID: 37632789)
1. dRFEtools: dynamic recursive feature elimination for omics.
Benjamin KJM; Katipalli T; Paquola ACM
Bioinformatics; 2023 Aug; 39(8):. PubMed ID: 37632789
[TBL] [Abstract][Full Text] [Related]
2. Robust biomarker screening from gene expression data by stable machine learning-recursive feature elimination methods.
Li L; Ching WK; Liu ZP
Comput Biol Chem; 2022 Oct; 100():107747. PubMed ID: 35932551
[TBL] [Abstract][Full Text] [Related]
3. Identifying interactions in omics data for clinical biomarker discovery using symbolic regression.
Christensen NJ; Demharter S; Machado M; Pedersen L; Salvatore M; Stentoft-Hansen V; Iglesias MT
Bioinformatics; 2022 Aug; 38(15):3749-3758. PubMed ID: 35731214
[TBL] [Abstract][Full Text] [Related]
4. A dynamic recursive feature elimination framework (dRFE) to further refine a set of OMIC biomarkers.
Han Y; Huang L; Zhou F
Bioinformatics; 2021 Aug; 37(15):2183-2189. PubMed ID: 33515240
[TBL] [Abstract][Full Text] [Related]
5. MinE-RFE: determine the optimal subset from RFE by minimizing the subset-accuracy-defined energy.
Su R; Liu X; Wei L
Brief Bioinform; 2020 Mar; 21(2):687-698. PubMed ID: 30860571
[TBL] [Abstract][Full Text] [Related]
6. SVM-RFE: selection and visualization of the most relevant features through non-linear kernels.
Sanz H; Valim C; Vegas E; Oller JM; Reverter F
BMC Bioinformatics; 2018 Nov; 19(1):432. PubMed ID: 30453885
[TBL] [Abstract][Full Text] [Related]
7. An efficient alpha seeding method for optimized extreme learning machine-based feature selection algorithm.
Ding X; Yang F; Jin S; Cao J
Comput Biol Med; 2021 Jul; 134():104505. PubMed ID: 34102404
[TBL] [Abstract][Full Text] [Related]
8. Effective hybrid feature selection using different bootstrap enhances cancers classification performance.
Abdelwahed NM; El-Tawel GS; Makhlouf MA
BioData Min; 2022 Sep; 15(1):24. PubMed ID: 36175944
[TBL] [Abstract][Full Text] [Related]
9. Selecting Feature Subsets Based on SVM-RFE and the Overlapping Ratio with Applications in Bioinformatics.
Lin X; Li C; Zhang Y; Su B; Fan M; Wei H
Molecules; 2017 Dec; 23(1):. PubMed ID: 29278382
[TBL] [Abstract][Full Text] [Related]
10. Gnocis: An integrated system for interactive and reproducible analysis and modelling of cis-regulatory elements in Python 3.
Bredesen-Aa BA; Rehmsmeier M
PLoS One; 2022; 17(9):e0274338. PubMed ID: 36084008
[TBL] [Abstract][Full Text] [Related]
11. FSelector: a Ruby gem for feature selection.
Cheng T; Wang Y; Bryant SH
Bioinformatics; 2012 Nov; 28(21):2851-2. PubMed ID: 22942017
[TBL] [Abstract][Full Text] [Related]
12. Leaf-GP: an open and automated software application for measuring growth phenotypes for arabidopsis and wheat.
Zhou J; Applegate C; Alonso AD; Reynolds D; Orford S; Mackiewicz M; Griffiths S; Penfield S; Pullen N
Plant Methods; 2017; 13():117. PubMed ID: 29299051
[TBL] [Abstract][Full Text] [Related]
13. An Efficient Feature Selection Strategy Based on Multiple Support Vector Machine Technology with Gene Expression Data.
Zhang Y; Deng Q; Liang W; Zou X
Biomed Res Int; 2018; 2018():7538204. PubMed ID: 30228989
[TBL] [Abstract][Full Text] [Related]
14. Improving the performance and interpretability on medical datasets using graphical ensemble feature selection.
Battistella E; Ghiassian D; Barabási AL
Bioinformatics; 2024 Jun; 40(6):. PubMed ID: 38837347
[TBL] [Abstract][Full Text] [Related]
15. PyIOmica: longitudinal omics analysis and trend identification.
Domanskyi S; Piermarocchi C; Mias GI
Bioinformatics; 2020 Apr; 36(7):2306-2307. PubMed ID: 31778155
[TBL] [Abstract][Full Text] [Related]
16. A Unified Multi-Class Feature Selection Framework for Microarray Data.
Ding X; Yang F; Ma F; Chen S
IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(6):3725-3736. PubMed ID: 37698974
[TBL] [Abstract][Full Text] [Related]
17. Recursive cluster elimination (RCE) for classification and feature selection from gene expression data.
Yousef M; Jung S; Showe LC; Showe MK
BMC Bioinformatics; 2007 May; 8():144. PubMed ID: 17474999
[TBL] [Abstract][Full Text] [Related]
18. GENECI: A novel evolutionary machine learning consensus-based approach for the inference of gene regulatory networks.
Segura-Ortiz A; García-Nieto J; Aldana-Montes JF; Navas-Delgado I
Comput Biol Med; 2023 Mar; 155():106653. PubMed ID: 36803795
[TBL] [Abstract][Full Text] [Related]
19. AdaBoost-based multiple SVM-RFE for classification of mammograms in DDSM.
Yoon S; Kim S
BMC Med Inform Decis Mak; 2009 Nov; 9 Suppl 1(Suppl 1):S1. PubMed ID: 19891795
[TBL] [Abstract][Full Text] [Related]
20. Fast and interpretable genomic data analysis using multiple approximate kernel learning.
Bektaş AB; Ak Ç; Gönen M
Bioinformatics; 2022 Jun; 38(Suppl 1):i77-i83. PubMed ID: 35758810
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
