141 related articles for article (PubMed ID: 34888624)
1. EnGRaiN: a supervised ensemble learning method for recovery of large-scale gene regulatory networks.
Aluru M; Shrivastava H; Chockalingam SP; Shivakumar S; Aluru S
Bioinformatics; 2022 Feb; 38(5):1312-1319. PubMed ID: 34888624
[TBL] [Abstract][Full Text] [Related]
2. MCPNet: a parallel maximum capacity-based genome-scale gene network construction framework.
Pan TC; Chockalingam SP; Aluru M; Aluru S
Bioinformatics; 2023 Jun; 39(6):. PubMed ID: 37289522
[TBL] [Abstract][Full Text] [Related]
3. Semi-supervised network inference using simulated gene expression dynamics.
Nguyen P; Braun R
Bioinformatics; 2018 Apr; 34(7):1148-1156. PubMed ID: 29186340
[TBL] [Abstract][Full Text] [Related]
4. High-performance single-cell gene regulatory network inference at scale: the Inferelator 3.0.
Skok Gibbs C; Jackson CA; Saldi GA; Tjärnberg A; Shah A; Watters A; De Veaux N; Tchourine K; Yi R; Hamamsy T; Castro DM; Carriero N; Gorissen BL; Gresham D; Miraldi ER; Bonneau R
Bioinformatics; 2022 Apr; 38(9):2519-2528. PubMed ID: 35188184
[TBL] [Abstract][Full Text] [Related]
5. Accurately modeling biased random walks on weighted networks using node2vec.
Liu R; Hirn M; Krishnan A
Bioinformatics; 2023 Jan; 39(1):. PubMed ID: 36688699
[TBL] [Abstract][Full Text] [Related]
6. Semi-Supervised Multi-View Learning for Gene Network Reconstruction.
Ceci M; Pio G; Kuzmanovski V; Džeroski S
PLoS One; 2015; 10(12):e0144031. PubMed ID: 26641091
[TBL] [Abstract][Full Text] [Related]
7. AGRN: accurate gene regulatory network inference using ensemble machine learning methods.
Alawad DM; Katebi A; Kabir MWU; Hoque MT
Bioinform Adv; 2023; 3(1):vbad032. PubMed ID: 37038446
[TBL] [Abstract][Full Text] [Related]
8. Differential network analysis by simultaneously considering changes in gene interactions and gene expression.
Tu JJ; Ou-Yang L; Zhu Y; Yan H; Qin H; Zhang XF
Bioinformatics; 2021 Dec; 37(23):4414-4423. PubMed ID: 34245246
[TBL] [Abstract][Full Text] [Related]
9. Maximizing capture of gene co-expression relationships through pre-clustering of input expression samples: an Arabidopsis case study.
Feltus FA; Ficklin SP; Gibson SM; Smith MC
BMC Syst Biol; 2013 Jun; 7():44. PubMed ID: 23738693
[TBL] [Abstract][Full Text] [Related]
10. Integrating microRNA target predictions for the discovery of gene regulatory networks: a semi-supervised ensemble learning approach.
Pio G; Malerba D; D'Elia D; Ceci M
BMC Bioinformatics; 2014; 15 Suppl 1(Suppl 1):S4. PubMed ID: 24564296
[TBL] [Abstract][Full Text] [Related]
11. Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories.
Chockalingam S; Aluru M; Aluru S
Microarrays (Basel); 2016 Sep; 5(3):. PubMed ID: 27657141
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. An approach of gene regulatory network construction using mixed entropy optimizing context-related likelihood mutual information.
Lei J; Cai Z; He X; Zheng W; Liu J
Bioinformatics; 2023 Jan; 39(1):. PubMed ID: 36342190
[TBL] [Abstract][Full Text] [Related]
14. PAFway: pairwise associations between functional annotations in biological networks and pathways.
Mahjoub M; Ezer D
Bioinformatics; 2020 Dec; 36(19):4963-4964. PubMed ID: 32678900
[TBL] [Abstract][Full Text] [Related]
15. Network-based multi-task learning models for biomarker selection and cancer outcome prediction.
Wang Z; He Z; Shah M; Zhang T; Fan D; Zhang W
Bioinformatics; 2020 Mar; 36(6):1814-1822. PubMed ID: 31688914
[TBL] [Abstract][Full Text] [Related]
16. Ensemble gene function prediction database reveals genes important for complex I formation in Arabidopsis thaliana.
Hansen BO; Meyer EH; Ferrari C; Vaid N; Movahedi S; Vandepoele K; Nikoloski Z; Mutwil M
New Phytol; 2018 Mar; 217(4):1521-1534. PubMed ID: 29205376
[TBL] [Abstract][Full Text] [Related]
17. PoLoBag: Polynomial Lasso Bagging for signed gene regulatory network inference from expression data.
Ghosh Roy G; Geard N; Verspoor K; He S
Bioinformatics; 2021 Jan; 36(21):5187-5193. PubMed ID: 32697830
[TBL] [Abstract][Full Text] [Related]
18. Extreme learning machines for reverse engineering of gene regulatory networks from expression time series.
Rubiolo M; Milone DH; Stegmayer G
Bioinformatics; 2018 Apr; 34(7):1253-1260. PubMed ID: 29182723
[TBL] [Abstract][Full Text] [Related]
19. Learning gene regulatory networks from only positive and unlabeled data.
Cerulo L; Elkan C; Ceccarelli M
BMC Bioinformatics; 2010 May; 11():228. PubMed ID: 20444264
[TBL] [Abstract][Full Text] [Related]
20. GENIUS: web server to predict local gene networks and key genes for biological functions.
Puelma T; Araus V; Canales J; Vidal EA; Cabello JM; Soto A; Gutiérrez RA
Bioinformatics; 2017 Mar; 33(5):760-761. PubMed ID: 27993775
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]