205 related articles for article (PubMed ID: 32393369)
1. Compressing gene expression data using multiple latent space dimensionalities learns complementary biological representations.
Way GP; Zietz M; Rubinetti V; Himmelstein DS; Greene CS
Genome Biol; 2020 May; 21(1):109. PubMed ID: 32393369
[TBL] [Abstract][Full Text] [Related]
2. Variational autoencoders learn transferrable representations of metabolomics data.
Gomari DP; Schweickart A; Cerchietti L; Paietta E; Fernandez H; Al-Amin H; Suhre K; Krumsiek J
Commun Biol; 2022 Jun; 5(1):645. PubMed ID: 35773471
[TBL] [Abstract][Full Text] [Related]
3. GenCoder: A Novel Convolutional Neural Network Based Autoencoder for Genomic Sequence Data Compression.
K S S; Nair MS
IEEE/ACM Trans Comput Biol Bioinform; 2024; 21(3):405-415. PubMed ID: 38358865
[TBL] [Abstract][Full Text] [Related]
4. Denoising Adversarial Autoencoders.
Creswell A; Bharath AA
IEEE Trans Neural Netw Learn Syst; 2019 Apr; 30(4):968-984. PubMed ID: 30130236
[TBL] [Abstract][Full Text] [Related]
5. Predicting drug polypharmacology from cell morphology readouts using variational autoencoder latent space arithmetic.
Chow YL; Singh S; Carpenter AE; Way GP
PLoS Comput Biol; 2022 Feb; 18(2):e1009888. PubMed ID: 35213530
[TBL] [Abstract][Full Text] [Related]
6. Semi-supervised automatic seizure detection using personalized anomaly detecting variational autoencoder with behind-the-ear EEG.
You S; Hwan Cho B; Shon YM; Seo DW; Kim IY
Comput Methods Programs Biomed; 2022 Jan; 213():106542. PubMed ID: 34839270
[TBL] [Abstract][Full Text] [Related]
7. Capturing the latent space of an Autoencoder for multi-omics integration and cancer subtyping.
Madhumita ; Paul S
Comput Biol Med; 2022 Sep; 148():105832. PubMed ID: 35834966
[TBL] [Abstract][Full Text] [Related]
8. Extracting a biologically relevant latent space from cancer transcriptomes with variational autoencoders.
Way GP; Greene CS
Pac Symp Biocomput; 2018; 23():80-91. PubMed ID: 29218871
[TBL] [Abstract][Full Text] [Related]
9. Adaptation of Autoencoder for Sparsity Reduction From Clinical Notes Representation Learning.
Le TD; Noumeir R; Rambaud J; Sans G; Jouvet P
IEEE J Transl Eng Health Med; 2023; 11():469-478. PubMed ID: 37817825
[TBL] [Abstract][Full Text] [Related]
10. Latent-space embedding of expression data identifies gene signatures from sputum samples of asthmatic patients.
Lou S; Li T; Spakowicz D; Yan X; Chupp GL; Gerstein M
BMC Bioinformatics; 2020 Oct; 21(1):457. PubMed ID: 33059594
[TBL] [Abstract][Full Text] [Related]
11. Parameter tuning is a key part of dimensionality reduction via deep variational autoencoders for single cell RNA transcriptomics.
Hu Q; Greene CS
Pac Symp Biocomput; 2019; 24():362-373. PubMed ID: 30963075
[TBL] [Abstract][Full Text] [Related]
12. Extracting a biologically latent space of lung cancer epigenetics with variational autoencoders.
Wang Z; Wang Y
BMC Bioinformatics; 2019 Nov; 20(Suppl 18):568. PubMed ID: 31760935
[TBL] [Abstract][Full Text] [Related]
13. Optimal dimensionality selection for independent component analysis of transcriptomic data.
McConn JL; Lamoureux CR; Poudel S; Palsson BO; Sastry AV
BMC Bioinformatics; 2021 Dec; 22(1):584. PubMed ID: 34879815
[TBL] [Abstract][Full Text] [Related]
14. Learning meaningful latent space representations for patient risk stratification: Model development and validation for dengue and other acute febrile illness.
Hernandez B; Stiff O; Ming DK; Ho Quang C; Nguyen Lam V; Nguyen Minh T; Nguyen Van Vinh C; Nguyen Minh N; Nguyen Quang H; Phung Khanh L; Dong Thi Hoai T; Dinh The T; Huynh Trung T; Wills B; Simmons CP; Holmes AH; Yacoub S; Georgiou P;
Front Digit Health; 2023; 5():1057467. PubMed ID: 36910574
[TBL] [Abstract][Full Text] [Related]
15. Interpretable Autoencoders Trained on Single Cell Sequencing Data Can Transfer Directly to Data from Unseen Tissues.
Walbech JS; Kinalis S; Winther O; Nielsen FC; Bagger FO
Cells; 2021 Dec; 11(1):. PubMed ID: 35011647
[TBL] [Abstract][Full Text] [Related]
16. Deep compressive autoencoder for action potential compression in large-scale neural recording.
Wu T; Zhao W; Keefer E; Yang Z
J Neural Eng; 2018 Dec; 15(6):066019. PubMed ID: 30215605
[TBL] [Abstract][Full Text] [Related]
17. Learning biologically-interpretable latent representations for gene expression data: Pathway Activity Score Learning Algorithm.
Karagiannaki I; Gourlia K; Lagani V; Pantazis Y; Tsamardinos I
Mach Learn; 2023; 112(11):4257-4287. PubMed ID: 37900054
[TBL] [Abstract][Full Text] [Related]
18. Estimating the functional dimensionality of neural representations.
Ahlheim C; Love BC
Neuroimage; 2018 Oct; 179():51-62. PubMed ID: 29886143
[TBL] [Abstract][Full Text] [Related]
19. scBGEDA: deep single-cell clustering analysis via a dual denoising autoencoder with bipartite graph ensemble clustering.
Wang Y; Yu Z; Li S; Bian C; Liang Y; Wong KC; Li X
Bioinformatics; 2023 Feb; 39(2):. PubMed ID: 36734596
[TBL] [Abstract][Full Text] [Related]
20. A multimodal dynamical variational autoencoder for audiovisual speech representation learning.
Sadok S; Leglaive S; Girin L; Alameda-Pineda X; Séguier R
Neural Netw; 2024 Apr; 172():106120. PubMed ID: 38266474
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
