137 related articles for article (PubMed ID: 37314414)
1. DeepSP: A Deep Learning Framework for Spatial Proteomics.
Wang B; Zhang X; Xu C; Han X; Wang Y; Situ C; Li Y; Guo X
J Proteome Res; 2023 Jul; 22(7):2186-2198. PubMed ID: 37314414
[TBL] [Abstract][Full Text] [Related]
2. DeepSP: Deep learning-based spatial properties to predict monoclonal antibody stability.
Kalejaye L; Wu IE; Terry T; Lai PK
Comput Struct Biotechnol J; 2024 Dec; 23():2220-2229. PubMed ID: 38827232
[TBL] [Abstract][Full Text] [Related]
3. Application of Machine Learning in Spatial Proteomics.
Mou M; Pan Z; Lu M; Sun H; Wang Y; Luo Y; Zhu F
J Chem Inf Model; 2022 Dec; 62(23):5875-5895. PubMed ID: 36378082
[TBL] [Abstract][Full Text] [Related]
4. TransGCN: a semi-supervised graph convolution network-based framework to infer protein translocations in spatio-temporal proteomics.
Wang B; Zhang X; Han X; Hao B; Li Y; Guo X
Brief Bioinform; 2024 Jan; 25(2):. PubMed ID: 38426320
[TBL] [Abstract][Full Text] [Related]
5. PScL-HDeep: image-based prediction of protein subcellular location in human tissue using ensemble learning of handcrafted and deep learned features with two-layer feature selection.
Ullah M; Han K; Hadi F; Xu J; Song J; Yu DJ
Brief Bioinform; 2021 Nov; 22(6):. PubMed ID: 34337652
[TBL] [Abstract][Full Text] [Related]
6. Learning from Heterogeneous Data Sources: An Application in Spatial Proteomics.
Breckels LM; Holden SB; Wojnar D; Mulvey CM; Christoforou A; Groen A; Trotter MW; Kohlbacher O; Lilley KS; Gatto L
PLoS Comput Biol; 2016 May; 12(5):e1004920. PubMed ID: 27175778
[TBL] [Abstract][Full Text] [Related]
7. A Bayesian mixture modelling approach for spatial proteomics.
Crook OM; Mulvey CM; Kirk PDW; Lilley KS; Gatto L
PLoS Comput Biol; 2018 Nov; 14(11):e1006516. PubMed ID: 30481170
[TBL] [Abstract][Full Text] [Related]
8. The effect of organelle discovery upon sub-cellular protein localisation.
Breckels LM; Gatto L; Christoforou A; Groen AJ; Lilley KS; Trotter MW
J Proteomics; 2013 Aug; 88():129-40. PubMed ID: 23523639
[TBL] [Abstract][Full Text] [Related]
9. PSL-LCCL: a resource for subcellular protein localization in liver cancer cell line SK_HEP1.
Huang F; Tang X; Ye B; Wu S; Ding K
Database (Oxford); 2022 Feb; 2022():. PubMed ID: 35134877
[TBL] [Abstract][Full Text] [Related]
10. Deep Learning in Proteomics.
Wen B; Zeng WF; Liao Y; Shi Z; Savage SR; Jiang W; Zhang B
Proteomics; 2020 Nov; 20(21-22):e1900335. PubMed ID: 32939979
[TBL] [Abstract][Full Text] [Related]
11. Machine and Deep Learning for Prediction of Subcellular Localization.
Pan G; Sun C; Liao Z; Tang J
Methods Mol Biol; 2021; 2361():249-261. PubMed ID: 34236666
[TBL] [Abstract][Full Text] [Related]
12. Proteome analysis using machine learning approaches and its applications to diseases.
Sengupta A; Naresh G; Mishra A; Parashar D; Narad P
Adv Protein Chem Struct Biol; 2021; 127():161-216. PubMed ID: 34340767
[TBL] [Abstract][Full Text] [Related]
13. A deep learning framework for identifying essential proteins based on multiple biological information.
Yue Y; Ye C; Peng PY; Zhai HX; Ahmad I; Xia C; Wu YZ; Zhang YH
BMC Bioinformatics; 2022 Aug; 23(1):318. PubMed ID: 35927611
[TBL] [Abstract][Full Text] [Related]
14. Protein Subcellular Localization Prediction Model Based on Graph Convolutional Network.
Zhang T; Gu J; Wang Z; Wu C; Liang Y; Shi X
Interdiscip Sci; 2022 Dec; 14(4):937-946. PubMed ID: 35713780
[TBL] [Abstract][Full Text] [Related]
15. ProteomicsML: An Online Platform for Community-Curated Data sets and Tutorials for Machine Learning in Proteomics.
Rehfeldt TG; Gabriels R; Bouwmeester R; Gessulat S; Neely BA; Palmblad M; Perez-Riverol Y; Schmidt T; Vizcaíno JA; Deutsch EW
J Proteome Res; 2023 Feb; 22(2):632-636. PubMed ID: 36693629
[TBL] [Abstract][Full Text] [Related]
16. Bioimage-Based Prediction of Protein Subcellular Location in Human Tissue with Ensemble Features and Deep Networks.
Liu GH; Zhang BW; Qian G; Wang B; Mao B; Bichindaritz I
IEEE/ACM Trans Comput Biol Bioinform; 2020; 17(6):1966-1980. PubMed ID: 31107658
[TBL] [Abstract][Full Text] [Related]
17. Spatial perspectives in the redox code-Mass spectrometric proteomics studies of moonlighting proteins.
Pinto G; Radulovic M; Godovac-Zimmermann J
Mass Spectrom Rev; 2018 Jan; 37(1):81-100. PubMed ID: 27186965
[TBL] [Abstract][Full Text] [Related]
18. PB-Net: Automatic peak integration by sequential deep learning for multiple reaction monitoring.
Wu Z; Serie D; Xu G; Zou J
J Proteomics; 2020 Jul; 223():103820. PubMed ID: 32416316
[TBL] [Abstract][Full Text] [Related]
19. Dynamic Organellar Maps for Spatial Proteomics.
Itzhak DN; Schessner JP; Borner GHH
Curr Protoc Cell Biol; 2019 Jun; 83(1):e81. PubMed ID: 30489039
[TBL] [Abstract][Full Text] [Related]
20. Automatic recognition of protein subcellular location patterns in single cells from immunofluorescence images based on deep learning.
Zhu XL; Bao LX; Xue MQ; Xu YY
Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36577448
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
