Multiple Protein Subcellular Locations Prediction Based on Deep Convolutional Neural Networks with Self-Attention Mechanism-Reference-Cited by-同舟云学术

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Multiple Protein Subcellular Locations Prediction Based on Deep Convolutional Neural Networks with Self-Attention Mechanism

Published:2022-01-23 Issue:2 Volume:14 Page:421-438
ISSN:1913-2751
Container-title:Interdisciplinary Sciences: Computational Life Sciences
language:en
Short-container-title:Interdiscip Sci Comput Life Sci

Author:

Cong Hanhan,Liu Hong,Cao Yi,Chen Yuehui,Liang Cheng

Funder

National Natural Science Foundation of China

Shandong Provincial Natural Science Foundation

University Innovation Team Project of Jinan

Publisher

Springer Science and Business Media LLC

Subject

Health Informatics,Computer Science Applications,General Biochemistry, Genetics and Molecular Biology

Link

https://link.springer.com/content/pdf/10.1007/s12539-021-00496-7.pdf

Reference78 articles.

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2. Chen X, Shi SP, Suo SB, Xu HD, Qiu JD (2015) Proteomic analysis and prediction of human phosphorylation sites in subcellular level reveal subcellular specificity. Bioinformatics 31(2):194–200. https://doi.org/10.1093/bioinformatics/btu598

3. Zhang W, Xue X, Xie C, Li Y, Liu J, Chen H, Li G (2021) CEGSO: boosting essential proteins prediction by integrating protein complex, gene expression, gene ontology, subcellular localization and orthology information. Interdiscip Sci Comput Life Sci. https://doi.org/10.1007/s12539-021-00426-7

4. Thul PJ, Åkesson L, Wiking M, Mahdessian D, Geladaki A, Blal HA et al (2017) A subcellular map of the human proteome. Science. https://doi.org/10.1126/science.aal3321

5. Yao L, Wang H, Bin Y (2021) Predicting hot spot residues at protein–DNA binding interfaces based on sequence information. Interdiscip Sci Comput Life Sci 13(1):1–11. https://doi.org/10.1007/s12539-020-00399-z

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