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MePred-RF

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Predicts and analyzes protein methylation sites, particularly for large-scale genome projects. MePred-RF is a machine-learning-based method for protein methylation site prediction. This approach exploits sequence information alone in its feature representation of proteins. This prediction procedure has four phases: 1) data pre-processing, 2) feature representation, 3) feature selection, and 4) prediction engine.

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MePred-RF classification

MePred-RF specifications

Software type:
Application/Script
Restrictions to use:
None
Input format:
FASTA
Stability:
Stable
Interface:
Web user interface
Input data:
Some peptide sequences.
Computer skills:
Basic
Maintained:
Yes

MePred-RF support

Maintainers

  • Quan Zou <>
  • Zhi-Liang Ji <>

Additional information

http://server.malab.cn/MePred-RF/about.jsp

Credits

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Publications

Institution(s)

School of Computer Science and Technology, Tianjin University, Tianjin, China; State Key Laboratory of Stress Cell Biology, School of Life Sciences, Xiamen University, Xiamen, China; The Key Laboratory for Chemical Biology of Fujian Province, Xiamen University, Xiamen, China

Funding source(s)

Supported by the National Natural Science Foundation of China (No. 61370010, No. 31271405, and No. 31671362).

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