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In Current pharmaceutical design ; h5-index 57.0

Bioluminescent proteins (BLPs) are widely distributed in many living organisms that act as a key role of light emission in the bioluminescence. Bioluminescence serves various functions in finding food and protecting themselves of lives of creatures. With the routinely biotechnological application of bioluminescence, it is recognized to be essential for many medical, commercial and other general technological advances. Therefore, the prediction and characterization of BLPs is significant and eager in that it could help to explore more secrets about bioluminescence and promote the development of application of bioluminescence. Since the experimental methods are money and time-consuming for BLPs identification, bioinformatics tools have played important parts for fast and accurately predicting BLPs by combining their sequences information with machine learning methods. In this review, we summarized and compared the application of machine learning methods in the prediction of BLPs from different aspects. We wish that this review will provide insights and inspirations for the researches on BLPs.

Zhang Dan, Guan Zheng-Xing, Zhang Zi-Mei, Li Shi-Hao, Dao Fu-Ying, Tang Hua, Lin Hao


bioluminescent proteins, feature analysis, machine learning methods, sequence-derived