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Regular Paper

Synthetic Lethal Interactions Prediction Based on Multiple Similarity Measures Fusion

Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China
Department of Biotechnology, Beijing Institute of Radiation Medicine, Beijing 100850, China
Experimental Center, Beijing Friendship Hospital, Capital Medical University, Beijing 100850, China

†The two authors contributed equally to this work.the two authors jointly supervised this work]]>

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Abstract

The synthetic lethality (SL) relationship arises when a combination of deficiencies in two genes leads to cell death, whereas a deficiency in either one of the two genes does not. The survival of the mutant tumor cells depends on the SL partners of the mutant gene, thereby the cancer cells could be selectively killed by inhibiting the SL partners of the oncogenic genes but normal cells could not. Therefore, there is an urgent need to develop more efficient computational methods of SL pairs identification for cancer targeted therapy. In this paper, we propose a new approach based on similarity fusion to predict SL pairs. Multiple types of gene similarity measures are integrated and k-nearest neighbors algorithm (k-NN) is applied to achieve the similarity-based classification task between gene pairs. As a similarity-based method, our method demonstrated excellent performance in multiple experiments. Besides the effectiveness of our method, the ease of use and expansibility can also make our method more widely used in practice.

Keywords

synthetic lethalitysimilarity measures fusionk-nearest neighbormulti-dimensional data

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Journal of Computer Science and Technology
Volume 36 Issue 2,
March 2021
Pages 261-275
DOI: 10.1007/s11390-021-0866-2
Cite this article:
Wu L-L, Wen Y-Q, Yang X-X, et al. Synthetic Lethal Interactions Prediction Based on Multiple Similarity Measures Fusion. Journal of Computer Science and Technology, 2021, 36(2): 261-275. https://doi.org/10.1007/s11390-021-0866-2

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Received: 03 August 2020
Accepted: 28 February 2021
Published: 05 March 2021
©Institute of Computing Technology, Chinese Academy of Sciences 2021
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