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- W3213133098 abstract "Chaos game representation (CGR), a milestone in graphical bioinformatics, has become a powerful tool regarding alignment-free sequence comparison and feature encoding for machine learning. The algorithm maps a sequence to 2-dimensional space, while an extension of the CGR, the so-called frequency matrix representation (FCGR), transforms sequences of different lengths into equal-sized images or matrices. The CGR is a generalized Markov chain and includes various properties, which allow a unique representation of a sequence. Therefore, it has a broad spectrum of applications in bioinformatics, such as sequence comparison and phylogenetic analysis and as an encoding of sequences for machine learning. This review introduces the construction of CGRs and FCGRs, their applications on DNA and proteins, and gives an overview of recent applications and progress in bioinformatics." @default.
- W3213133098 created "2021-11-22" @default.
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- W3213133098 date "2021-01-01" @default.
- W3213133098 modified "2023-10-13" @default.
- W3213133098 title "Chaos game representation and its applications in bioinformatics" @default.
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- W3213133098 doi "https://doi.org/10.1016/j.csbj.2021.11.008" @default.
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