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BioCode: Two biologically compatible Algorithms for embedding data in non-coding and coding regions of DNA

机译:BioCode:两种生物兼容算法,可将数据嵌入DNA的非编码和编码区域

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Background In recent times, the application of deoxyribonucleic acid (DNA) has diversified with the emergence of fields such as DNA computing and DNA data embedding. DNA data embedding, also known as DNA watermarking or DNA steganography, aims to develop robust algorithms for encoding non-genetic information in DNA. Inherently DNA is a digital medium whereby the nucleotide bases act as digital symbols, a fact which underpins all bioinformatics techniques, and which also makes trivial information encoding using DNA straightforward. However, the situation is more complex in methods which aim at embedding information in the genomes of living organisms. DNA is susceptible to mutations, which act as a noisy channel from the point of view of information encoded using DNA. This means that the DNA data embedding field is closely related to digital communications. Moreover it is a particularly unique digital communications area, because important biological constraints must be observed by all methods. Many DNA data embedding algorithms have been presented to date, all of which operate in one of two regions: non-coding DNA (ncDNA) or protein-coding DNA (pcDNA). Results This paper proposes two novel DNA data embedding algorithms jointly called BioCode, which operate in ncDNA and pcDNA, respectively, and which comply fully with stricter biological restrictions. Existing methods comply with some elementary biological constraints, such as preserving protein translation in pcDNA. However there exist further biological restrictions which no DNA data embedding methods to date account for. Observing these constraints is key to increasing the biocompatibility and in turn, the robustness of information encoded in DNA. Conclusion The algorithms encode information in near optimal ways from a coding point of view, as we demonstrate by means of theoretical and empirical ( in silico ) analyses. Also, they are shown to encode information in a robust way, such that mutations have isolated effects. Furthermore, the preservation of codon statistics, while achieving a near-optimum embedding rate, implies that BioCode pcDNA is also a near-optimum first-order steganographic method.
机译:背景技术近年来,随着DNA计算和DNA数据嵌入等领域的出现,脱氧核糖核酸(DNA)的应用变得多样化。 DNA数据嵌入(也称为DNA水印或DNA隐写术)旨在开发强大的算法来编码DNA中的非遗传​​信息。 DNA本身就是一种数字介质,核苷酸碱基充当数字符号,这是所有生物信息技术的基础,并且也使使用DNA进行琐碎的信息编码变得简单。但是,在旨在将信息嵌入生物体基因组中的方法中,情况更为复杂。 DNA易受突变的影响,从使用DNA编码的信息的角度来看,突变会充当嘈杂的通道。这意味着DNA数据嵌入领域与数字通信密切相关。此外,这是一个特别独特的数字通信领域,因为必须通过所有方法来观察重要的生物学限制。迄今为止,已经提出了许多DNA数据嵌入算法,所有算法都在两个区域之一中运行:非编码DNA(ncDNA)或蛋白质编码DNA(pcDNA)。结果本文提出了两种新颖的DNA数据嵌入算法,共同称为BioCode,分别在ncDNA和pcDNA上运行,并且完全符合更严格的生物学限制。现有方法符合一些基本的生物学限制,例如在pcDNA中保留蛋白质翻译。但是,存在进一步的生物学限制,迄今为止没有DNA数据嵌入方法能够解决。遵守这些限制条件对于提高生物相容性以及提高DNA编码信息的鲁棒性至关重要。结束语正如我们通过理论和经验(计算机分析)分析所证明的那样,这些算法从编码的角度以接近最佳的方式对信息进行编码。同样,它们被显示为以可靠的方式编码信息,从而使突变具有孤立的作用。此外,密码子统计的保存,同时实现了接近最佳的包埋率,这意味着BioCode pcDNA也是接近最佳的一阶隐写方法。

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