Coding for Optimized Writing Rate in DNA Storage

A method for encoding information in DNA sequences is described. The method is based on the precisionresolution framework, and is aimed to work in conjunction with a recently suggested terminator-free template independent DNA synthesis method. The suggested method optimizes the amount of information bits per synthesis time unit, namely, the writing rate. Additionally, the encoding scheme studied here takes into account the existence of multiple copies of the DNA sequence, which are independently distorted. Finally, quantizers for various run-length distributions are designed

Encoding DNA sequences by integer chaos game representation

DNA sequences are fundamental for encoding genetic information. The genetic information may not only be understood by symbolic sequences but also from the hidden signals inside the sequences. The symbolic sequences need to be transformed into numerical sequences so the hidden signals can be revealed by signal processing techniques. All current transformation methods encode DNA sequences into numerical values of the same length. These representations have limitations in the applications of genomic signal compression, encryption, and steganography. We propose an integer chaos game representation (iCGR) of DNA sequences and a lossless encoding method DNA sequences by the iCGR. In the iCGR method, a DNA sequence is represented by the iterated function of the nucleotides and their positions in the sequence. Then the DNA sequence can be uniquely encoded and recovered using three integers from iCGR. One integer is the sequence length and the other two integers represent the accumulated distributions of nucleotides in the sequence. The integer encoding scheme can compress a DNA sequence by 2 bits per nucleotide. The integer representation of DNA sequences provides a prospective tool for sequence compression, encryption, and steganography. The Python programs in this study are freely available to the public at https://github.com/cyinbox/iCG

Identification of a Novel 81-kDa Component of the Xenopus Origin Recognition Complex

The Xenopus origin recognition complex is essential for chromosomal DNA replication in cell-free extracts. We have immunopurified the Xenopus origin recognition complex with anti-Xorc2 antibodies and analyzed its composition and properties. Xorc2 (p63) is specifically associated with Xorc1 (p115) and up to four additional polypeptides (p81, p78, p45, and p40). The cDNA encoding p81 is highly homologous to various expressed sequence tags from humans and mice encoding a protein of previously unknown function. Immunodepletion of p81 from Xenopus egg extracts, which also results in the removal of Xorc2, completely abolishes chromosomal DNA replication. Thus, p81 appears to play a crucial role at S phase in higher eukaryotes

Late phase inhibition of murine cytomegalovirus replication by synergistic action of interferon-gamma and tumour necrosis factor

We have shown previously that the antiviral function of CD4+ T lymphocytes against murine cytomegalovirus (MCMV) is associated with the release of interferon- (IFN-). We now demonstrate that IFN- and tumour necrosis factor alpha (TNF-) display synergism in their antiviral activity. As little as 2 ng/ml of IFN- and TNF- reduced the virus yield by about three orders of magnitude. There was no effect on immediate early (IE) and early (E) gene expression as far as the candidate genes IE1, E1 and those encoding the major DNA-binding protein and the DNA polymerase were concerned. Late gene transcription, assayed by the candidate genes encoding glycoprotein B and the MCMV homologue of ICP 18.5, was blocked and MCMV DNA replication was found to be reduced but not halted. The most prominent finding of the cytokine effect, seen by electron microscopy, was an alteration of nucleocapsid formation. Altogether, the synergism is multifaceted and acts at more than one stage during viral morphogenesis. Because the cytokines clearly do not act at an early stage of infection we conclude that the mode of cytokine activity differs between alpha- and betaherpesviruses

Capacity of DNA Data Embedding Under Substitution Mutations

A number of methods have been proposed over the last decade for encoding information using deoxyribonucleic acid (DNA), giving rise to the emerging area of DNA data embedding. Since a DNA sequence is conceptually equivalent to a sequence of quaternary symbols (bases), DNA data embedding (diversely called DNA watermarking or DNA steganography) can be seen as a digital communications problem where channel errors are tantamount to mutations of DNA bases. Depending on the use of coding or noncoding DNA hosts, which, respectively, denote DNA segments that can or cannot be translated into proteins, DNA data embedding is essentially a problem of communications with or without side information at the encoder. In this paper the Shannon capacity of DNA data embedding is obtained for the case in which DNA sequences are subject to substitution mutations modelled using the Kimura model from molecular evolution studies. Inferences are also drawn with respect to the biological implications of some of the results presented.Comment: 22 pages, 13 figures; preliminary versions of this work were presented at the SPIE Media Forensics and Security XII conference (January 2010) and at the IEEE ICASSP conference (March 2010

Coding for Optimized Writing Rate in DNA Storage

A method for encoding information in DNA sequences is described. The method is based on the precision-resolution framework, and is aimed to work in conjunction with a recently suggested terminator-free template independent DNA synthesis method. The suggested method optimizes the amount of information bits per synthesis time unit, namely, the writing rate. Additionally, the encoding scheme studied here takes into account the existence of multiple copies of the DNA sequence, which are independently distorted. Finally, quantizers for various run-length distributions are designed.Comment: To appear in ISIT 202

Fast matrix multiplication techniques based on the Adleman-Lipton model

On distributed memory electronic computers, the implementation and association of fast parallel matrix multiplication algorithms has yielded astounding results and insights. In this discourse, we use the tools of molecular biology to demonstrate the theoretical encoding of Strassen's fast matrix multiplication algorithm with DNA based on an $n$-moduli set in the residue number system, thereby demonstrating the viability of computational mathematics with DNA. As a result, a general scalable implementation of this model in the DNA computing paradigm is presented and can be generalized to the application of \emph{all} fast matrix multiplication algorithms on a DNA computer. We also discuss the practical capabilities and issues of this scalable implementation. Fast methods of matrix computations with DNA are important because they also allow for the efficient implementation of other algorithms (i.e. inversion, computing determinants, and graph theory) with DNA.Comment: To appear in the International Journal of Computer Engineering Research. Minor changes made to make the preprint as similar as possible to the published versio