34,192 research outputs found
On Optimal Family of Codes for Archival DNA Storage
DNA based storage systems received attention by many researchers. This
includes archival and re-writable random access DNA based storage systems. In
this work, we have developed an efficient technique to encode the data into DNA
sequence by using non-linear families of ternary codes. In particular, we
proposes an algorithm to encode data into DNA with high information storage
density and better error correction using a sub code of Golay code.
Theoretically, 115 exabytes (EB) data can be stored in one gram of DNA by our
method.Comment: Supplementary file and the software DNA Cloud 2.0 is available at
http://www.guptalab.org/dnacloud This is the preliminary version of the paper
that appeared in Proceedings of IWSDA 2015, pp. 143--14
Mutually Uncorrelated Primers for DNA-Based Data Storage
We introduce the notion of weakly mutually uncorrelated (WMU) sequences,
motivated by applications in DNA-based data storage systems and for
synchronization of communication devices. WMU sequences are characterized by
the property that no sufficiently long suffix of one sequence is the prefix of
the same or another sequence. WMU sequences used for primer design in DNA-based
data storage systems are also required to be at large mutual Hamming distance
from each other, have balanced compositions of symbols, and avoid primer-dimer
byproducts. We derive bounds on the size of WMU and various constrained WMU
codes and present a number of constructions for balanced, error-correcting,
primer-dimer free WMU codes using Dyck paths, prefix-synchronized and cyclic
codes.Comment: 14 pages, 3 figures, 1 Table. arXiv admin note: text overlap with
arXiv:1601.0817
Reconstruction Codes for DNA Sequences with Uniform Tandem-Duplication Errors
DNA as a data storage medium has several advantages, including far greater
data density compared to electronic media. We propose that schemes for data
storage in the DNA of living organisms may benefit from studying the
reconstruction problem, which is applicable whenever multiple reads of noisy
data are available. This strategy is uniquely suited to the medium, which
inherently replicates stored data in multiple distinct ways, caused by
mutations. We consider noise introduced solely by uniform tandem-duplication,
and utilize the relation to constant-weight integer codes in the Manhattan
metric. By bounding the intersection of the cross-polytope with hyperplanes, we
prove the existence of reconstruction codes with greater capacity than known
error-correcting codes, which we can determine analytically for any set of
parameters.Comment: 11 pages, 2 figures, Latex; version accepted for publicatio
On Coding over Sliced Information
The interest in channel models in which the data is sent as an unordered set
of binary strings has increased lately, due to emerging applications in DNA
storage, among others. In this paper we analyze the minimal redundancy of
binary codes for this channel under substitution errors, and provide several
constructions, some of which are shown to be asymptotically optimal up to
constants. The surprising result in this paper is that while the information
vector is sliced into a set of unordered strings, the amount of redundant bits
that are required to correct errors is order-wise equivalent to the amount
required in the classical error correcting paradigm
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