5 papers · ranked by Valyu relevance
Ian Holmes
We describe a strategy for constructing codes for DNA-based information storage by serial composition of weighted finite-state transducers. The resulting state machines can integrate correction of substitution errors; synchronization by interleaving watermark and periodic marker signals; conversion from binary to…
Inbal Preuss, Michael Rosenberg, Zohar Yakhini, Leon Anavy
With the world generating digital data at an exponential rate, DNA has emerged as a promising archival medium. It offers a more efficient and long-lasting digital storage solution due to its durability, physical density, and high information capacity. Research in the field includes the development of encoding schemes…
Neha Periwal, Priya Sharma, Pooja Arora, Saurabh Pandey + 2 more
Classification among coding (CDS) and non-coding RNA (ncRNA) sequences is a challenge and several machine learning models have been developed for the same. Since the frequency of curated coding sequences is many-folds as compared to that of the ncRNAs, we devised a novel approach to work with the complete datasets from…
Xuyang Zhao, Junyao Li, Qingyuan Fan, Jing Dai + 5 more
DNA, as the origin for the genetic information flow, has also been a compelling alternative to non-volatile information storage medium. Reading digital information from this highly dense but lightweighted medium nowadays relied on conventional next-generation sequencing (NGS), which involves ‘wash and read’ cycles for…
Rod Rinkus
The brain is believed to implement probabilistic reasoning and to represent information via population, or distributed, coding. Most previous population-based probabilistic (PPC) theories share several basic properties: 1) continuous-valued neurons (units); 2) fully/densely-distributed codes, i.e., all/most coding…