12 papers · ranked by Valyu relevance
Jin Sima, Netanel Raviv, Jehoshua Bruck
Encoding data as a set of unordered strings is receiving great attention as it captures one of the basic features of DNA storage systems. However, the challenge of constructing optimal redundancy codes for this channel remained elusive. In this paper, we address this problem and present an order-wise optimal…
Daniella Bar-Lev, Adir Kobovich, Orian Leitersdorf, Eitan Yaakobi
—This paper presents a novel approach to address the constrained coding challenge of generating almost-balanced sequences. While strictly balanced sequences have been well studied in the past, the problem of designing efficient algorithms with small redundancy, preferably constant or even a single bit, for almost…
Amir Said
Entropy coding, compression, complexity This introduction to arithmetic coding is divided in two parts. The first explains how and why arithmetic coding works. We start presenting it in very general terms, so that its simplicity is not lost under layers of implementation details. Next, we show some of its basic…
Robert Bamler
Entropy coding is the backbone data compression. Novel machine-learning based compression methods often use a new entropy coder called Asymmetric Numeral Systems (ANS) [Duda et al., 2015], which provides very close to optimal bitrates and simplifies [Townsend et al., 2019] advanced compression techniques such as…
M. Gao, Kenneth W. Shum
single-deletion-correcting permutation codes Authors: ['M. Gao' 'Kenneth W. Shum'] A permutation code is a nonlinear code whose codewords are permutation of a set of symbols. We consider the use of permutation code in the deletion channel, and consider the symbol-invariant error model, meaning that the values of the…
Mohammad Hosseini
—Today, with the growing demands of information storage and data transfer, data compression is becoming increasingly important. Data Compression is a technique which is used to decrease the size of data. This is very useful when some huge files have to be transferred over networks or being stored on a data storage…
Melih Şahin, Beyza E. Ortlek, Özgür B. Akan
(IoBNT) Authors: ['Melih Şahin' 'Beyza E. Ortlek' 'Özgür B. Akan'] Abstract—Molecular Communication (MC) has emerged as a promising paradigm employing molecules to transfer information at the nano-scale. Unlike MC channel coding, MC source coding has remained mostly an unexplored area of research. In a recent paper…
Rıza Özçelik, Laura van Weesep, Sarah de Ruiter, Francesca Grisoni
In this work, we introduce peptidy -- a lightweight Python library that facilitates converting peptides (expressed as aminoacid sequences) to numerical representations suited to machine learning. peptidy is free from external dependencies, integrates seamlessly into modern Python environments, and supports a range of…
Hajime Tamaki, Yoh Matsuki
Fast magic-angle spinning (MAS) solid-state NMR spectroscopy is a powerful tool for gaining structural and dynamics in-formation on solid proteins. To access such information site-specifically, the signal assignment process is unavoidable. In the assignment process, Cα and Cβ chemical shifts are of paramount importance…
Authors not listed
Experimental design plays an important role in efficiently acquiring informative data for system characterization and deriving robust conclusions under resource limitations. Recent advancements in high-throughput experimentation coupled with machine learning have notably improved experimental procedures. While Bayesian…
Jürgen Köfinger, Gerhard Hummer
The proper balancing of information from experiment and theory is a long-standing problem in the analysis of noisy and incomplete data. Viewed as a Pareto optimization problem, improved agreement with the experimental data comes at the expense of growing inconsistencies with the theoretical reference model. Here, we…
Jürgen Köfinger, Gerhard Hummer
The proper balancing of information from experiment and theory is a long-standing problem in the analysis of noisy and incomplete data. Viewed as a Pareto optimization problem, improved agreement with the experimental data comes at the expense of growing inconsistencies with the theoretical reference model. Here, we…