Abstract Information theory (IT) addresses the analysis of communication systems and has
been widely applied in molecular biology. In particular, alignment-free sequence analysis …

This article highlights advantages of entropy-based genetic diversity measures, at levels
from gene expression to landscapes. Shannon's entropy-based diversity is the standard for …

Most data mining algorithms require the setting of many input parameters. Two main
dangers of working with parameter-laden algorithms are the following. First, incorrect …

Recent research has considered DNA as a medium for ultra-scale computation and for ultra-
compact information storage. One potential key application is DNA-based, molecular …

Motivation: Most existing approaches for phylogenetic inference use multiple alignment of
sequences and assume some sort of an evolutionary model. The multiple alignment strategy …

This paper introduces a novel algorithm for biological sequence compression that makes
use of both statistical properties and repetition within sequences. A panel of experts is …

The vast majority of data mining algorithms require the setting of many input parameters.
The dangers of working with parameter-laden algorithms are twofold. First, incorrect settings …

Partly motivated by entropy-estimation problems in neuroscience, we present a detailed and
extensive comparison between some of the most popular and effective entropy estimation …

Motivation: It is well known that the regulatory regions of genomes are highly repetitive. They
are rich in direct, symmetric and complemented repeats, and there is no doubt about the …

Research in the genomic sciences is confronted with the volume of sequencing and
resequencing data increasing at a higher pace than that of data storage and communication …