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We study the primary DNA structure of four of the most completely sequenced human chromosomes (including chromosome 19 which is the most dense in coding), using Non-extensive Statistics. We show that the exponents governing the decay of the…
In this paper, we review the literature on statistical long-range correlation in DNA sequences. We examine the current evidence for these correlations, and conclude that a mixture of many length scales (including some relatively long ones)…
Single molecule studies, at constant force, of the separation of double-stranded DNA into two separated single strands may provide information relevant to the dynamics of DNA replication. At constant applied force, theory predicts that the…
Evidence has mounted that Type Ia and core-collapse (CC) supernovae (SNe) can have substantial deviations from spherical symmetry; one such piece of evidence is the complex morphologies of supernova remnants (SNRs). However, the relative…
Selecting appropriate datasets is critical in modern computer vision. However, no general-purpose tools exist to evaluate the extent to which two datasets differ. For this, we propose representing images - and by extension datasets - using…
We show that textual analysis of microbial genomes reveal telling footprints of the early evolution of the genomes. The frequencies of word occurrence of random DNA sequences considered as texts in their four nucleotides are expected to…
Understanding supernova (SN) progenitors remains a major challenge in astrophysics, as it involves untangling the complex interplay between stellar physics (e.g., evolution, binarity, explosion) and environments (e.g., metallicity, star…
We present observational constraints on the nature of core-collapse supernovae through an investigation into their radial distributions with respect to those of young and old stellar populations within their host galaxies, as traced by…
A catalogue of 231 Galactic supernova remnants (SNRs) is presented, and the selection effects applicable to the identification of remnants at radio wavelengths are discussed. In addition to missing low surface brightness remnants, small…
Recent studies have shown that single-stranded viral RNAs fold into more compact structures than random RNA sequences with similar chemical composition and identical length. Based on this comparison it has been suggested that wild-type…
This thesis studies how the segmentation results, produced by convolutional neural networks (CNN), is different from each other when applied to small biomedical datasets. We use different architectures, parameters and hyper-parameters,…
Recent approaches for music source separation are almost exclusively based on deep neural networks, mostly employing recurrent neural networks (RNNs). Although RNNs are in many cases superior than other types of deep neural networks for…
The ~4-Mbp basic genome shared by 32 independent isolates of E. coli representing considerable population diversity has been approximated by whole-genome multiple-alignment and computational filtering designed to remove mobile elements and…
Large whole-genome sequencing projects have provided access to much of the rare variation in human populations, which is highly informative about population structure and recent demography. Here, we show how the age of rare variants can be…
Context.This is the first paper of a series aiming to determine the fractions and birth rates of various types of supernovae (SNe) in the local Universe. Aims. In this paper, we aim to construct a complete sample of SNe in the nearby…
Supernova remnants (SNRs) are the aftermath of massive stellar explosions or of a white dwarf in a binary system, representing critical phases in the life cycle of stars and playing an important role in galactic evolution. Physical…
Regularization techniques help prevent overfitting and therefore improve the ability of convolutional neural networks (CNNs) to generalize. One reason for overfitting is the complex co-adaptations among different parts of the network, which…
There are often multiple ways to implement the same requirement in source code. Different implementation choices can result in code snippets that are similar, and have been defined in multiple ways: code clones, examples, simions and…
When using Convolutional Neural Networks (CNNs) for segmentation of organs and lesions in medical images, the conventional approach is to work with inputs and outputs either as single slice (2D) or whole volumes (3D). One common…
Since the sequencing of large genomes, many statistical features of their sequences have been found. One intriguing feature is that certain subsequences are much more abundant than others. In fact, abundances of subsequences of a given…