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Related papers: Spectral concepts in genome informational analysis

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The cosmic ray energy distributions contain spectral features, that is narrow energy regions where the slope of the spectrum changes rapidly. The identification and study of these features is of great importance to understand the…

High Energy Astrophysical Phenomena · Physics 2017-12-27 Paolo Lipari

This note is to indicate the new sphere of applicability of the method developed by Mlak as well as by the author. Restoring those ideas is summoned by current developments concerning $K$-spectral sets on numerical ranges.

Functional Analysis · Mathematics 2009-03-20 F. H. Szafraniec

Raman spectroscopy provides spectral information related to the specific molecular structures of substances and has been well established as a powerful tool for studying biological tissues and diagnosing diseases. This article reviews…

Spectroscopy is the most important method for probing the structure of molecules. However, predicting molecular spectra on classical computers is computationally expensive, with the most accurate methods having a cost that grows…

Quantum Physics · Physics 2025-10-06 Liam P. Flew , Ivan Kassal

In medicine, visualizing chromosomes is important for medical diagnostics, drug development, and biomedical research. Unfortunately, chromosomes often overlap and it is necessary to identify and distinguish between the overlapping…

Computer Vision and Pattern Recognition · Computer Science 2017-12-21 R. Lily Hu , Jeremy Karnowski , Ross Fadely , Jean-Patrick Pommier

Let $\Omega$ be an open convex domain of the complex plane. We study constants K such that $\Omega$ is K-spectral or complete K-spectral for each continuous linear Hilbert space operator with numerical range included in $\Omega$. Several…

Functional Analysis · Mathematics 2018-06-05 Catalin Badea , Michel Crouzeix , Bernard Delyon

Periodic patterns play the important regulatory and structural roles in genomic DNA sequences. Commonly, the underlying periodicities should be understood in a broad statistical sense, since the corresponding periodic patterns have been…

Quantitative Methods · Quantitative Biology 2011-04-05 V. R. Chechetkin

Fractals with different levels of self-similarity and magnification are defined as reduced fractals. It is shown that spectra of these reduced fractals can be constructed and used to describe levels of complexity of natural phenomena.…

Quantitative Methods · Quantitative Biology 2023-01-16 Diana T. Pham , Zdzislaw E. Musielak

The purpose of this review is to introduce the reader to graph kernels and the corresponding literature, with an emphasis on those with direct application to chemoinformatics. Graph kernels are functions that allow for the inference of…

Machine Learning · Statistics 2022-08-29 James Young

Beginning with a historical account of the spectral classification, its refinement through additional criteria is presented. The line strengths and ratios used in two dimensional classifications of each spectral class are described. A…

Solar and Stellar Astrophysics · Physics 2015-05-18 Sunetra Giridhar

Segmentation and genome annotation (SAGA) algorithms are widely used to understand genome activity and gene regulation. These algorithms take as input epigenomic datasets, such as chromatin immunoprecipitation-sequencing (ChIP-seq)…

Genomics · Quantitative Biology 2022-06-14 Maxwell W Libbrecht , Rachel CW Chan , Michael M Hoffman

The density function of the limiting spectral distribution of general sample covariance matrices is usually unknown. We propose to use kernel estimators which are proved to be consistent. A simulation study is also conducted to show the…

Statistics Theory · Mathematics 2012-11-15 Bing-Yi Jing , Guangming Pan , Qi-Man Shao , Wang Zhou

We experimentally demonstrated a spectral imaging scheme with dual compressed sensing. With the dimensions of spectral and spatial information both compressed, the spectral image of a colored object can be obtained with only a single point…

Optics · Physics 2015-02-17 Xue-Feng Liu , Wen-Kai Yu , Xu-Ri Yao , Bin Dai , Long-Zhen Li , Chao Wang , Guang-Jie Zhai

This article introduces the physics of information in the context of molecular biology and genomics. Entropy and information, the two central concepts of Shannon's theory of information and communication, are often confused with each other…

Biomolecules · Quantitative Biology 2007-05-23 Christoph Adami

The notions of spectral measures and spectral classes, which are well known for graphs, are generalized and investigated for oriented hypergraphs.

Combinatorics · Mathematics 2021-02-16 Raffaella Mulas

For convex optimization problems Bregman divergences appear as regret functions. Such regret functions can be defined on any convex set but if a sufficiency condition is added the regret function must be proportional to information…

Information Theory · Computer Science 2017-02-20 Peter Harremoës

A proper treatment of K-mixing is the key to understanding K-isomers. Here, we present a method based on the projected shell model. This method differs from the usual description of multi-quasiparticle states by introducing a transformation…

Nuclear Theory · Physics 2016-09-08 Yang Sun

Phylogenetically informed k-mers, or phylo-k-mers for short, are k-mers that are predicted to appear within a given genomic region at predefined locations of a fixed phylogeny. Given a reference alignment for this genomic region and…

Quantitative Methods · Quantitative Biology 2022-09-21 Nikolai Romashchenko , Benjamin Linard , Fabio Pardi , Eric Rivals

Genome rearrangements can be modeled as $k$-breaks, which break a genome at k positions and glue the resulting fragments in a new order. In particular, reversals, translocations, fusions, and fissions are modeled as $2$-breaks, and…

Genomics · Quantitative Biology 2017-02-21 Nikita Alexeev , Anna Pologova , Max A. Alekseyev

Understanding functional organization of genetic information is a major challenge in modern biology. Following the initial publication of the human genome sequence in 2001, advances in high-throughput measurement technologies and efficient…

Machine Learning · Statistics 2011-03-01 Leo Lahti