Reversal and Transposition Distance on Unbalanced Genomes Using Intergenic Information.

The most common way to calculate the rearrangement distance between two genomes is to use the size of a minimum length sequence of rearrangements that transforms one of the two given genomes into the other, where the genomes are represented as permutations using only their gene order, based on the assumption that genomes have the same gene content. With the advance of research in genome rearrangements, new works extended the classical models by either considering genomes with different gene content (unbalanced genomes) or including more genomic characteristics to the mathematical representation of the genomes, such as the distribution of intergenic regions sizes. In this study, we study the Reversal, Transposition, and Indel (Insertion and Deletion) Distance using intergenic information, which allows comparing unbalanced genomes, because indels are included in the rearrangement model (i.

Rearrangement distance with reversals, indels, and moves in intergenic regions on signed and unsigned permutations.

Genome rearrangement events are widely used to estimate a minimum-size sequence of mutations capable of transforming a genome into another. The length of this sequence is called distance, and determining it is the main goal in genome rearrangement distance problems. Problems in the genome rearrangement field differ regarding the set of rearrangement events allowed and the genome representation.

Using machine learning pipeline to predict entry into the attack zone in football.

Sports sciences are increasingly data-intensive nowadays since computational tools can extract information from large amounts of data and derive insights from athlete performances during the competition. This paper addresses a performance prediction problem in soccer, a popular collective sport modality played by two teams competing against each other in the same field. In a soccer game, teams score points by placing the ball into the opponent's goal and the winner is the team with the highest count of goals.

Reversal and Indel Distance With Intergenic Region Information.

Recent works on genome rearrangements have shown that incorporating intergenic region information along with gene order in models provides better estimations for the rearrangement distance than using gene order alone. The reversal distance is one of the main problems in genome rearrangements. It has a polynomial time algorithm when only gene order is used to model genomes, assuming that repeated genes do not exist and that gene orientation is known, even when the genomes have distinct gene sets.

Genome Rearrangement Distance With a Flexible Intergenic Regions Aspect.

Most mathematical models for genome rearrangement problems have considered only gene order. In this way, the rearrangement distance considering some set of events, such as reversal and transposition events, is commonly defined as the minimum number of rearrangement events that transform the gene order from a genome G into the gene order from a genome G. Recent works initiate incorporating more information such as the sizes of the intergenic regions (i.

An improved approximation algorithm for the reversal and transposition distance considering gene order and intergenic sizes.

Background: In the comparative genomics field, one of the goals is to estimate a sequence of genetic changes capable of transforming a genome into another. Genome rearrangement events are mutations that can alter the genetic content or the arrangement of elements from the genome. Reversal and transposition are two of the most studied genome rearrangement events.

Incorporating intergenic regions into reversal and transposition distances with indels.

Problems in the genome rearrangement field are often formulated in terms of pairwise genome comparison: given two genomes [Formula: see text] and [Formula: see text], find the minimum number of genome rearrangements that may have occurred during the evolutionary process. This broad definition lacks at least two important considerations: the first being which features are extracted from genomes to create a useful mathematical model, and the second being which types of genome rearrangement events should be represented. Regarding the first consideration, seminal works in the genome rearrangement field solely used gene order to represent genomes as permutations of integer numbers, neglecting many important aspects like gene duplication, intergenic regions, and complex interactions between genes.

Labeled Cycle Graph for Transposition and Indel Distance.

In the comparative genomics field, one way to infer the evolutionary distance between two organisms of related species is by finding the minimum number of large-scale mutations, called genome rearrangements, that transform one genome into the other. This number is referred to as the . Since problems in this area emerged in the mid-1990s, several genome rearrangements have been proposed.

Prostatic Artery Embolization: Indications, Preparation, Techniques, Imaging Evaluation, Reporting, and Complications.

Benign prostatic hyperplasia (BPH) is a noncancerous growth of the transitional zone of the prostate, which surrounds the prostatic urethra. Consequently, it can cause lower urinary tract symptoms (LUTS) and bladder outlet obstruction symptoms that may substantially reduce a patient's quality of life. Several treatments are available for BPH, including medications such as α-blockers and 5α-reductase inhibitors and surgical options including transurethral resection of the prostate and prostatectomy.

Heuristics for Genome Rearrangement Distance With Replicated Genes.

In comparative genomics, one goal is to find similarities between genomes of different organisms. Comparisons using genome features like genes, gene order, and regulatory sequences are carried out with this purpose in mind. Genome rearrangements are mutational events that affect large extensions of the genome.

Reversals and transpositions distance with proportion restriction.

In the field of comparative genomics, one way of comparing two genomes is through the analysis of how they distinguish themselves based on a set of mutations called rearrangement events. When considering that genomes undergo different types of rearrangements, it can be assumed that some events are more common than others. To model this assumption, one can assign different weights to different events, where common events tend to cost less than others.

Sorting Permutations by Intergenic Operations.

Genome Rearrangements are events that affect large stretches of genomes during evolution. Many mathematical models have been used to estimate the evolutionary distance between two genomes based on genome rearrangements. However, most of them focused on the (order of the) genes of a genome, disregarding other important elements in it.

Genome Rearrangement Distance with Reversals, Transpositions, and Indels.

The rearrangement distance is a well-known problem in the field of comparative genomics. Given two genomes, the rearrangement distance is the minimum number of rearrangements in a set of allowed rearrangements (rearrangement model), which transforms one genome into the other. In rearrangement distance problems, a genome is modeled as a string, where each element represents a conserved region within the two genomes.

Sorting Signed Permutations by Intergenic Reversals.

Genome rearrangements are mutations affecting large portions of a genome, and a reversal is one of the most studied genome rearrangements in the literature through the Sorting by Reversals (SbR) problem. SbR is solvable in polynomial time on signed permutations (i.e.

Sorting by Genome Rearrangements on Both Gene Order and Intergenic Sizes.

During the evolutionary process, genomes are affected by various , that is, events that modify large stretches of the genetic material. In the literature, a large number of models have been proposed to estimate the number of events that occurred during evolution; most of them represent a genome as an ordered sequence of genes, and, in particular, disregard the genetic material between consecutive genes. However, recent studies showed that taking into account the genetic material between consecutive genes can enhance evolutionary distance estimations.

Super short operations on both gene order and intergenic sizes.

Background: The evolutionary distance between two genomes can be estimated by computing a minimum length sequence of operations, called , that transform one genome into another. Usually, a genome is modeled as an ordered sequence of genes, and most of the studies in the genome rearrangement literature consist in shaping biological scenarios into mathematical models. For instance, allowing different genome rearrangements operations at the same time, adding constraints to these rearrangements (e.

Heuristics for the Reversal and Transposition Distance Problem.

We present three heuristics-Sliding Window, Look Ahead, and Iterative Sliding Window-to improve solutions for the Sorting Signed Permutations by Reversals and Transpositions Problem. We investigate the classical version of the problem as well as versions restricted to prefix and prefix or suffix operations. To assess the heuristics based on its improvement, we implemented algorithms described in the literature to provide initial solutions.

On the Complexity of Sorting by Reversals and Transpositions Problems.

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Sorting signed circular permutations by super short operations.

Background: One way to estimate the evolutionary distance between two given genomes is to determine the minimum number of large-scale mutations, or , that are necessary to transform one into the other. In this context, genomes can be represented as ordered sequences of genes, each gene being represented by a signed integer. If no gene is repeated, genomes are thus modeled as signed permutations of the form , and in that case we can consider without loss of generality that one of them is the identity permutation , and that we just need to the other (i.

Surveillance of antimicrobial resistance in Neisseria meningitidis strains isolated from invasive cases in Brazil from 2009 to 2016.

Purpose: To describe the antimicrobial resistance profile of Neisseria meningitidis isolates causing invasive disease in Brazil from 2009 to 2016.

Methodology: Among 3548 N. meningitidis isolates received, 2888 (81.

Sorting by weighted inversions considering length and symmetry.

Large-scale mutational events that occur when stretches of DNA sequence move throughout genomes are called genome rearrangements. In bacteria, inversions are one of the most frequently observed rearrangements. In some bacterial families, inversions are biased in favor of symmetry as shown by recent research.

A GRASP-Based Heuristic for the Sorting by Length-Weighted Inversions Problem.

Genome Rearrangements are large-scale mutational events that affect genomes during the evolutionary process. Therefore, these mutations differ from punctual mutations. They can move genes from one place to the other, change the orientation of some genes, or even change the number of chromosomes.

A general heuristic for genome rearrangement problems.

In this paper, we present a general heuristic for several problems in the genome rearrangement field. Our heuristic does not solve any problem directly, it is rather used to improve the solutions provided by any non-optimal algorithm that solve them. Therefore, we have implemented several algorithms described in the literature and several algorithms developed by ourselves.

Heuristics for the transposition distance problem.

Transpositions are large-scale mutational events that occur when a block of genes moves from a region of a chromosome to another region within the same chromosome. The transposition distance problem is the minimum number of transpositions required to transform one genome into another. Recently, Bulteau et al.