DISTANCE-BASED PHYLOGENETIC ALGORITHMS: NEW INSIGHTS AND APPLICATIONS

2010 ◽  
Vol 20 (supp01) ◽  
pp. 1511-1532 ◽  
Author(s):  
S. POMPEI ◽  
E. CAGLIOTI ◽  
V. LORETO ◽  
F. TRIA
Keyword(s):  
Horizontal Transfer ◽  
Evolutionary Dynamics ◽  
Phylogenetic Reconstruction ◽  
Local Property ◽  
Reconstruction Algorithms ◽  
Reconstruction Methods ◽  
Tree Length ◽  
Point Condition ◽  
Generative Algorithms ◽  
The One

Phylogenetic methods have recently been rediscovered in several interesting areas among which immunodynamics, epidemiology and many branches of evolutionary dynamics. In many interesting cases the reconstruction of a correct phylogeny is blurred by high mutation rates and/or horizontal transfer events. As a consequence, a divergence arises between the true evolutionary distances and the distances between pairs of taxa as inferred from the available data, making the phylogenetic reconstruction a challenging problem. Mathematically this divergence translates in the non-additivity of the actual distances between taxa and the quest for new algorithms able to efficiently cope with these effects is wide open. In distance-based reconstruction methods, two properties of additive distances were extensively exploited as antagonist criteria to drive phylogeny reconstruction: on the one hand a local property of quartets, i.e. sets of four taxa in a tree, the four-point condition; on the other hand, a recently proposed formula that allows to write the tree length as a function of the distances between taxa, the Pauplin's formula. A deeper comprehension of the effects of the non-additivity on the inspiring principles of the existing reconstruction algorithms is thus of paramount importance. In this paper we present a comparative analysis of the performances of the most important distance-based phylogenetic algorithms. We focus in particular on the dependence of their performances on two main sources of non-additivity: back-mutation processes and horizontal transfer processes. The comparison is carried out in the framework of a set of generative algorithms for phylogenies that incorporate non-additivity in a tunable way.

scholarly journals Morphological phylogenetic analysis with inapplicable data

2017 ◽  
Author(s):  
Martin D. Brazeau ◽  
Thomas Guillerme ◽  
Martin R. Smith
Keyword(s):  
Phylogenetic Analysis ◽  
Missing Data ◽  
Phylogenetic Reconstruction ◽  
Reconstruction Algorithms ◽  
Popular Method ◽  
Single Character ◽  
Tree Length ◽  
Real Phenomenon ◽  
Ancestral States ◽  
Explicit Criteria

AbstractNon-independence of characters is a real phenomenon in phylogenetic data matrices, even though phylogenetic reconstruction algorithms generally assume character independence. In morphological datasets, the problem results in characters that cannot be applied to certain terminal taxa, with this inapplicability treated as “missing data” in a popular method of character coding. However, this treatment is known to create spurious tree length estimates on certain topologies, potentially leading to erroneous results in phylogenetic searches. Here we present a single-character algorithm for ancestral states reconstruction in datasets that have been coded using reductive coding. The algorithm uses up to four traversals on a tree to resolve final ancestral states – which are required in full before a tree can be scored. The algorithm employs explicit criteria for the resolution of ambiguity in applicable/inapplicable dichotomies and the optimization of missing data. We score trees following a previously published procedure that minimizes homoplasy over all characters. Our analysis of published datasets shows that, compared to traditional methods, our new method identifies different trees as “optimal”; as such, correcting for inapplicable data may significantly alter the outcome of tree searches.

scholarly journals Using Avida to Test the Effects of Natural Selection on Phylogenetic Reconstruction Methods

2004 ◽  
Vol 10 (2) ◽  
pp. 157-166 ◽  
Author(s):  
George I. Hagstrom ◽  
Dehua H. Hang ◽  
Charles Ofria ◽  
Eric Torng
Keyword(s):  
Natural Selection ◽  
Phylogenetic Trees ◽  
Sequence Data ◽  
Phylogenetic Reconstruction ◽  
Branch Points ◽  
Reconstruction Algorithms ◽  
Molecular Sequence Data ◽  
Molecular Sequence ◽  
Reconstruction Methods

Phylogenetic trees group organisms by their ancestral relationships. There are a number of distinct algorithms used to reconstruct these trees from molecular sequence data, but different methods sometimes give conflicting results. Since there are few precisely known phylogenies, simulations are typically used to test the quality of reconstruction algorithms. These simulations randomly evolve strings of symbols to produce a tree, and then the algorithms are run with the tree leaves as inputs. Here we use Avida to test two widely used reconstruction methods, which gives us the chance to observe the effect of natural selection on tree reconstruction. We find that if the organisms undergo natural selection between branch points, the methods will be successful even on very large time scales. However, these algorithms often falter when selection is absent.

scholarly journals Phylogenetic Analysis: Basic Concepts and Its Use as a Tool for Virology and Molecular Epidemiology

2018 ◽  
Vol 44 (1) ◽  
pp. 20
Author(s):  
Eloiza Teles Caldart ◽  
Helena Mata ◽  
Cláudio Wageck Canal ◽  
Ana Paula Ravazzolo
Keyword(s):  
Phylogenetic Analysis ◽  
Amino Acid ◽  
Molecular Epidemiology ◽  
Phylogenetic Analyses ◽  
Phylogenetic Reconstruction ◽  
Evolutionary Process ◽  
Amino Acid Sequences ◽  
Evolutionary Models ◽  
Reconstruction Methods ◽  
Basic Concepts

Background: Phylogenetic analyses are an essential part in the exploratory assessment of nucleic acid and amino acid sequences. Particularly in virology, they are able to delineate the evolution and epidemiology of disease etiologic agents and/or the evolutionary path of their hosts. The objective of this review is to help researchers who want to use phylogenetic analyses as a tool in virology and molecular epidemiology studies, presenting the most commonly used methodologies, describing the importance of the different techniques, their peculiar vocabulary and some examples of their use in virology.Review: This article starts presenting basic concepts of molecular epidemiology and molecular evolution, emphasizing their relevance in the context of viral infectious diseases. It presents a session on the vocabulary relevant to the subject, bringing readers to a minimum level of knowledge needed throughout this literature review. Within its main subject, the text explains what a molecular phylogenetic analysis is, starting from a multiple alignment of nucleotide or amino acid sequences. The different software used to perform multiple alignments may apply different algorithms. To build a phylogeny based on amino acid or nucleotide sequences it is necessary to produce a data matrix based on a model for nucleotide or amino acid replacement, also called evolutionary model. There are a number of evolutionary models available, varying in complexity according to the number of parameters (transition, transversion, GC content, nucleotide position in the codon, among others). Some papers presented herein provide techniques that can be used to choose evolutionary models. After the model is chosen, the next step is to opt for a phylogenetic reconstruction method that best fits the available data and the selected model. Here we present the most common reconstruction methods currently used, describing their principles, advantages and disadvantages. Distance methods, for example, are simpler and faster, however, they do not provide reliable estimations when the sequences are highly divergent. The accuracy of the analysis with probabilistic models (neighbour joining, maximum likelihood and bayesian inference) strongly depends on the adherence of the actual data to the chosen development model. Finally, we also explore topology confidence tests, especially the most used one, the bootstrap. To assist the reader, this review presents figures to explain specific situations discussed in the text and numerous examples of previously published scientific articles in virology that demonstrate the importance of the techniques discussed herein, as well as their judicious use.Conclusion: The DNA sequence is not only a record of phylogeny and divergence times, but also keeps signs of how the evolutionary process has shaped its history and also the elapsed time in the evolutionary process of the population. Analyses of genomic sequences by molecular phylogeny have demonstrated a broad spectrum of applications. It is important to note that for the different available data and different purposes of phylogenies, reconstruction methods and evolutionary models should be wisely chosen. This review provides theoretical basis for the choice of evolutionary models and phylogenetic reconstruction methods best suited to each situation. In addition, it presents examples of diverse applications of molecular phylogeny in virology.

scholarly journals Combining Acceleration Techniques for Low-Dose X-Ray Cone Beam Computed Tomography Image Reconstruction

2017 ◽  
Vol 2017 ◽  
pp. 1-10
Author(s):  
Hsuan-Ming Huang ◽  
Ing-Tsung Hsiao
Keyword(s):  
Computed Tomography ◽  
Image Reconstruction ◽  
Low Dose ◽  
Computational Cost ◽  
Reconstruction Algorithm ◽  
Reconstruction Algorithms ◽  
Acceleration Techniques ◽  
Reconstruction Methods ◽  
Speed Up ◽  
Phantom Studies

Background and Objective. Over the past decade, image quality in low-dose computed tomography has been greatly improved by various compressive sensing- (CS-) based reconstruction methods. However, these methods have some disadvantages including high computational cost and slow convergence rate. Many different speed-up techniques for CS-based reconstruction algorithms have been developed. The purpose of this paper is to propose a fast reconstruction framework that combines a CS-based reconstruction algorithm with several speed-up techniques.Methods. First, total difference minimization (TDM) was implemented using the soft-threshold filtering (STF). Second, we combined TDM-STF with the ordered subsets transmission (OSTR) algorithm for accelerating the convergence. To further speed up the convergence of the proposed method, we applied the power factor and the fast iterative shrinkage thresholding algorithm to OSTR and TDM-STF, respectively.Results. Results obtained from simulation and phantom studies showed that many speed-up techniques could be combined to greatly improve the convergence speed of a CS-based reconstruction algorithm. More importantly, the increased computation time (≤10%) was minor as compared to the acceleration provided by the proposed method.Conclusions. In this paper, we have presented a CS-based reconstruction framework that combines several acceleration techniques. Both simulation and phantom studies provide evidence that the proposed method has the potential to satisfy the requirement of fast image reconstruction in practical CT.

scholarly journals Evaluation of Algebraic Iterative Image Reconstruction Methods for Tetrahedron Beam Computed Tomography Systems

2013 ◽  
Vol 2013 ◽  
pp. 1-14
Author(s):  
Joshua Kim ◽  
Huaiqun Guan ◽  
David Gersten ◽  
Tiezhi Zhang
Keyword(s):  
Computed Tomography ◽  
Iterative Reconstruction ◽  
Cone Angle ◽  
Iterative Algorithms ◽  
Projection Data ◽  
Reconstruction Algorithms ◽  
Reconstruction Methods ◽  
Large Cone Angle ◽  
Using Data ◽  
Dual Detector

Tetrahedron beam computed tomography (TBCT) performs volumetric imaging using a stack of fan beams generated by a multiple pixel X-ray source. While the TBCT system was designed to overcome the scatter and detector issues faced by cone beam computed tomography (CBCT), it still suffers the same large cone angle artifacts as CBCT due to the use of approximate reconstruction algorithms. It has been shown that iterative reconstruction algorithms are better able to model irregular system geometries and that algebraic iterative algorithms in particular have been able to reduce cone artifacts appearing at large cone angles. In this paper, the SART algorithm is modified for the use with the different TBCT geometries and is tested using both simulated projection data and data acquired using the TBCT benchtop system. The modified SART reconstruction algorithms were able to mitigate the effects of using data generated at large cone angles and were also able to reconstruct CT images without the introduction of artifacts due to either the longitudinal or transverse truncation in the data sets. Algebraic iterative reconstruction can be especially useful for dual-source dual-detector TBCT, wherein the cone angle is the largest in the center of the field of view.

scholarly journals A Benchmark Dataset and Deep Learning-Based Image Reconstruction for Electrical Capacitance Tomography

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3701 ◽  
Author(s):  
Jin Zheng ◽  
Jinku Li ◽  
Yi Li ◽  
Lihui Peng
Keyword(s):  
Machine Learning ◽  
Image Reconstruction ◽  
Benchmark Dataset ◽  
Electrical Capacitance Tomography ◽  
Electrical Capacitance ◽  
Reconstruction Algorithms ◽  
Reconstruction Methods ◽  
Image Reconstruction Algorithms ◽  
Capacitance Tomography ◽  
The Relationship

Electrical Capacitance Tomography (ECT) image reconstruction has developed for decades and made great achievements, but there is still a need to find a new theoretical framework to make it better and faster. In recent years, machine learning theory has been introduced in the ECT area to solve the image reconstruction problem. However, there is still no public benchmark dataset in the ECT field for the training and testing of machine learning-based image reconstruction algorithms. On the other hand, a public benchmark dataset can provide a standard framework to evaluate and compare the results of different image reconstruction methods. In this paper, a benchmark dataset for ECT image reconstruction is presented. Like the great contribution of ImageNet that transformed machine learning research, this benchmark dataset is hoped to be helpful for society to investigate new image reconstruction algorithms since the relationship between permittivity distribution and capacitance can be better mapped. In addition, different machine learning-based image reconstruction algorithms can be trained and tested by the unified dataset, and the results can be evaluated and compared under the same standard, thus, making the ECT image reconstruction study more open and causing a breakthrough.

scholarly journals Mathematical Modelling to Study the Horizontal Transfer of Antimicrobial Resistance Genes in Bacteria: Current State of the Field and Recommendations

2019 ◽  
Author(s):  
Quentin J. Leclerc ◽  
Jodi A. Lindsay ◽  
Gwenan M. Knight
Keyword(s):  
Public Health ◽  
Antimicrobial Resistance ◽  
Mathematical Modelling ◽  
Resistance Genes ◽  
Horizontal Transfer ◽  
Evolutionary Dynamics ◽  
Research Field ◽  
Contact Transformation ◽  
Current State ◽  
Antimicrobial Resistance Genes

Antimicrobial resistance (AMR) is one of the greatest public health challenges we are currently facing. To develop effective interventions against this, it is essential to understand the processes behind the spread of AMR. These are partly dependent on the dynamics of horizontal transfer of resistance genes between bacteria, which can occur by conjugation (direct contact), transformation (uptake from the environment) or transduction (mediated by bacteriophages). Mathematical modelling is a powerful tool to investigate the dynamics of AMR, however its application to study the horizontal transfer of AMR genes is currently unclear. In this systematic review, we searched for mathematical modelling studies which focused on horizontal transfer of AMR genes. We compared their aims and methods using a list of predetermined criteria, and utilized our results to assess the current state of this research field. Of the 43 studies we identified, most focused on the transfer of single genes by conjugation in Escherichia coli in culture, and its impact on the bacterial evolutionary dynamics. Our findings highlight the existence of an important research gap on the dynamics of transformation and transduction, and the overall public health implications of horizontal transfer of AMR genes. To further develop this field and improve our ability to control AMR, it is essential that we clarify the structural complexity required to study the dynamics of horizontal gene transfer, which will require cooperation between microbiologists and modellers.

An Overview of 3D X-Ray Reconstruction Algorithms for PCB Inspection

2020 ◽  
Author(s):  
Alexandra Roberts ◽  
John True ◽  
Nathan T. Jessurun ◽  
Dr. Navid Asadizanjani
Keyword(s):  
Open Source ◽  
Printed Circuit Boards ◽  
Critical Role ◽  
Reconstruction Algorithms ◽  
X Ray ◽  
Reconstruction Methods ◽  
Verification Methods ◽  
Pcb Manufacturing ◽  
Micro Tomography ◽  
The Government

Abstract Printed Circuit Boards (PCBs) play a critical role in everyday electronic systems, therefore the quality and assurance of the functionality for these systems is a topic of great interest to the government and industry. PCB manufacturing has been largely outsourced to cut manufacturing costs in comparison with the designing and testing of PCBs which still retains a large presence domestically. This offshoring of manufacturing has created a surge in the supply chain vulnerability for potential adversaries to garner access and attack a device via a malicious modification. Current hardware assurance and verification methods are based on electrical and optical tests. These tests are limited in the detection of malicious hardware modifications, otherwise known as Hardware Trojans. For PCB manufacturing there has been an increase in the use of automated X-ray inspection. These inspections can validate a PCB’s functionality during production. Such inspections mitigate process errors in real time but are unable to perform highresolution characterization on multi-layer fully assembled PCBs. In this paper, several X-ray reconstruction methods, ranging from proprietary to open-source, are compared. The high-fidelity, commercial NRecon software for SkyScan 2211 Multi-scale X-ray micro-Tomography system is compared to various methods from the ASTRA Toolbox. The latter is an open-source, transparent approach to reconstruction via analytical and iterative methods. The toolbox is based on C++ and MEX file functions with MATLAB and Python wrappers for analysis of PCB samples. In addition, the differences in required imaging parameters and the resultant artifacts generated by planar PCBs are compared to the imaging of cylindrical biological samples. Finally, recommendations are made for improving the ASTRA Toolbox reconstruction results and guidance is given on the appropriate scenarios for each algorithm in the context of hardware assurance for PCBs.

scholarly journals Surface Reconstruction for Three-Dimensional Rockfall Volumetric Analysis

2019 ◽  
Vol 8 (12) ◽  
pp. 548 ◽  
Author(s):  
David Bonneau ◽  
Paul-Mark DiFrancesco ◽  
D. Jean Hutchinson
Keyword(s):  
Surface Reconstruction ◽  
Laser Scanning ◽  
Volumetric Analysis ◽  
Technical Note ◽  
Surface Topology ◽  
Reconstruction Algorithms ◽  
Hole Filling ◽  
Alpha Shape ◽  
Reconstruction Methods ◽  
Volume Estimates

Laser scanning is routinely being used for the characterization and management of rockfall hazards. A key component of many studies is the ability to use the high-resolution topographic datasets for detailed volume estimates. 2.5-Dimensional (2.5D) approaches exist to estimate the volume of rockfall events; however these approaches require rasterization of the point cloud. These 2.5D volume estimates are therefore sensitive to picking an appropriate cell size to preserve resolution while minimizing interpolation, especially for lower volume rockfall events. To overcome the limitations of working with 2.5D raster datasets, surface reconstruction methods originating from the field of computational geometry can be implemented to assess the volume of rockfalls in 3D. In this technical note, the authors address the methods and implications of how the surface of 3D rockfall objects, derived from sequential terrestrial laser scans (TLS), are reconstructed for volumetric analysis. The Power Crust, Convex Hull and Alpha-shape algorithms are implemented to reconstruct a synthetic rockfall object generated in Houdini, a procedural modeling and animation software package. The reconstruction algorithms are also implemented for a selection of three rockfall cases studies which occurred in the White Canyon, British Columbia, Canada. The authors find that there is a trade-off between accurate surface topology reconstruction and ensuring the mesh is watertight manifold; which is required for accurate volumetric estimates. Power Crust is shown to be the most robust algorithm, however, the iterative Alpha-shape approach introduced in the study is also shown to find a balance between hole-filling and loss of detail.

scholarly journals Birth, School, Work, Death, and Resurrection: The Life Stages and Dynamics of Transposable Element Proliferation

Genes ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 336 ◽  
Author(s):  
Justin P. Blumenstiel
Keyword(s):  
Transposable Elements ◽  
Transposable Element ◽  
Horizontal Transfer ◽  
Evolutionary Dynamics ◽  
Evolutionary Strategies ◽  
Species Boundaries ◽  
Life Stages ◽  
School Work

Transposable elements (TEs) can be maintained in sexually reproducing species even if they are harmful. However, the evolutionary strategies that TEs employ during proliferation can modulate their impact. In this review, I outline the different life stages of a TE lineage, from birth to proliferation to extinction. Through their interactions with the host, TEs can exploit diverse strategies that range from long-term coexistence to recurrent movement across species boundaries by horizontal transfer. TEs can also engage in a poorly understood phenomenon of TE resurrection, where TE lineages can apparently go extinct, only to proliferate again. By determining how this is possible, we may obtain new insights into the evolutionary dynamics of TEs and how they shape the genomes of their hosts.

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