CD-MAWS: An Alignment-free Phylogeny Estimation Method Using Cosine Distance on Minimal Absent Word Sets

2021 ◽  
pp. 1-1
Author(s):  
Naser Anjum ◽  
Raian Latif Nabil ◽  
Rakibul Islam Rafi ◽  
Shamsuzzoha Bayzid ◽  
M. Saifur Rahman
Keyword(s):  
Estimation Method ◽  
Alignment Free ◽  
Phylogeny Estimation ◽  
Cosine Distance

scholarly journals SANS serif: alignment-free, whole-genome based phylogenetic reconstruction

2021 ◽  
Author(s):  
Andreas Rempel ◽  
Roland Wittler
Keyword(s):  
Phylogenetic Tree ◽  
Source Code ◽  
Phylogenetic Reconstruction ◽  
Whole Genome ◽  
Link Type ◽  
Alignment Free ◽  
Phylogeny Estimation

AbstractSummarySANS serif is a novel software for alignment-free, whole-genome based phylogeny estimation that follows a pangenomic approach to efficiently calculate a set of splits in a phylogenetic tree or network.Availability and ImplementationImplemented in C++ and supported on Linux, MacOS, and Windows. The source code is freely available for download at https://gitlab.ub.uni-bielefeld.de/gi/[email protected]

scholarly journals An Alignment-free Method for Phylogeny Estimation using Maximum Likelihood

2019 ◽  
Author(s):  
Tasfia Zahin ◽  
Md. Hasin Abrar ◽  
Mizanur Rahman ◽  
Tahrina Tasnim ◽  
Md. Shamsuzzoha Bayzid ◽  
...  
Keyword(s):  
Phylogenetic Analysis ◽  
Computational Complexity ◽  
Maximum Likelihood ◽  
Phylogenetic Tree ◽  
Sequence Alignment ◽  
Multiple Sequence Alignment ◽  
Multiple Sequence ◽  
Alignment Free ◽  
Phylogeny Estimation ◽  
Statistical Approaches

AbstractPhylogenetic analysis i.e. construction of an accurate phylogenetic tree from genomic sequences of a set of species is one of the main challenges in bioinformatics. The popular approaches to this require aligning each pair of sequences to calculate pairwise distances or aligning all the sequences to construct a multiple sequence alignment. The computational complexity and difficulties in getting accurate alignments have led to development of alignment-free methods to estimate phylogenies. However, the alignment free approaches focus on computing distances between species and do not utilize statistical approaches for phylogeny estimation. Herein, we present a simple alignment free method for phylogeny construction based on contiguous sub-sequences of length k termed k-mers. The presence or absence of these k-mers are used to construct a phylogeny using a maximum likelihood approach. The results suggest our method is competitive with other alignment-free approaches, while outperforming them in some cases.

Coaches estimation method for the athletes (CEM)

1995 ◽  
Author(s):  
Nagykaldi Csaba ◽  
Manohar Singh Badhan
Keyword(s):  
Estimation Method

Theoretical, methodological and practical issues of choice models

2018 ◽  
Vol 1 (1) ◽  
pp. 21-37
Author(s):  
Bharat P. Bhatta
Keyword(s):  
Discrete Choice ◽  
Model Building ◽  
Estimation Method ◽  
Choice Models ◽  
Discrete Choice Models ◽  
Decision Makers ◽  
Model Formulation ◽  
Random Utility Maximization ◽  
The Relationship ◽  
Method Model

This paper analyzes and synthesizes the fundamentals of discrete choice models. This paper alsodiscusses the basic concept and theory underlying the econometrics of discrete choice, specific choicemodels, estimation method, model building and tests, and applications of discrete choice models. Thiswork highlights the relationship between economic theory and discrete choice models: how economictheory contributes to choice modeling and vice versa. Keywords: Discrete choice models; Random utility maximization; Decision makers; Utility function;Model formulation

An Absolute Phase Estimation Method for Interferometry Imagery

2019 ◽  
Vol 1 (2) ◽  
pp. 14-19
Author(s):  
Sui Ping Lee ◽  
Yee Kit Chan ◽  
Tien Sze Lim
Keyword(s):  
Noise Suppression ◽  
Estimation Method ◽  
Phase Image ◽  
Phase Estimation ◽  
Phase Reconstruction ◽  
Estimation Algorithms ◽  
Absolute Phase ◽  
Filtering Rate ◽  
Interferometric Phase ◽  
Image Performance

Accurate interpretation of interferometric image requires an extremely challenging task based on actual phase reconstruction for incomplete noise observation. In spite of the establishment of comprehensive solutions, until now, a guaranteed means of solution method is yet to exist. The initially observed interferometric image is formed by 2π-periodic phase image that wrapped within (-π, π]. Such inverse problem is further corrupted by noise distortion and leads to the degradation of interferometric image. In order to overcome this, an effective algorithm that enables noise suppression and absolute phase reconstruction of interferometric phase image is proposed. The proposed method incorporates an improved order statistical filter that is able to adjust or vary on its filtering rate by adapting to phase noise level of relevant interferometric image. Performance of proposed method is evaluated and compared with other existing phase estimation algorithms. The comparison is based on a series of computer simulated and real interferometric data images. The experiment results illustrate the effectiveness and competency of the proposed method.

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