scholarly journals A new method of representing DNA sequences which combines ease of visual analysis with machine readability

1986 ◽  
Vol 14 (1) ◽  
pp. 509-515 ◽  
Author(s):  
J.E. Cowin ◽  
C.H. Jellis ◽  
D. Rickwood
Keyword(s):  
Dna Sequences ◽  
Visual Analysis ◽  
New Method ◽  
Machine Readability

A new method to analyze the similarity of the DNA sequences

2008 ◽  
Vol 853 (1-3) ◽  
pp. 62-67 ◽  
Author(s):  
Ying Guo ◽  
Tian-ming Wang
Keyword(s):  
Dna Sequences ◽  
New Method

Resolving the multiple sequence alignment problem using biogeography-based optimization with multiple populations

2015 ◽  
Vol 13 (04) ◽  
pp. 1550016 ◽  
Author(s):  
El-Amine Zemali ◽  
Abdelmadjid Boukra
Keyword(s):  
Sequence Alignment ◽  
Dna Sequences ◽  
Multiple Sequence Alignment ◽  
Search Space ◽  
New Method ◽  
Average Score ◽  
Solution Quality ◽  
Multiple Sequence ◽  
Multiple Populations ◽  
Alignment Problem

The multiple sequence alignment (MSA) is one of the most challenging problems in bioinformatics, it involves discovering similarity between a set of protein or DNA sequences. This paper introduces a new method for the MSA problem called biogeography-based optimization with multiple populations (BBOMP). It is based on a recent metaheuristic inspired from the mathematics of biogeography named biogeography-based optimization (BBO). To improve the exploration ability of BBO, we have introduced a new concept allowing better exploration of the search space. It consists of manipulating multiple populations having each one its own parameters. These parameters are used to build up progressive alignments allowing more diversity. At each iteration, the best found solution is injected in each population. Moreover, to improve solution quality, six operators are defined. These operators are selected with a dynamic probability which changes according to the operators efficiency. In order to test proposed approach performance, we have considered a set of datasets from Balibase 2.0 and compared it with many recent algorithms such as GAPAM, MSA-GA, QEAMSA and RBT-GA. The results show that the proposed approach achieves better average score than the previously cited methods.

scholarly journals MYI Floes Identification Based on the Texture and Shape Feature from Dual-Polarized Sentinel-1 Imagery

2020 ◽  
Vol 12 (19) ◽  
pp. 3221
Author(s):  
Shiyi Chen ◽  
Mohammed Shokr ◽  
Xinqing Li ◽  
Yufang Ye ◽  
Zhilun Zhang ◽  
...  
Keyword(s):  
Visual Analysis ◽  
Open Water ◽  
New Method ◽  
The Arctic ◽  
First Year ◽  
Ancillary Data ◽  
Sar Images ◽  
Morphological Image Processing ◽  
Automated Algorithms ◽  
Fine Resolution

The Northwest Passage (NWP) in the Arctic is usually covered with hazardous multi-year ice (MYI) and seasonal first-year ice (FYI) in winter, with possible thin ice and open-water areas during transition seasons. Ice classification is important for both marine navigation and climate change studies. Satellite-based Synthetic Aperture Radar (SAR) systems have shown advantages of retrieving this information. Operational ice mapping relies on visual analysis of SAR images along with ancillary data. However, these maps estimate ice types and concentrations within large-size polygons of a few tens or hundreds of kilometers, which are subjectively identified and selected by analysts. This study aims at developing an automated algorithm to identify individual MYI floes from SAR images then classify the rest of the image as FYI and other ice types. The algorithm identifies the MYI floes using extended-maximum operator, morphological image processing, and a few geometrical features. Classifying the rest of the image uses texture and neural network model. The input data is a set of Sentinel-1 A/B Extended Wide (EW) mode images, acquired between September and March 2016–2019. Although the overall accuracy (for all type classification) from the new method scored 93.26%, the accuracy from using the texture classifier only was 75.81%. The kappa coefficient from the former was higher than the latter by 0.25. Compared with the operational ice charts from the Canadian Ice Service, ice type maps from the new method show better distribution of MYI at the fine scale of individual floes. Comparison against MYI concentration from two automated algorithms that use a combination of coarse-resolution passive and active microwave data also confirms the advantage of resolving MYI floes from the fine-resolution SAR.

scholarly journals NOVO MÉTODO UPLOT-DAP PARA REPRESENTAÇÃO GRÁFICA DE DISTRIBUIÇÕES DIAMÉTRICAS

FLORESTA ◽  
2002 ◽  
Vol 32 (2) ◽  
Author(s):  
Ulisses Silva Da Cunha ◽  
Sebastião Do Amaral Machado ◽  
Afonso Figueiredo Filho ◽  
Roberto Tuyoshi Hosokawa
Keyword(s):  
Visual Analysis ◽  
Constant Width ◽  
Reference Value ◽  
New Method ◽  
Natural Forests ◽  
Class Interval ◽  
Support Tool ◽  
Diameter Structure ◽  
Exploratory Data ◽  
Diameter Classes

Foi apresentado um novo método gráfico denominado de UPLOT-DAP cuja finalidade é auxiliar a preparação de dados para interpretação visual ou análises sobre o comportamento de variáveis por classes diamétricas. A pesquisa objetivou desenvolver uma solução gráfica para a determinação das classes diamétricas. Para desenvolver e testar o método foram utilizados 28320 DAP com casca de árvores procedentes de 15 blocos de 96ha da Floresta Nacional do Tapajós, Belterra, Pará. O UPLOT-DAP é bastante flexível e utiliza-se de técnicas de análise visual de dados como forma de interpretação da dispersão dos diâmetros. Os gráficos foram construídos considerando uma amplitude de classe diamétrica de 10 cm adotada como valor de referência. Foram escolhidos 2 blocos com amplitudes em DAP (cm) representativas da população, bloco 18 [55,225] e bloco 25 [55,195] para discutir os resultados. O principal papel do novo método é evitar a construção equivocada de perfis diamétricos inexistentes ou diferentes da realidade. A eficiência do UPLOT-DAP baseia-se na sua capacidade de controlar a variação dos dados de modo que as análises sejam mais consistentes com os fatores físicos e biológicos que caracterizam a dinâmica de florestas naturais. Através do uso de UPLOT-DAP foi possível também mostrar que a tentativa de se fixar uma amplitude constante ou com variação constante crescente para os dados, pode resultar em conclusões duvidosas sobre a estrutura diamétrica da floresta. NEW METHOD “UPLOT-DAP” FOR GRAPHIC REPRESENTATION OF DIAMETER DISTRIBUTIONS Abstract This research presents a new method of exploratory data analysis for diameter classes in natural tropical forests by using the graph denominated UPLOT-DAP used as support tool in the construction of frequency histograms. The research aimed to develop a new graphic solution, different from the traditional methods, for the determination of the diameter classes. To develop and to test the new graphic method were used 28320 DBH outside bark coming from 15 blocks of 96 hectares of the National Forest of Tapajós, Belterra, Pará, Brazil. The new method is quite flexible and essentially practical consisting in the use of visual analysis techniques of data as a way of diameters dispersion interpretation. The graphs were built considering a diameter class interval of 10 cm adopted as reference value. Two blocks were chosen with DBH (cm) representative range of the population, block 18 [55,225] and block 25 [55,195] to discuss the results. The outcoming of the new method is to avoid the mistakes in constructing inexistent diameter profiles or different from the reality. The efficiency of the new method is based on its capacity to control the variation of the data so that the analysis are more consistent with the physical and biological factors that characterize the dynamics of natural forests. The method also showed that the attempt of establishing a constant width or with a growing constant variation for the data, it can result in biased conclusions on the diameter structure of the forest.

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