SVEM: A Structural Variant Estimation Method Using Multi-mapped Reads on Breakpoints

2014 ◽  
pp. 208-219
Author(s):  
Tomohiko Ohtsuki ◽  
Naoki Nariai ◽  
Kaname Kojima ◽  
Takahiro Mimori ◽  
Yukuto Sato ◽  
...  
Keyword(s):  
Estimation Method ◽  
Structural Variant

Coaches estimation method for the athletes (CEM)

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

Diversity of Glycoprotein Deficiencies in Glanzmann’s Thrombasthenia

1985 ◽  
Vol 54 (03) ◽  
pp. 626-629 ◽  
Author(s):  
M Meyer ◽  
F H Herrmann
Keyword(s):  
High Resolution ◽  
Gel Electrophoresis ◽  
Type Ii ◽  
Two Dimensional ◽  
Two Dimensional Gel Electrophoresis ◽  
Structural Variant ◽  
Glanzmann’S Thrombasthenia ◽  
Crossed Immunoelectrophoresis ◽  
Glanzmann's Thrombasthenia ◽  
Platelet Proteins

SummaryThe platelet proteins of 9 thrombasthenic patients from 7 families were analysed by high resolution two-dimensional gel electrophoresis (HR-2DE) and crossed immunoelectrophoresis (CIE). In 7 patients both glycoproteins (GPs) IIb and Ilia were absent or reduced to roughly the same extent. In two related patients only a trace of GP Ilb-IIIa complex was detected in CIE, but HR-2DE revealed a glycopeptide in the position of GP Ilia in an amount comparable to type II thrombasthenia. This GP Ilia-like component was neither recognized normally by anti-GP Ilb-IIIa antibodies nor labeled by surface iodination. In unreduced-reduced two-dimensional gel electrophoresis two components were observed in the region of GP Ilia. The assumption of a structural variant of GP Ilia in the two related patients is discussed.

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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