Proceedings of the 2021 on Performance EngineeRing, Modelling, Analysis, and VisualizatiOn STrategy

2021 ◽  
Keyword(s):  
Performance Engineering ◽  
Modelling Analysis ◽  
Visualization Strategy

Editorial: Performance engineering

2003 ◽  
Vol 150 (2) ◽  
pp. 66
Author(s):  
M. Ould-Khaoua ◽  
L.M. Mackenzie
Keyword(s):  
Performance Engineering

Cogeneration and District Energy Systems: Modelling, Analysis and Optimization

2016 ◽  
Author(s):  
Marc A. Rosen Rosen ◽  
Seama Koohi-Fayegh Koohi-Fayegh
Keyword(s):  
Energy Systems ◽  
District Energy ◽  
Modelling Analysis ◽  
Systems Modelling

HCVS: Pinpointing Chromatin States Through Hierarchical Clustering and Visualization Scheme

2019 ◽  
Vol 14 (2) ◽  
pp. 148-156
Author(s):  
Nighat Noureen ◽  
Sahar Fazal ◽  
Muhammad Abdul Qadir ◽  
Muhammad Tanvir Afzal
Keyword(s):  
Hierarchical Clustering ◽  
Real Data ◽  
Cell Types ◽  
Computational Scheme ◽  
Data Set ◽  
Chromatin States ◽  
Functional Regions ◽  
Visualization Strategy ◽  
Hidden States ◽  
Next Generation Sequencing Ngs

Background: Specific combinations of Histone Modifications (HMs) contributing towards histone code hypothesis lead to various biological functions. HMs combinations have been utilized by various studies to divide the genome into different regions. These study regions have been classified as chromatin states. Mostly Hidden Markov Model (HMM) based techniques have been utilized for this purpose. In case of chromatin studies, data from Next Generation Sequencing (NGS) platforms is being used. Chromatin states based on histone modification combinatorics are annotated by mapping them to functional regions of the genome. The number of states being predicted so far by the HMM tools have been justified biologically till now. Objective: The present study aimed at providing a computational scheme to identify the underlying hidden states in the data under consideration. </P><P> Methods: We proposed a computational scheme HCVS based on hierarchical clustering and visualization strategy in order to achieve the objective of study. Results: We tested our proposed scheme on a real data set of nine cell types comprising of nine chromatin marks. The approach successfully identified the state numbers for various possibilities. The results have been compared with one of the existing models as well which showed quite good correlation. Conclusion: The HCVS model not only helps in deciding the optimal state numbers for a particular data but it also justifies the results biologically thereby correlating the computational and biological aspects.

scholarly journals The impact and cost‐effectiveness of community‐basedHIVself‐testing in sub‐Saharan Africa: a health economic and modelling analysis

2019 ◽  
Vol 22 (S1) ◽  
pp. e25243 ◽  
Author(s):  
Valentina Cambiano ◽  
Cheryl C Johnson ◽  
Karin Hatzold ◽  
Fern Terris‐Prestholt ◽  
Hendy Maheswaran ◽  
...  
Keyword(s):  
Health Economic ◽  
Cost Effectiveness ◽  
Sub Saharan Africa ◽  
Modelling Analysis ◽  
Sub Saharan ◽  
The Impact
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