Time-course data prediction for repeatedly measured gene expression-Reference-Cited by-同舟云学术

Time-course data prediction for repeatedly measured gene expression

Published:2019-05 Issue:04 Volume:12 Page:1950033
ISSN:1793-5245
Container-title:International Journal of Biomathematics
language:en
Short-container-title:Int. J. Biomath.

Author:

Bhattacharjee Atanu¹^ORCID,Vishwakarma Gajendra K.²

Affiliation:

1. Section of Biostatistics, Centre for Cancer Epidemiology, Tata Memorial Centre, Navi Mumbai 410210, India

2. Department of Applied Mathematics, Indian Institute of Technology (ISM), Dhanbad-826004, India

Abstract

Variability in time course gene expression data is a natural phenomenon. The intention of this work is to predict the future time point data through observed sample data point. The Bayesian inference is carried to serve the objective. A total of 6 replicates 3 time point’s data of 218 genes expression is adopted to illustrate the method. The estimates are found consistent with HPD interval to predict the future time point gene expression value. This proposed method can be adopted in other gene expression data setup to predict the future time course data.

Funder

Science and Engineering Research Board, Department of Science & Technology, Government of India

Publisher

World Scientific Pub Co Pte Lt

Subject

Applied Mathematics,Modeling and Simulation

Link

https://www.worldscientific.com/doi/pdf/10.1142/S1793524519500335

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