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DC Field | Value | Language |
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dc.contributor.author | Jain, Jain | - |
dc.contributor.author | Chauhan, D S | - |
dc.date.accessioned | 2022-12-15T06:08:09Z | - |
dc.date.available | 2022-12-15T06:08:09Z | - |
dc.date.issued | 2018 | - |
dc.identifier.uri | http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/8616 | - |
dc.description.abstract | Multicellular organisms have three subfamilies of mitogen-activated protein kinases (MAPKs) that control a vast array of physiological processes. This paper stresses on stress activation protein kinase (SAPK/JNK) which are activated when cells are exposed to heat shock or UV radiation. SAPK protein is activated by different cycles of TNF, EGF and insulin proteins. The computational analysis using adjustment Anderson darling statistics (AD) and Pearson correlation coefficient (PCC) for different distribution functions. For good results AD value should be lower which was obtained for 100 ng/ml of TNF, 0 ng/ml of EGF and 0 ng/ml of insulin concentration for every distribution function. The PCC value should be higher which was obtained for 5 ng/ml of TNF, 1 ng/ml of EGF and 0 ng/ml of insulin concentration for herd Johnson method. The best value of PCC is 0.995. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Jaypee University of Information Technology, Solan, H.P. | en_US |
dc.subject | SAPK | en_US |
dc.subject | Parametric | en_US |
dc.subject | Non-parametric | en_US |
dc.subject | Anderson darling | en_US |
dc.subject | Pearson correlation coefficient | en_US |
dc.title | Computational Model Using Anderson Darling Statistics and Pearson Correlation Coefficients of Different Distribution Functions for Stress Activation Protein Kinase | en_US |
dc.type | Article | en_US |
Appears in Collections: | Journal Articles |
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