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Bioinformatics: Essentially the application of the information theory to biology to deal with the deluge of the information resulting from the advances in molecular biology. The major tasks in this ?eld is the creation and maintenance of the databases of biological information, specifically nucleic acid sequences, ?nding genes in the DNA sequences of the various organisms and clustering protein sequences into families of the related sequences.
Prepare a 1,400- to 1,750-word paper in which you formulate a hypothesis based on your selected research issue, problem, or opportunity. Address the following: •Describe your sele
Asymmetric proximity matrices : Proximity matrices in which the non-diagonal elements, in the ith row and jth column and the jth row and ith column, are not essentially equal. Exam
Lagrange Multiplier (LM) test The Null Hypothesis - H0: There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1: There is heteroscedasticity i.e. β 1
Bioassay : It is an abbreviation of biological assay, which in its classical form includes an experiment conducted on biological material to determine relative potency of test and
Zero-inflated Poisson regression is the model for count data with the excess zeros. It supposes that with probability p the only possible observation is 0 and with the probabilit
MAREG is the software package for the analysis of the marginal regression models. The package permits the application of generalized estimating equations and the maximum likelihoo
Lagging indicators: The part of a collection of the economic time series designed to give information about the broad swings in measures of the aggregate economic activity known a
The Null Hypothesis - H0: β 1 = 0 i.e. there is homoscedasticity errors and no heteroscedasticity exists The Alternative Hypothesis - H1: β 1 ≠ 0 i.e. there is no homoscedasti
This is an attempt to measure the suffering caused by the illness which takes into the account both the years of the potential life lost due to the premature mortality as well as t
This is the theorem which states that if the error terms in a multiple regression have the same variance and are not corrected, then the estimators of the parameters in the model p
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