In SVMs (Support vector machines) Data points are log-transformed and normalized as in method A, where for N observations of a gene i, the log transform Xi of the expression level Ei and reference level Ri is?(a) Xi = \(\frac{Log (E_i/R_i)}{\sqrt{\sum_{j=1,N} Log_{z-2} (E_j/R_j)}}\)(b) Xj = \(\frac{Log (E_j/R_i)}{\sqrt{\sum_{j=1,N} Log_z (E_j/R_j)}}\)(c) Xi = \(\frac{Log (E_i/R_i)}{\sqrt{\sum_{j=1,(N-1)} Log_z (E_j/R_j)}}\)(d) Xi = \(\frac{Log (E_i/R_i)}{\sqrt{\sum_{j=1,N} Log_z (E_j/R_j)}}\)This question was addressed to me in an interview for job.The doubt is from Global Gene Regulation in chapter Genome Analysis of Bioinformatics

In SVMs (Support vector machines) Data points are log-transformed and

1.	In SVMs (Support vector machines) Data points are log-transformed and normalized as in method A, where for N observations of a gene i, the log transform Xi of the expression level Ei and reference level Ri is?(a) Xi = \(\frac{Log (E_i/R_i)}{\sqrt{\sum_{j=1,N} Log_{z-2} (E_j/R_j)}}\)(b) Xj = \(\frac{Log (E_j/R_i)}{\sqrt{\sum_{j=1,N} Log_z (E_j/R_j)}}\)(c) Xi = \(\frac{Log (E_i/R_i)}{\sqrt{\sum_{j=1,(N-1)} Log_z (E_j/R_j)}}\)(d) Xi = \(\frac{Log (E_i/R_i)}{\sqrt{\sum_{j=1,N} Log_z (E_j/R_j)}}\)This question was addressed to me in an interview for job.The doubt is from Global Gene Regulation in chapter Genome Analysis of Bioinformatics
Answer» Correct answer is (a) Xi = \(\frac{Log (E_i/R_i)}{\sqrt{\sum_{j=1,N} Log_{z-2} (E_j/R_j)}}\) Explanation: SVMs were used to categorize genes based on 79 different sets of data points from studies of the yeast cell cycle and are PARTICULARLY useful for such complex data sets. Gene combinations averaged over all EXPERIMENTAL CONDITIONS are then EXAMINED by a multidimensional ANALYSIS.

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