Q. SAGExProfiler doesn’t provide information about overexpressed or silenced genes.

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Q. Which of the following is untrue about SAGE Genie?

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Q. Which of the following is an incorrect statement?

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Q. DNA microarrays measure “absolute” mRNA expression levels without arbitrary reference standards, whereas SAGE indicates the relative expression levels.

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Q. The PCR amplification step involved in the SAGE procedure means that it requires a large quantity of sample mRNA.

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Q. Which of the following is an incorrect statement?

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Q. The classic protein separation methods involve two-dimensional gel electrophoresis followed by gel image analysis.

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Q. Which of the following is incorrect regarding 2D-Page?

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Q. Which of the following is incorrect regarding 2D-Page?

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Q. Comparing two-dimensional gel images from various experiments can sometimes pose a challenge because the gels, unlike DNA microarrays, may shrink or warp.

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Q. Which of the following is incorrect regarding Mass Spectrometry Protein Identification?

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Q. Electrospray ionization MS and matrix-assisted laser desorption ionization (MALDI) MS only differ in the ionization procedure used.

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Q. Which of the following is incorrect regarding the Protein Identification through Database Searching?

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Q. ExPASY is a comprehensive proteomics web server with a suite of programs for searching peptide information from the SWISS-PROT and TrEMBL databases.

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Q. Which of the following is incorrect regarding Mascot and ProFound?

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Q. Which of the following is incorrect regarding Differential In-Gel Electrophoresis?

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Q. Which of the following is a wrong statement?

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Q. Which of the following is a wrong about AutoMotif?

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Q. It is important to use bioinformatics tools to predict sites for posttranslational modifications based on specific protein sequences. However, prediction of such modifications can often be difficult because the short lengths of the sequence motifs associated with certain modifications.

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Q. To minimize false-positive results, a statistical learning process called support vector machine (SVM) can be used to increase the specificity of prediction.

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