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Ray Enke Ph.D.

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Articles 1 - 9 of 9

Full-Text Articles in Life Sciences

Sequence Annotation & Designing Gene-Specific Qpcr Primers (Computational), Ray A. Enke Oct 2016

Sequence Annotation & Designing Gene-Specific Qpcr Primers (Computational), Ray A. Enke

Ray Enke Ph.D.

This class tested protocol will guide students through the steps for the following activities:
  • Obtaining and annotating genomic DNA and mRNA sequence information
  • Designing primers for quantitative PCR (qPCR) analysis of a cDNA library

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Qpcr Primer Standard Curve Assay (Wet Lab) + Kegg Pathway Analysis (Computational), Ray A. Enke Oct 2016

Qpcr Primer Standard Curve Assay (Wet Lab) + Kegg Pathway Analysis (Computational), Ray A. Enke

Ray Enke Ph.D.

This class tested protocol will guide students through the steps for the following activities:
  • analyzing qPCR standard curve data to determine primer efficiency
  • analyzing differential gene expression experimental qPCR data
  • applying KEGG pathway analysis of selected candidates genes

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Qpcr Analysis Of Differential Gene Expression (Wet Lab), Raymond A. Enke May 2016

Qpcr Analysis Of Differential Gene Expression (Wet Lab), Raymond A. Enke

Ray Enke Ph.D.

This class tested protocol will guide students through the steps for the following activities:
  • Analyze qPCR data to determine normalized gene expression for candidate genes identified from an RNA-Seq data set
  • Set up additional or repeat experimental qPCR reactions
  • Create a draft poster outlining the methods & data collected during the 6-week RNA-Seq analysis lab module

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1st Strand Cdna Synthesis From Total Rna (Wet Lab), Raymond A. Enke May 2016

1st Strand Cdna Synthesis From Total Rna (Wet Lab), Raymond A. Enke

Ray Enke Ph.D.

This class tested protocol will guide students through the steps for the following activities:
• Construct a cDNA library representative of total cellular messenger RNAs

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Pathway Analysis Of Differentially Expressed Genes (Computational), Raymond A. Enke May 2016

Pathway Analysis Of Differentially Expressed Genes (Computational), Raymond A. Enke

Ray Enke Ph.D.

This class tested protocol will guide students through the steps for the following activities:
  • Conduct gene ontology (GO) pathway analysis of statistically and biologically significant differentially expressed genes (DEGs)
  • Sort and organize lists of DEGs in MS Excel spreadsheets based on biological function

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Dissection & Rna Isolation From Embryonic Chicken Retina (Wet Lab), Raymond A. Enke May 2016

Dissection & Rna Isolation From Embryonic Chicken Retina (Wet Lab), Raymond A. Enke

Ray Enke Ph.D.

This class tested protocol will guide students through the steps for the following activities:
  • Dissect retina & cornea from developing chicken embryos
  • Extract total cellular RNA from tissues for downstream gene expression analysis

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Rna Gel & Spectrophotometer Analysis (Wet Lab), Raymond A. Enke May 2016

Rna Gel & Spectrophotometer Analysis (Wet Lab), Raymond A. Enke

Ray Enke Ph.D.

This class tested protocol will guide students through the steps for the following activities:
  • Determine quantity & purity of total RNA using a spectrophotometer
  • Determine the quality of total RNA using native agarose gel electrophoresis (no formaldehyde required)

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Analysis Of Rna-Seq Alignments Using Dna Subway Green Line (Computational), Raymond A. Enke May 2016

Analysis Of Rna-Seq Alignments Using Dna Subway Green Line (Computational), Raymond A. Enke

Ray Enke Ph.D.

This class tested protocol will guide students through the steps for the following activities:
  • Review basic steps of RNA-Seq bioinformatics analysis in DNA Subway Green Line
  • View and run basic analytics of RNA-Seq data set in DNA Subway Green Line

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Creating Custom Rna-Seq Data Tracks In The Ucsc Genome Browser (Computational), Raymond A. Enke May 2016

Creating Custom Rna-Seq Data Tracks In The Ucsc Genome Browser (Computational), Raymond A. Enke

Ray Enke Ph.D.

This class tested protocol will guide students through the steps for the following activities:
  • Create your own custom data tracks in the UCSC Genome Browser
  • Visualize RNA-Seq TopHat alignment data as custom tracks in the UCSC Genome Browser
  • Integrate RNA-Seq alignment data with other genome-wide data sets

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