@article{Shittu_2023, title={Microarray Gene Expression Data Generation and Pre-Processing of Moringa Oleifera Leaves for the Improvement of Medicinal Use}, volume={9}, url={https://jbarbiomed.com/index.php/home/article/view/221}, DOI={10.51152/jbarbiomed.v9i1.221}, abstractNote={<p><em>Moringa oleifera</em> is a plant species belonging to the family name called Moringaceae widely cultivated for human use. This study aimed to generate microarray gene expression data from the leaves of the Moringa oleifera plant and explore the usage of some tools available in the Bioconductor R package for the quality control. Six (6) young <em>Moringa Oleifera</em> leaves (YMOL) samples and six (6) old Moringa oleifera leaves (OMOL) samples were collected from the plant and processed for microarray data generation. Microarray gene expression raw data from the   leaves of the Moringa oleifera plants were generated, each in a CEL file format and the usage of some tools available in R programming Bioconductor open source and development software project were explored for the quality control of the data. Affycoretools were installed in the R environment for pre-processing of microarray raw data. AffyQCReport tools were used to generate a comprehensive quality control (QC) report for the microarray unnormalized raw data in PDF format. It is recommended that Gene chip robust multiarray analysis (GCRMA) method can be used for visual inspection, background correction, normalization and summarization of this microarray raw data.  The normalized microarray raw data can be used through the genetic engineering to improve the Moringa oleifera plant medicinal values in order to solve some medical problems especially with patients suffering from diabetes and hypertension and also can be of enormous importance in the fields of pharmacy and medicine at large.</p>}, number={1}, journal={Journal of Basic and Applied Research in Biomedicine}, author={Shittu, Umar}, year={2023}, month={Apr.}, pages={1–4} }