Unsupervised Detection of Outliers in In-vitro Cellular Gene Expression Data
The poster was exhibited within the Fall School in Mathematical Biology (Escuela de Otoño en Biología Matemática, EOBM) 2019 that was assigned to Mérida, Yucatán.
The poster shows the results of the application of different methods to detect outliers in a set of vitamin D genes.
The dataset only had 3 attributes, which were:
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Retention intensity of the Vitamin D Receptor (VDR) at 8 hours.
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Retention intensity of the Vitamin D Receptor (VDR) at 24 hours.
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Histone count.
The results were interesting, the algorithms for the outlier detection showed genes that presented an abnormal VDR clamping intensity at 8 hours and, later, at 24 hours, they normalized.