On the entropy of the human transcriptome
February 27, 2018
Via Celoria 26 — Milano
Department of Biosciences
Next-generation sequencing technologies applied to RNAs (known as RNA-Seq) have become the de facto standard in transcriptome investigations, aimed at the characterization and quantification of gene transcription. While on one hand they have opened new avenues of research, on the other have posed several challenges in the bioinformatic and statistical analysis of the data produced. In this talk I will present how measures based on information theory and Shannon's entropy can be defined and employed to shed light on several aspects of modern transcriptomic studies, and in particular how they permit to capture and characterize the complex pattern of variability of human gene expression across multiple conditions and individuals, at different levels of detail (from gene families to a single alternative splicing event).