Concluding Remarks and Research Challenges
Pankaj Barah, Dhruba K. Bhattacharyya, Jugal Kumar Kalita · 2021
This conclusion presents some closing thoughts on the concepts covered in the preceding chapters of this book. The book focuses on gene expression data analysis using three widely used approaches–co-expression analysis, differential co-expression analysis, and differential expression analysis using statistical and machine learning approaches. It discusses high-throughput technologies used in the generation of large-scale gene expression data to provide a good understanding of how such data are generated as well as various issues involved in generating quality data. The book presents pre-processing requirements for both microarray and RNAseq data before such data can be used for analysis. It provides a number of internal and external validity measures, and the sources and repositories connected to the external validity measures. The book introduces a broad array of practical tools, systems and repositories to provide a hands-on experience with gene expression data pre-processing, analysis with clustering-based or network-based approaches, and to validate the outcomes of analysis.