Gene Expression

Exploring Genetic Insights and Unlocking Biological Patterns through Data Analysis with R Programming language

Become a bioinformatic analysis master: qPCR, RNAseq, Functional Genomics, Transcriptomics, R, RStudio, TUXEDO pipeline

Learn about Next-generation sequencing and use of Galaxy Server to analyze your datasets for Differential Gene Expresion

Development of high-throughput technologies in molecular biology during the last two decades has contributed to the production of tremendous amounts of data. Microarray and RNA sequencing are two such widely used high-throughput technologies for simultaneously monitoring the expression patterns of thousands of genes. Data produced from such experiments are voluminous (both in dimensionality and numbers of instances) and evolving in nature. Analysis of huge amounts of data toward the identification of interesting patterns that are relevant for a given biological question requires high-performance computational infrastructure as well as efficient machine learning algorithms. Cross-communication of ideas between biologists and computer scientists remains a big challenge.

This book explores the significance, mechanism, function, characteristic, determination, and application of gene expression and phenotypic traits.

This book is intended for scientists, especially those who are interested in the future prospect of gene expression and control in medicine and industry.

The current explosive progress in molecular biological research can be definitively traced to the development of molecular cloning technology.