Transcriptomics 1

What is the transcriptome and why study it?

Molecular biology is a vast and eclectic field, composed of many branches and subdisciplines. Molecular biologists study a broad spectrum of topics relating to the molecular regulation of cell biology, from DNA and RNA, to protein expression and protein-protein interactions. A dominant theme in molecular biology is how variation in nucleic acids (genotype) affects the biology of organisms (phenotype). The 2 main types of nucleic acid variation are:

• gene variation at the level of DNA (genomics)
• variation in gene expression (transcriptomics)

Major Trends and Applications

Next Generation Sequencing (NGS) and machine learning are key technologies enabling an unprecedented level of power, precision, and efficacy in understanding genomic regulation. Digital information that can represent biology in such detail requires appropriate computational and storage resources. In a digital file representing sequenced DNA or RNA, nucleotides are represented by letters corresponding to their bases. These letters are stored in text files that a computer can process as a series of strings.

Course objectives and methodology

The goal of this course is to open the world of big-data analysis to biologists and clinicians who currently lack the ability to work with this large scale of data. Realizing that the backgrounds of people interested in this course will be diverse, we want to provide sufficient background for the hands-on exercises that are included in these course. For the exercises, we will be using the T-BioInfo platform that hides the complexity of code and algorithms behind an intuitive visual interface. Part of the course will be dedicated to a detailed description of the analysis steps that are combined into pipelines on the platform. As a result, participants will gain independence and will be able to analyze their own data.

Our courses are designed to be accessible to diverse audiences, so we are limiting the number of technical concepts that some might find useful. Additional technical terminology and expanded review can be found on other websites that we will provide links to for additional reading.

We would like to thank the following people who helped to prepare the projects, develop the tools, and compile the the learning resources for this course:

Dr. Leonid Brodsky and the Tauber Bioinformatics Research Center, Dr. Claudia Copeland, Dr. Ron Ferrucci, Julia Panov, Jaclyn Williams