Pratim Chakraborti is a Phd in Biophysics, Molecular Biology and Bioinformatics. He has more than 12 years of experience in industry and academia in translational research and delivering courses respectively.
The Transcriptomics course touches on the bare essentials, that one needs, to understand and analyze the Transcriptome (popularly known as Gene Expression). In addition to basic theories, it provides real data sets to play with and follow the philosophy of “learn by doing”. Spanned across three sections, Transcriptomics 1, Transcriptomics 2 and Transcriptomics 3, it starts from the RNA biology and move to the actual analysis methods with sample data sets – what to look for (patterns), how to look for (data science algorithms), what the patterns mean (biological interpretation) and last but not the least, visualization of the results in accordance to the biological interpretation.
Modern Biology is all about data, which is generated from High Throughput Technologies, and for educators and the students it is absolutely essential to know the methods to handle this data to gain meaningful insights. The Supplementary Resources is an excellent resource within the Course, equipping the participants to delve deeper into the subject. The Quiz Series let you self evaluate as the course progresses, giving a stronger hold over the contents and concepts. It would be unwise, not to mention about the carefully selected Videos embedded within the course. Hence the reading of the text and the interspersed videos make the journey of the course pretty smooth. At the heart of the course there is this pipeline, server.t-bio, where for each algorithm, there is a pop-up that describes the algorithm.
The course, which is meant for both experienced and non-experienced audience, is one of a kind in its entirety, and it springboards the incumbents to become a practitioner in the domain of Biology as a Data Science.