STATUS: PAST Recording available below
The advent of the -omics age, coupled with the development of robust bioinformatics tools, has granted scientists a window into the molecular and cellular processes which are the root causes of human disease. Simultaneously, large patient datasets have been made publicly available via massive online repositories and are invaluable resources for bioinformatics students.
This STEMCasts® episode will teach students the fundamental skills necessary and inspire a
passion for future explorations in bioinformatics. Due to the extensive nature of the material, the webinar will be 2 hours. We will also host a special Q&A session with renowned expert Dr. Sudeshna Das, Assistant Professor of Neurology at Harvard Medical School.
Ayush Noori is an incoming freshman at Harvard University and student researcher finding solutions for intractable contemporary problems. Dedicated to advancing the fight against neurodegeneration and galvanizing tomorrow’s scientists. Fostering compassion and empathy in the lives of those around him.
Ayush is also the Boston Chapter Founder of EduSTEM, an youth led international organization with a motto of ‘Educate, encourage and empower’.
- Fundamental skills necessary for future explorations in bioinformatics.
- The history of and biology behind the transcriptomics revolution, from microarrays to next generation sequencing to the future of third generation sequencers.
- How to perform introductory bioinformatics analysis on datasets from the Gene Expression Omnibus. (GEO, Home - GEO - NCBI)
- Real-world case studies of using transcriptomics to better patient healthcare.
- Advanced middle school, high school, and college students interested in bioinformatics or data science.
- Students should have previously taken an introductory biology course.
- Introduction and Overview
- Overview of workshop schedule.
- What sparked my own passion for neuroscience and bioinformatics?
- How can students become involved in impactful research, even with limited resource availability?
- What distinct advantages are offered by bioinformatics over wet lab science?
- What are some drawbacks that every bioinformatician must consider before drawing conclusions from their data?
- Biology Background
- All about genes, DNA, and RNA! Overview of transcription and translation.
- How do cells respond to environmental and endogenous stimuli?
- How does the transcriptome govern the function of a cell?
- What are the differences between the transcriptome and the proteome?
- What can we discern about biological function from transcriptomic datasets?
- Studying non-coding RNAs and their influence on cellular function.
- History of the Transcriptomics Revolution
- Overview of RNA extraction, reverse transcriptase, cDNA libraries, and expressed sequence tags (ESTs).
- Sanger sequencing – serial analysis of gene expression (SAGE), cap analysis of gene expression (CAGE), and massively parallel signature sequencing (MPSS).
- The advent of microarray technology via complementary hybridization.
- Spotted oligonucleotide arrays and Affymetrix high-density arrays.
- The rise of RNA-seq technology from 2006-2008.
- Data Analysis of Transcriptomics Data
- Differential expression analysis of microarray data using example datasets from the Gene Expression Omnibus.
- Differences between RNA-seq and microarray analyses.
- Mapping to pathway databases (Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, etc.) and exploring intra-pathway interactions.
- From Transcriptomics to Therapeutics
- How can transcriptomics data help us identify new biomarkers and therapeutic targets for patients?
- Examine real-world case studies of using transcriptomics to better patient healthcare.