Applied Bioinformatics and Biostatistics (Live Online)

Required Prerequisites: Successfully completed "Fundamentals of Bioinformatics and Biostatistics" OR "Introduction to Bioinformatics and Statistics"  

Course Description:

The purpose of this applied, project-based data course is to utilize skills from “Fundamentals of Bioinformatics” course and apply them to research-generated data sets analyzing behavioral, physiological, genomic, transcriptomic, and metagenomic data sets. Students will use the data generated from fruit-fly sex-specific neurobiology project focused on behavior, microbial genomics, and head gene expression relative to mating and food restriction – temperature stress scenarios. Besides analyzing and visualizing experimental data, students will participate in statistical design, data inference, and scientific writing. The goal of this course is to help students develop and advance data management and analytical skills and improve formal science communication written and oral skills. Students who successfully participate in the course will have an opportunity to work with our research team and earn an authorship in a peer-reviewed scientific manuscript. Course content, supplemented by relevant bioinformatics and biostatistical concepts and applications, include genomic and biomolecular bioinformatics resources and databases, advances in sequencing technologies, genome and structural informatics, and transcriptomics. Computational tools (using R programming language) and applications promoting best analytical practices will be emphasized. Students will present their research and analysis during the end-of-course formal online / synchronous science symposium. 

By the end of the course, students will be able to: 

• Statistical test a null and alternative hypothesis 
• Understand the experiments with adequate biological, technical replication and statistical power 
• Critically assess primary scientific literature focused on biostatistics and bioinformatics concepts 
• Perform gene finding and sequence alignments, DNA and Protein Database searching 
• Utilize bioinformatics databases, including NCBI / EBI, PDB, UCSC Genome browser, DAVID Bioinformatics, and STRING protein network bioinformatics 
• Visualize experimental data and perform bioinformatic analysis, including principal component analysis (PCA) and hierarchical using R 
• Visualize and interpret high throughput sequencing data 
• Analyze transcriptomics data using a 3’-end shallow_RNASeq 
• Analyze metagenomic data 
• Assist in peer-reviewed manuscript preparation 

Course Topics:  

• Hypothesis testing, experimental design, biological and technical replicates, and statistical power 
• Sequence alignments, gene finding, and differential gene expression analysis. 
• Bioinformatics databases (GenBank, EBI, PDB, UCSC genome browser, David Bioinformatics, STRING…) 
• Data exploration and visualization using R 
• Differential gene expression workflow, data normalization 
• Principal component analysis 
• Hierarchical Clustering and Phylogenetics / Phylogenomic 
• Genome informatics and High Throughput Sequencing 
• Structural bioinformatics 
• Transcriptomics and RNASeq 
• Metagenomics 
  

Quarter Dates, Schedules, and Deadlines