This course is tailored for graduate students with a basic understanding of genomics who aim to deepen their expertise in advanced concepts and applications in the field. The curriculum covers a wide range of topics including the mapping and sequencing of genomes, the latest computational and experimental techniques for identifying genomic variants, and the study of epigenetic modifications such as DNA methylation and chromatin accessibility. Students will also delve into methods for inferring transcription factor binding sites and motifs. High-throughput techniques for ascribing function to DNA, RNA, and protein sequences, including single-cell RNA sequencing, whole-genome sequencing, massively parallel reporter assays, chromosome conformation capture (Hi-C) analysis, metagenomics, and proteogenomic, will also be discussed. Finally, the use of genomic techniques and resources for studies of human disease will be addressed. A significant focus will be placed on equipping students with the essential bioinformatics skills required to navigate and utilize databases that store sequence data, expression data, and other types of genome-wide information. Through practical problem sets, students will learn to manipulate and analyze large datasets typical of genomic analyses by developing simple computer scripts. While the course will enable students to become proficient in the use of computational tools and databases, specific programming skills and the theoretical underpinnings of these tools are covered in a separate course, "Bio 5495 Computational Molecular Biology," taught by Michael Brent. Due to space limitations in our teaching lab, enrollment for lab credit is capped at 30 students, with priority given to those enrolled in the DBBS programs. Other students may enroll in the lecture component only, with the instructor's permission. Those with prior experience in computer programming are advised not to enroll for lab credit. Prereqs, Molecular Cell Biology (Bio 5068),
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