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Guided learning journeys that build knowledge step by step.
category · Learning · slug · learning · 7817 Paths
7817 Paths · page 585 / 782
This learning path explores the relationship between human genetic variation, ancestry estimation, and social constructs of race. It integrates basic population genetics with social science perspectives to critically examine genetic determinism and health disparities.
This learning path equips pre-med students with the knowledge to understand and apply genomic technologies in diagnostic genetic testing. It covers foundational medical genetics, the principles of WES, WGS, and panel testing, and the critical steps of variant interpretation and clinical reporting. The path emphasizes clinical reasoning and the practical application of genomics in patient care.
This advanced graduate-level path guides environmental biology students through the principles and applications of environmental genomics, focusing on metagenomics and environmental DNA (eDNA) for biodiversity assessment and climate change studies. It begins with foundational molecular biology and ecology, progresses through sampling and sequencing technologies, and culminates in bioinformatics analysis and interpretation of environmental genomic data.
This advanced graduate-level path equips public health and microbiology students with the knowledge and skills to apply pathogen genomics in tracking infectious diseases. Learners progress from foundational genomics and public health concepts through sequencing technologies, bioinformatics, and phylogenetic analysis to the practical application of genomic data in outbreak investigations and public health decision-making.
This graduate-level path equips evolutionary anthropology students with the conceptual and practical knowledge to analyze ancient DNA (aDNA) from archaeological remains. It covers the unique challenges of DNA degradation and contamination, the computational workflows for mapping and authenticating ancient genomes, and the population history insights gained from Neanderthal and Denisovan genomes. Learners will integrate basic genomics principles with specialized paleogenomic methods to understand human evolution.
This graduate-level path explores how changes in genomes drive developmental evolution. It begins with core developmental biology and molecular genetics, then focuses on Hox genes, cis-regulatory evolution, and gene regulatory networks, culminating in an understanding of developmental constraints. The path emphasizes the interplay between genetic change and developmental processes in shaping morphological evolution.
This graduate-level path guides synthetic biology students through the principles and practices of designing and building synthetic genomes, from foundational genetics to whole-genome synthesis, including minimal genomes, synthetic yeast, and ethical considerations.
This learning path guides systems biology students through the process of building and analyzing biological networks from genomic data. It covers essential bioinformatics prerequisites, network inference methods for protein-protein interaction (PPI) and gene regulatory networks (GRNs), and topological analysis techniques.
This learning path equips quantitative biology students with the statistical toolkit needed to analyze high-dimensional genomic datasets. It covers essential topics from multiple testing correction and dimensionality reduction to clustering, machine learning, and Bayesian approaches, with a strong foundation in basic statistics and bioinformatics.
This path equips graduate bioinformatics students with the essential command-line and software skills for genomic data analysis. It covers UNIX proficiency, key file formats, quality control, read mapping, and visualization, grounded in basic programming concepts.