University of California, Los Angeles 4 credits Chemistry and Biochemistry
(Same as Bioinformatics M291.) Lecture, three hours. Practical training in the analysis of largescale biological datasets using Python. Students work with real-world data from single-cell RNA-seq, spatial transcriptomics, phospho-proteomics, and high-content imaging studies. Emphasis on hands-on coding, statistical and machine learning modeling, and clear data interpretation and visualization. A key component is the responsible use of artificial intelligence coding assistants. Students learn how to use tools like ChatGPT and Copilot to scaffold code, debug, and accelerate their analysis, while ensuring transparency and reproducibility. S/U or letter grading.
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