Proteomics Analysis using Python | Functional Annotation & Protein Data | Bioinformatics Ep. 17

Welcome to Lecture 17 of the Bioinformatics Data Analysis using Linux, Python & R series! In this lecture, you’ll explore proteomics analysis using Python — covering how to analyze protein sequences, parse annotation data, and perform functional profiling using public proteomics databases and Python libraries. 🧪 What You’ll Learn: Accessing and parsing protein data from UniProt using Biopython and REST APIs Analyzing protein domains, motifs, and annotations Functional profiling: GO terms, enzymes, Pfam families Introduction to mass spectrometry data parsing (mzML/mzIdentML) Visualizing protein structures and annotations (brief intro to Py3Dmol) Whether you're working on protein function prediction, biomarker discovery, or functional enrichment, this lecture equips you with Python tools to tackle proteomics data confidently. 📂 Scripts & Proteomics Resources: https://bioinfocamp.co 📺 Full series playlist: [Series Playlist Link] 💬 Join our learner discussion: [Discord/FB Group Link] 👍 Like | 💬 Comment your proteomics use-case | 🔔 Subscribe for more hands-on Python bioinformatics tutorials #proteomics #bioinformatics #pythonforbioinformatics #uniprot #proteinsequence #functionalgenomics #massspectrometry #biopython #linuxpythonr #computationalbiology