Microbiology

Test how mineral additives change protocell stability in salty early Earth mixes and practice microscopy, image analysis, and controls.

Cluster unknown microbial proteins, predict structures, and test how sequence space can hint at new function classes with bioinformatics.

Build a sequence-based forecasting model that tracks spike protein changes, scores variant fitness, and back-tests predictions with public viral data.

Build a promoter-strength model, then test it against GFP readings from synthetic E. coli promoters and learn how sequence predicts expression.

Compare how different plastics affect biofilm growth and bacterial community shifts with crystal violet staining, 16S sequencing, and strong controls.

Build a lichen-based air-quality index by classifying images, mapping species, and linking community patterns to AirNow pollution data.

Find and classify candidate toxin-antitoxin genes in E. coli genomes with HMMER, synteny, and ColabFold to build bioinformatics skill.

Build a yeast biosensor and compare its colorimetric signal with literature copper values while learning calibration, controls, and data analysis.

Train a CNN on microscope images to predict food spoilage before mold appears, then compare image signals with public 16S microbiome data.

Use docking and validation to test GRAS food additives as growth inhibitors, and learn how to rank hits with real bioinformatics and assay data.