Someonefinisheswithin thetime limitJablonskidiagramCirculardichroismCake“Freakingcool” -JoBikingLigandMPNNChromaNew-to-natureFluorescencepolarizationYang askshow we canmakesomethingmore efficientSomeonegoes overthe timelimitDiscussionof structurepredictionmodelsSomeoneuploadsslides after9:15 AMEquilibriumProteinfoldingImpromptuperformancesDerivatesofCOMBSTechnicaldifficultiesEnergeticpenalty ofLeu to AlaBindingaffinity“Isn’t thatneat” -BillFirstprinciplesHigh-throughputMachinelearningDynamicvs staticParameterizedSomeonefinisheswithin thetime limitJablonskidiagramCirculardichroismCake“Freakingcool” -JoBikingLigandMPNNChromaNew-to-natureFluorescencepolarizationYang askshow we canmakesomethingmore efficientSomeonegoes overthe timelimitDiscussionof structurepredictionmodelsSomeoneuploadsslides after9:15 AMEquilibriumProteinfoldingImpromptuperformancesDerivatesofCOMBSTechnicaldifficultiesEnergeticpenalty ofLeu to AlaBindingaffinity“Isn’t thatneat” -BillFirstprinciplesHigh-throughputMachinelearningDynamicvs staticParameterized

Untitled Bingo - Call List

(Print) Use this randomly generated list as your call list when playing the game. There is no need to say the BINGO column name. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.


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  1. Someone finishes within the time limit
  2. Jablonski diagram
  3. Circular dichroism
  4. Cake
  5. “Freaking cool” -Jo
  6. Biking
  7. LigandMPNN
  8. Chroma
  9. New-to-nature
  10. Fluorescence polarization
  11. Yang asks how we can make something more efficient
  12. Someone goes over the time limit
  13. Discussion of structure prediction models
  14. Someone uploads slides after 9:15 AM
  15. Equilibrium
  16. Protein folding
  17. Impromptu performances
  18. Derivates of COMBS
  19. Technical difficulties
  20. Energetic penalty of Leu to Ala
  21. Binding affinity
  22. “Isn’t that neat” -Bill
  23. First principles
  24. High-throughput
  25. Machine learning
  26. Dynamic vs static
  27. Parameterized