455 CARDS · 41 WEEKS · EVERY SOURCE THE PLAN NAMES

Everything you could
study, filtered.

Every video, chapter, paper and repository in the programme, as one card each, with the time it costs and why it is there. Filter by how long you have.

Type Watch Read Run Track Biology AI & stats Build Craft Depth Core Optional Time ≤15 ≤30 ≤60 Week This week Clear all

7/13 Run 30 min? W17 Saturday Sandbox optional

Andrew White, Deep Learning for Molecules and Materials — dmol.pub, chapter on "Deep learning on…

Saturday sandbox · after Notin et al. (2023), "ProteinGym: large-scale benchmarks for protein fitness prediction and desi…

Andrew White, Deep Learning for Molecules and Materials — dmol.pub, chapter on "Deep learning on sequences" (with Colab buttons)

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In: LABLOOP-W17 Notebook

9/13 Run 30 min W17 Build

J-SNACKKB/FLIP

Download the meltome splits; read the README on "mixed", "human" and "human_cell" splits; load them with pandas

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In: LABLOOP-W17 Notebook

10/13 Run 30 min W17 Build

OATML-Markslab/ProteinGym

Browse the leaderboard page and the baselines list; note where ESM-2 sits

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In: LABLOOP-W17 Notebook

11/13 Run 30 min W17 Build

huggingface/notebooks

Reuse protein_language_modeling.ipynb to cache mean-pooled embeddings to disk

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In: LABLOOP-W17 Notebook

12/13 Run 30 min W17 Build

yangkky/Machine-learning-for-proteins

The curated reading list by Kevin Yang; pick 2 papers for PARKING.md, not more

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In: LABLOOP-W17 Notebook

13/13 Run 30 min W17 Build

scikit-learn/scikit-learn

RidgeCV on embeddings → melting temperature; report Spearman correlation with a bootstrap interval

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In: LABLOOP-W17 Notebook