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

4/13 Watch 15 min? W17 Saturday Sandbox optional

Yang, Wu & Arnold (2019), "Machine-learning-guided directed evolution for protein engineering"

Saturday sandbox

Yang, Wu & Arnold (2019), "Machine-learning-guided directed evolution for protein engineering", Nature Methods 16:687-694. The classic review; read it before week 21

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In: LABLOOP-W17 Notebook

5/13 Watch 15 min? W17 Saturday Sandbox optional

Frances Arnold, Nobel Lecture 2018 "Innovation by Evolution: Bringing New Chemistry to Life"

Saturday sandbox · after Yang, Wu & Arnold (2019), "Machine-learning-guided directed evolution for protein engineering"

Frances Arnold, Nobel Lecture 2018 "Innovation by Evolution: Bringing New Chemistry to Life" (nobelprize.org)

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In: LABLOOP-W17 Notebook

6/13 Read 30 min? W17 Saturday Sandbox optional

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

Saturday sandbox · after Frances Arnold, Nobel Lecture 2018 "Innovation by Evolution: Bringing New Chemistry to Life"

Notin et al. (2023), "ProteinGym: large-scale benchmarks for protein fitness prediction and design", NeurIPS Datasets and Benchmarks

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In: LABLOOP-W17 Notebook

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