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New methods using rigorous machine learning for coarse-grained protein folding and dynamics

PhD thesis by John M. Jumper
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New methods using rigorous machine learning for coarse-grained protein folding and dynamics

Summary

New methods using rigorous machine learning for coarse-grained protein folding and dynamics is a doctoral thesis[1].

Key Facts

  • New methods using rigorous machine learning for coarse-grained protein folding and dynamics authored John Michael Jumper[2].
  • New methods using rigorous machine learning for coarse-grained protein folding and dynamics's instance of is recorded as doctoral thesis[3].
  • New methods using rigorous machine learning for coarse-grained protein folding and dynamics's page is recorded as 105[4].
  • New methods using rigorous machine learning for coarse-grained protein folding and dynamics's DOI is recorded as 10.6082/M1BZ647N[5].
  • New methods using rigorous machine learning for coarse-grained protein folding and dynamics's language of work or name is recorded as English[6].
  • New methods using rigorous machine learning for coarse-grained protein folding and dynamics's publication date is recorded as +2017-03-00T00:00:00Z[7].
  • New methods using rigorous machine learning for coarse-grained protein folding and dynamics's main subject is recorded as coarse graining[8].
  • New methods using rigorous machine learning for coarse-grained protein folding and dynamics's main subject is recorded as protein[9].
  • New methods using rigorous machine learning for coarse-grained protein folding and dynamics's main subject is recorded as machine learning[10].
  • New methods using rigorous machine learning for coarse-grained protein folding and dynamics's work available at URL is recorded as https://knowledge.uchicago.edu/record/229?v=pdf[11].
  • New methods using rigorous machine learning for coarse-grained protein folding and dynamics's title is recorded as New methods using rigorous machine learning for coarse-grained protein folding and dynamics[12].
  • New methods using rigorous machine learning for coarse-grained protein folding and dynamics's thesis submitted to is recorded as University of Chicago[13].

Body

Designation and Status

New methods using rigorous machine learning for coarse-grained protein folding and dynamics's instance of is recorded as doctoral thesis[3].

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [3] ↑ . wikidata.org.
  2. [2] ↑ . wikidata.org.
  3. [4] ↑ . wikidata.org.
  4. [5] ↑ . wikidata.org.
  5. [6] ↑ . wikidata.org.
  6. [7] ↑ . knowledge.uchicago.edu. Retrieved . knowledge.uchicago.edu. Provenance: wikidata.org.
  7. [8] ↑ . wikidata.org.
  8. [9] ↑ . wikidata.org.
  9. [10] ↑ . wikidata.org.
  10. [11] ↑ . wikidata.org.
  11. [12] ↑ . wikidata.org.
  12. [13] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). New methods using rigorous machine learning for coarse-grained protein folding and dynamics. Retrieved May 3, 2026, from https://4ort.xyz/entity/new-methods-using-rigorous-machine-learning-for-coarse-grained-protein-folding-and-dynamics
MLA “New methods using rigorous machine learning for coarse-grained protein folding and dynamics.” 4ort.xyz Knowledge Graph, 4ort.xyz, 3 May. 2026, https://4ort.xyz/entity/new-methods-using-rigorous-machine-learning-for-coarse-grained-protein-folding-and-dynamics.
BibTeX @misc{4ortxyz_new-methods-using-rigorous-machine-learning-for-coarse-grained-protein-folding-and-dynamics_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{New methods using rigorous machine learning for coarse-grained protein folding and dynamics}}, year = {2026}, url = {https://4ort.xyz/entity/new-methods-using-rigorous-machine-learning-for-coarse-grained-protein-folding-and-dynamics}, note = {Accessed: 2026-05-03}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): New methods using rigorous machine learning for coarse-grained protein folding and dynamics — https://4ort.xyz/entity/new-methods-using-rigorous-machine-learning-for-coarse-grained-protein-folding-and-dynamics (retrieved 2026-05-03)

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