Project Details
| Status | Finished |
|---|---|
| Effective start/end date | 1/04/19 → 31/03/24 |
Funding
- BBSRC (BIOTECHNOLOGY AND BIOLOGICAL SCIENCES RESEARCH COUNCIL): £373,868.00
-
Cryo-EM model validation recommendations based on outcomes of the 2019 EMDataResource challenge
Lawson, C. L., Kryshtafovych, A., Adams, P. D., Afonine, P. V., Baker, M. L., Barad, B. A., Bond, P., Burnley, T., Cao, R., Cheng, J., Chojnowski, G., Cowtan, K., Dill, K. A., DiMaio, F., Farrell, D. P., Fraser, J. S., Herzik, M. A., Hoh, S. W., Hou, J. & Hung, L. W. & 34 others, , 4 Feb 2021, In: Nature Methods. 18, 2, p. 156-164 9 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile -
Predicting the performance of automated crystallographic model-building pipelines
Alharbi, E., Bond, P., Calinescu, R. & Cowtan, K., 1 Dec 2021, In: Acta crystallographica. Section D, Structural biology. 77, Pt 12, p. 1591-1601 11 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile -
'Sheetbend' software for model morphing of atomic models. version 0.5
Cowtan, K. D., 18 Apr 2021Research output: Non-textual form › Software
-
Macromolecular refinement using shift field optimization and regularization
Cowtan, K. D. (Invited speaker)
6 Jan 2022Activity: Talk or presentation › Invited talk
-
Picture a programmer
Cowtan, K. D. (Keynote/plenary speaker)
5 Jan 2022Activity: Talk or presentation › Invited talk
-
Collaborative Computational Project No. 4 Software for Macromolecular X-Ray Crystallography (External organisation)
Cowtan, K. D. (Member)
1 Jan 2022 → 31 Dec 2022Activity: Membership › Board
Datasets
-
Shift field refinement of macromolecular atomic models
Cowtan, K. D. (Creator), University of York, 28 Sept 2020
DOI: 10.15124/5d8e7307-7bde-4e47-875d-5f15f30177bd
Dataset
-
Predicting Protein Model Correctness in COOT Using Machine Learning
Cowtan, K. D. (Supervisor) & Bond, P. (Creator), University of York, 2020
DOI: 10.15124/44145f0a-5d82-4604-9494-7cf71190bd82, https://webfiles.york.ac.uk/INFODATA/44145f0a-5d82-4604-9494-7cf71190bd82 and one more link, https://creativecommons.org/licenses/by/4.0/ (show fewer)
Dataset
-
Predicting the performance of automated crystallographic model-building pipelines
Alharbi, E. (Creator), Bond, P. (Contributor), Calinescu, R. (Contributor) & Cowtan, K. D. (Contributor), University of York, 20 Oct 2021
DOI: 10.15124/ee9d169f-c34b-44f2-8c75-3b68e7cd68a8
Dataset