Rhiju Das
Affiliations: | Biochemistry and Physics | Stanford University, Palo Alto, CA |
Area:
predictive understanding of how biopolymer sequences code for biopolymer structures, with an initial focus on RNAWebsite:
http://www.stanford.edu/~rhiju/index.htmlGoogle:
"Rhiju Das"Bio:
http://www.stanford.edu/~rhiju/rhiju_cv.pdf
Cross-listing: Chemistry Tree
Parents
Sign in to add mentorSebastian Doniach | grad student | 2001-2005 | Stanford (Physics Tree) | |
Daniel Herschlag | grad student | 2001-2005 | Department of Biochemistry Stanford University School of Medicine (Chemistry Tree) | |
(Visualizing Forces and Folds of Self-Assembling RNA Molecules) | ||||
David Baker | post-doc | 2005-2008 | University of Washington |
BETA: Related publications
See more...
Publications
You can help our author matching system! If you notice any publications incorrectly attributed to this author, please sign in and mark matches as correct or incorrect. |
Bu F, Adam Y, Adamiak RW, et al. (2024) RNA-Puzzles Round V: blind predictions of 23 RNA structures. Nature Methods |
Mulvaney T, Kretsch RC, Elliott L, et al. (2023) CASP15 cryo-EM protein and RNA targets: Refinement and analysis using experimental maps. Proteins. 91: 1935-1951 |
Das R, Kretsch RC, Simpkin AJ, et al. (2023) Assessment of three-dimensional RNA structure prediction in CASP15. Proteins |
Mulvaney T, Kretsch RC, Elliott L, et al. (2023) CASP15 cryoEM protein and RNA targets: refinement and analysis using experimental maps. Biorxiv : the Preprint Server For Biology |
Kretsch RC, Andersen ES, Bujnicki JM, et al. (2023) RNA target highlights in CASP15: Evaluation of predicted models by structure providers. Proteins |
Kryshtafovych A, Antczak M, Szachniuk M, et al. (2023) New prediction categories in CASP15. Proteins |
Das R, Kretsch RC, Simpkin A, et al. (2023) Assessment of three-dimensional RNA structure prediction in CASP15. Biorxiv : the Preprint Server For Biology |
Watkins AM, Das R. (2023) RNA 3D Modeling with FARFAR2, Online. Methods in Molecular Biology (Clifton, N.J.). 2586: 233-249 |
Wayment-Steele HK, Kladwang W, Watkins AM, et al. (2022) Deep learning models for predicting RNA degradation via dual crowdsourcing. Nature Machine Intelligence. 4: 1174-1184 |
Wayment-Steele HK, Kladwang W, Strom AI, et al. (2022) RNA secondary structure packages evaluated and improved by high-throughput experiments. Nature Methods |