Author

G. Terashi

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Biophysics· 2 Biochemistry· 1

Signature Assays, Organisms & Methods

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Assay:cryo-EM· 3 Approach:deep learning· 2 Research Focus:protein structure prediction· 2 Approach:benchmark study· 1 Research Focus:benchmarking· 1 Approach:mechanistic / dynamical model· 1

Frequent Co-Authors

D. Kihara· 3 shared A. Perez· 2 shared A. Singharoy· 2 shared D. Sarkar· 2 shared M. Shekhar· 2 shared A. Kryshtafovych· 1 shared A. Mondal· 1 shared A. P. Joseph· 1 shared

Activity by Year

2020-2020 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 41 mutual co-author links

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3 shared papersBiophysics

D. Kihara

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Author profile →

3 papers

Recent·Most cited

Emap2sec+: Detecting Protein and DNA/RNA Structures in Cryo-EM Maps of Intermediate Resolution Using Deep Learning

X. Wang, E. Alnabati, T. W. Aderinwale, S. R. Maddhuri Venkata Subramaniya, G. Terashi, D. Kihara

Emap2sec+ uses deep learning to detect DNA/RNA and protein secondary structures in intermediate-resolution cryo-EM maps, showing improved accuracy over its previous version.

bioRxiv · Aug 22, 2020 · PreprintBiophysics

CryoFold: Ab-initio structure determination from electron density maps using molecular dynamics

M. Shekhar, G. Terashi, C. Gupta, D. Sarkar, G. Debussche, N. Sisco, J. Nguyen, A. Mondal, J. Zook, J. Vant, P. Fromme, W. D. van Horn, D. Kihara, E. Tajkhorshid, K. Dill, , A. Singharoy

CryoFold determines protein structures from electron density maps using molecular dynamics and physical knowledge, producing ensembles of low-energy conformations validated experimentally.

bioRxiv · Aug 3, 2020 · PreprintBiophysics

Outcomes of the 2019 EMDataResource model challenge: validation of cryo-EM models at near-atomic resolution

C. L. Lawson, A. Kryshtafovych, P. D. Adams, P. Afonine, M. L. Baker, B. A. Barad, P. Bond, T. Burnley, R. Cao, J. Cheng, G. Chojnowski, K. Cowtan, K. A. Dill, F. DiMaio, D. Farrell, , Wan

The paper evaluates cryo-EM model quality using benchmark maps, showing high accuracy and reproducibility across 13 teams and recommending multiple metrics for model assessment.

bioRxiv · Jun 12, 2020Biochemistry