Author

T. Head-Gordon

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· 3

Signature Assays, Organisms & Methods

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Research Focus:protein folding & dynamics· 2 Assay:protein structure· 2 Approach:deep learning· 1 Approach:experimental assay· 1 Approach:machine learning (classical)· 1 Research Focus:protein structure prediction· 1 Approach:statistical model· 1

Frequent Co-Authors

A. Namini· 2 shared J. D. Forman-Kay· 2 shared J. Li· 2 shared J. M. C. Teixeira· 2 shared M. Krzeminski· 2 shared O. Zhang· 2 shared Z. H. Liu· 2 shared A. A. Shamandy· 1 shared

Activity by Year

2020-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 35 mutual co-author links

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2 shared papersBiophysics

A. Namini

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Author profile →

3 papers

Recent·Most cited

Local Disordered Region Sampling (LDRS) for Ensemble Modeling of Proteins with Experimentally Undetermined or Low Confidence Prediction Segments

Z. H. Liu, J. M. C. Teixeira, O. Zhang, T. E. Tsangaris, J. Li, C. C. Gradinaru, T. Head-Gordon, J. D. Forman-Kay

The paper introduces LDRS, a tool for generating conformational ensembles of intrinsically disordered regions in proteins, improving structural modeling of flexible segments.

bioRxiv · Jul 25, 2023Biophysics

IDPConformerGenerator: A Flexible Software Suite for Sampling Conformational Space of Disordered Protein States

J. M. C. Teixeira, Z. H. Liu, A. Namini, J. Li, R. M. Vernon, M. Krzeminski, A. A. Shamandy, O. Zhang, M. Haghighatlari, L. Yu, T. Head-Gordon, J. D. Forman-Kay

IDPConformerGenerator generates diverse ensembles of disordered protein states using physical restraints and machine learning, enabling structural analysis of intrinsically disordered proteins.

bioRxiv · May 28, 2022Biophysics

Integrating multiple experimental data to determine conformational ensembles of an intrinsically disordered protein

G.-N. W. Gomes, M. Krzeminski, A. Namini, E. Martin, T. Mittag, T. Head-Gordon, J. Forman-Kay, C. Gradinaru

The paper integrates NMR, SAXS, and smFRET data to determine the conformational ensembles of Sic1 and pSic1, showing consistency across methods and validating their structural models.

bioRxiv · Feb 5, 2020 · PreprintBiophysics