Jeffrey M. Lotthammer
Biochemistry, Genetics and Molecular Biology · The Ohio State University
Publications
50
Citations
797
Est. group size
~5
Recurring co-author estimate
Active years
8
Publishing since 2019
Jeffrey M. Lotthammer works on intrinsically disordered proteins (IDPs) — proteins or protein regions that don't fold into a fixed 3D shape but still carry out biological functions. His work combines computational modeling, machine learning, and biophysics to predict how these flexible protein regions behave, interact with other molecules, and contribute to processes like stress tolerance and cellular organization.
Publication output grew markedly from 2019 through 2023 and has remained high, averaging about 9 papers per year over the last five years.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Accurate predictions of disordered protein ensembles with STARLING
Nature · 2026
- BPS2026 – Probabilistic deep learning enables the data-driven design of disordered proteins
Biophysical Journal · 2026
- BPS2026 – Accurate predictions of conformational ensembles of disordered proteins with STARLING
Biophysical Journal · 2026
- Learning Sequence Constraints Governing Conformational Ensembles and Function in Intrinsically Disordered Proteins
Washington University in St. Louis Libraries · 2026
- Sequence-based prediction of intermolecular interactions driven by disordered regions
Science · 2025
- Disentangling Folding from Energetic Traps in Simulations of Disordered Proteins
Journal of Chemical Information and Modeling · 2025
- Protein surface chemistry encodes an adaptive tolerance to desiccation
Cell Systems · 2025
- Accurate predictions of conformational ensembles of disordered proteins with STARLING
bioRxiv (Cold Spring Harbor Laboratory) · 2025
- Protein Surface Chemistry Encodes an Adaptive Tolerance to Desiccation
SSRN Electronic Journal · 2025
- BPS2025 - A flock of computational methods for investigating disordered protein regions
Biophysical Journal · 2025
- BPS2025 - Construction of IDR ensembles directly from the sequence through multi-scale generative modeling
Biophysical Journal · 2025
- Accurate predictions of conformational ensembles of disordered proteins with STARLING
Research Square · 2025
- Direct prediction of intrinsically disordered protein conformational properties from sequence
Nature Methods · 2024
- Direct prediction of intrinsically disordered protein conformational properties from sequence
Biophysical Journal · 2024
- Direct prediction of intermolecular interactions driven by disordered regions
bioRxiv (Cold Spring Harbor Laboratory) · 2024
- bioRxiv (Cold Spring Harbor Laboratory)×13
- Biophysical Journal×12
- eLife×4
- Research Square×2
- SSRN Electronic Journal×2
- Yuki Kagaya
Biochemistry, Genetics and Molecular Biology · Purdue University West Lafayette
- Aashish Jain
Biochemistry, Genetics and Molecular Biology · Purdue University West Lafayette
- Andrzej Kloczkowski
Biochemistry, Genetics and Molecular Biology · The Ohio State University
- Daisuke Kihara
Biochemistry, Genetics and Molecular Biology · Purdue University West Lafayette
- Charles Christoffer
Biochemistry, Genetics and Molecular Biology · Purdue University West Lafayette
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 19, 2026.
Claim or correct this profile