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6 Publications


2025 | Published | Journal Article | IST-REx-ID: 20100 | OA | PlanS
Vedula S, Bronstein AM, Marx A. Improving prediction accuracy in chimeric proteins with windowed multiple sequence alignment. Computational and Structural Biotechnology Journal. 2025;27:3292-3298. doi:10.1016/j.csbj.2025.07.039
[Published Version] View | Files available | DOI | WoS
 

2025 | Research Data Reference | IST-REx-ID: 20103 | OA
Vedula S, Bronstein AM, Marx A. Replication Data for: “Improving Prediction Accuracy in Chimeric Proteins with Windowed Multiple Sequence Alignment.” 2025. doi:10.7910/DVN/DYEBVM
[Published Version] View | Files available | DOI | Download Published Version (ext.)
 

2025 | Published | Conference Paper | IST-REx-ID: 20707 | OA
Gahtan B, Vedula S, Samuelly Leichtag G, Kodesh E, Bronstein AM. From lab to wrist: Bridging metabolic monitoring and consumer wearables for heart rate and oxygen consumption modeling. In: Proceedings of the 27th International Conference on Multimodal Interaction. Association for Computing Machinery; 2025:60-77. doi:10.1145/3716553.3750815
[Published Version] View | Files available | DOI | arXiv
 

2025 | Published | Journal Article | IST-REx-ID: 19595 | OA
Davidson Y, Philipp A, Chakraborty S, Bronstein AM, Gershoni-Poranne R. How local is “local”? Deep learning reveals locality of the induced magnetic field of polycyclic aromatic hydrocarbons. Journal of Chemical Physics. 2025;162(14). doi:10.1063/5.0257558
[Published Version] View | Files available | DOI | WoS | PubMed | Europe PMC
 

2025 | Published | Journal Article | IST-REx-ID: 21246 | OA | PlanS
Kamai I, Bronstein AM, Perets HB. Machine Learning inference of stellar properties using integrated photometric and spectroscopic data. The Astrophysical Journal. 2025;994. doi:10.3847/1538-4357/ae0cbc
[Published Version] View | Files available | DOI | arXiv
 

2025 | Published | Conference Paper | IST-REx-ID: 21327 | OA
Maddipatla SA, Sellam NE, Bojan MI, et al. Inverse problems with experiment-guided AlphaFold. In: Proceedings of the 42nd International Conference on Machine Learning. Vol 267. ML Research Press; 2025:42366-42393.
[Published Version] View | Files available | arXiv
 

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