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6 Publications


2025 | Published | Journal Article | IST-REx-ID: 20100 | OA | PlanS
Vedula, Sanketh, et al. “Improving Prediction Accuracy in Chimeric Proteins with Windowed Multiple Sequence Alignment.” Computational and Structural Biotechnology Journal, vol. 27, Elsevier, 2025, pp. 3292–98, 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, Sanketh, et al. Replication Data for: “Improving Prediction Accuracy in Chimeric Proteins with Windowed Multiple Sequence Alignment.” Harvard Dataverse, 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, Barak, et al. “From Lab to Wrist: Bridging Metabolic Monitoring and Consumer Wearables for Heart Rate and Oxygen Consumption Modeling.” Proceedings of the 27th International Conference on Multimodal Interaction, Association for Computing Machinery, 2025, pp. 60–77, doi:10.1145/3716553.3750815.
[Published Version] View | Files available | DOI | arXiv
 

2025 | Published | Journal Article | IST-REx-ID: 19595 | OA
Davidson, Yair, et al. “How Local Is ‘Local’? Deep Learning Reveals Locality of the Induced Magnetic Field of Polycyclic Aromatic Hydrocarbons.” Journal of Chemical Physics, vol. 162, no. 14, 144101, AIP Publishing, 2025, 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, Ilay, et al. “Machine Learning Inference of Stellar Properties Using Integrated Photometric and Spectroscopic Data.” The Astrophysical Journal, vol. 994, 110, IOP Publishing, 2025, doi:10.3847/1538-4357/ae0cbc.
[Published Version] View | Files available | DOI | arXiv
 

2025 | Published | Conference Paper | IST-REx-ID: 21327 | OA
Maddipatla, Sai A., et al. “Inverse Problems with Experiment-Guided AlphaFold.” Proceedings of the 42nd International Conference on Machine Learning, vol. 267, ML Research Press, 2025, pp. 42366–93.
[Published Version] View | Files available | arXiv
 

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