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Kamila Riedlová

Showing results (1-10 of 10) with videos related to

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Biochimica Et Biophysica Acta. Biomembranes|January 10, 2022
H1 helix of colicin U causes phospholipid membrane permeationKamila Riedlová, Tereza Dolejšová, Radovan Fišer, et al.
ACS Applied Materials & Interfaces|February 27, 2020
Functionalization of the Parylene C Surface Enhances the Nucleation of Calcium Phosphate: Combined Experimental and Molecular Dynamics Simulations ApproachMonika Golda-Cepa, Kamila Riedlová, Waldemar Kulig, et al.
Nucleic Acids Research|May 19, 2025
PrankWeb 4: a modular web server for protein-ligand binding site prediction and downstream analysisLukáš Polák, Petr Škoda, Kamila Riedlová, et al.
European Journal of Pharmaceutics and Biopharmaceutics : Official Journal of Arbeitsgemeinschaft Fur Pharmazeutische Verfahrenstechnik E.V|March 18, 2023
Influence of BAKs on tear film lipid layer: In vitro and in silico modelsKamila Riedlová, Maria Chiara Saija, Agnieszka Olżyńska, et al.
International Journal of Pharmaceutics|September 4, 2023
Latanoprost incorporates in the tear film lipid layer: An experimental and computational model studyKamila Riedlová, Maria Chiara Saija, Agnieszka Olżyńska, et al.
Chemistry and Physics of Lipids|January 4, 2017
Distributions of therapeutically promising neurosteroids in cellular membranesKamila Riedlová, Michaela Nekardová, Petr Kačer, et al.
Biorxiv : the Preprint Server for Biology|January 16, 2026
Protein Language Models and Structure-Based Machine Learning for Prediction of Allosteric Binding Sites in Protein Kinases: An Explainable AI Framework Grounded in Energy Landscape-Encoded FrustrationKamila Riedlová, Vít Škrhák, Will Gatlin, et al.
Journal of Chemical Theory and Computation|May 7, 2026
Predicting and Decoding Allosteric Binding Sites Using Protein Language Models and Structure-Based Machine Learning: An Energy Landscape-Guided Explainable AI FrameworkKamila Riedlová, Vít Škrhák, William G Gatlin, et al.
Protein Science : a Publication of the Protein Society|July 9, 2026
Decoding the allosteric grammar of protein kinases: A dual-stream framework integrating protein language models and energy landscape frustration analysisWill Gatlin, Max Ludwick, Lucas Turano, et al.
International Journal of Molecular Sciences|May 28, 2022
The Potential Role of SP-G as Surface Tension Regulator in Tear Film: From Molecular Simulations to Experimental ObservationsMartin Schicht, Kamila Riedlová, Mercedes Kukulka, et al.
Pageof 1

Showing results (1-10 of 10) with videos related to

Sort By:
Pageof 1
Biochimica Et Biophysica Acta. Biomembranes|January 10, 2022
H1 helix of colicin U causes phospholipid membrane permeationKamila Riedlová, Tereza Dolejšová, Radovan Fišer, et al.
ACS Applied Materials & Interfaces|February 27, 2020
Functionalization of the Parylene C Surface Enhances the Nucleation of Calcium Phosphate: Combined Experimental and Molecular Dynamics Simulations ApproachMonika Golda-Cepa, Kamila Riedlová, Waldemar Kulig, et al.
Nucleic Acids Research|May 19, 2025
PrankWeb 4: a modular web server for protein-ligand binding site prediction and downstream analysisLukáš Polák, Petr Škoda, Kamila Riedlová, et al.
European Journal of Pharmaceutics and Biopharmaceutics : Official Journal of Arbeitsgemeinschaft Fur Pharmazeutische Verfahrenstechnik E.V|March 18, 2023
Influence of BAKs on tear film lipid layer: In vitro and in silico modelsKamila Riedlová, Maria Chiara Saija, Agnieszka Olżyńska, et al.
International Journal of Pharmaceutics|September 4, 2023
Latanoprost incorporates in the tear film lipid layer: An experimental and computational model studyKamila Riedlová, Maria Chiara Saija, Agnieszka Olżyńska, et al.
Chemistry and Physics of Lipids|January 4, 2017
Distributions of therapeutically promising neurosteroids in cellular membranesKamila Riedlová, Michaela Nekardová, Petr Kačer, et al.
Biorxiv : the Preprint Server for Biology|January 16, 2026
Protein Language Models and Structure-Based Machine Learning for Prediction of Allosteric Binding Sites in Protein Kinases: An Explainable AI Framework Grounded in Energy Landscape-Encoded FrustrationKamila Riedlová, Vít Škrhák, Will Gatlin, et al.
Journal of Chemical Theory and Computation|May 7, 2026
Predicting and Decoding Allosteric Binding Sites Using Protein Language Models and Structure-Based Machine Learning: An Energy Landscape-Guided Explainable AI FrameworkKamila Riedlová, Vít Škrhák, William G Gatlin, et al.
Protein Science : a Publication of the Protein Society|July 9, 2026
Decoding the allosteric grammar of protein kinases: A dual-stream framework integrating protein language models and energy landscape frustration analysisWill Gatlin, Max Ludwick, Lucas Turano, et al.
International Journal of Molecular Sciences|May 28, 2022
The Potential Role of SP-G as Surface Tension Regulator in Tear Film: From Molecular Simulations to Experimental ObservationsMartin Schicht, Kamila Riedlová, Mercedes Kukulka, et al.
Pageof 1