ASGHARZADEH, Pouyan, BIRKHOLD, Annette Isabell, TRIVERDI, Zubin, ÖZDEMIR, Bugra, RESKI, Ralf und RÖHRLE, Oliver, 2020. A Nano FE simulation-based surrogate machine learning model to predict mechanical functionality of protein networks from live confocal imaging. Freiburg: Universität.
Elsevier - Harvard (with titles)Asgharzadeh, P., Birkhold, A.I., Triverdi, Z., Özdemir, B., Reski, R., Röhrle, O., 2020. A Nano FE simulation-based surrogate machine learning model to predict mechanical functionality of protein networks from live confocal imaging. Universität, Freiburg. https://doi.org/10.1016/j.csbj.2020.09.024
American Psychological Association 7th editionAsgharzadeh, P., Birkhold, A. I., Triverdi, Z., Özdemir, B., Reski, R., & Röhrle, O. (ca. 2020). A Nano FE simulation-based surrogate machine learning model to predict mechanical functionality of protein networks from live confocal imaging [Cd]. Universität. https://doi.org/10.1016/j.csbj.2020.09.024
Springer - Basic (author-date)Asgharzadeh P, Birkhold AI, Triverdi Z, Özdemir B, Reski R, Röhrle O (2020) A Nano FE simulation-based surrogate machine learning model to predict mechanical functionality of protein networks from live confocal imaging. Universität, Freiburg
Juristische Zitierweise (Stüber) (Deutsch)Asgharzadeh, Pouyan/ Birkhold, Annette Isabell/ Triverdi, Zubin/ Özdemir, Bugra/ Reski, Ralf/ Röhrle, Oliver, A Nano FE simulation-based surrogate machine learning model to predict mechanical functionality of protein networks from live confocal imaging, Freiburg 2020.