Data för: A Morphology-Based Machine Learning Model for Scoring Epithelial-Mesenchymal Plasticity using Organelle Dynamics Data for: A Morphology-Based Machine Learning Model for Scoring Epithelial-Mesenchymal Plasticity using Organelle Dynamics 2025-306-1 https://doi.org/10.48723/m1cg-v223 Swedish National Data Service Svensk nationell datatjänst Landing page Data för: A Morphology-Based Machine Learning Model for Scoring Epithelial-Mesenchymal Plasticity using Organelle Dynamics Data for: A Morphology-Based Machine Learning Model for Scoring Epithelial-Mesenchymal Plasticity using Organelle Dynamics 2025-306-1 https://doi.org/10.48723/m1cg-v223 oai:swepub.ki.se:1083116 10.21203/rs.3.rs-5859608/v1 Fuxe, Jonas Fuxe, Jonas 21 1739 Pj; 24 3842 Pj 21 1739 Pj; 24 3842 Pj 211092; 231172 211092; 231172 Swedish National Data Service Svensk nationell datatjänst Landing page Organelle Shape Organellform Epithelial-Mesenchymal Transition Epitelial mesenkymövergång Triple Negative Breast Neoplasms Trippelnegativa brösttumörer Cell Plasticity Cellplasticitet Triple-negative breast cancer trippelnegativ bröstcancer Project Description: This project is aimed at modelling dynamic organelle morphology changes in a cellular model of epithelial-mesenchymal transition (EMT). EMT is a developmental process, which is re-activated in cancer and promotes invasion, metastasis and resistance to various therapies. The repository contains raw microscopy images (.nd2 files) and numerical data outputs of all the experiments performed on a variety of cell lines (breast cancer, lung cancer). Cells were stained with the CellPainting kit. Experiments codes are listed below. Categories: Translational and applied bioinformatics; Cellular interactions (incl. adhesion, matrix, cell wall) Numerical Data Source_wet lab + database (782.78 KB) (1 excel file with numerical data source for MS experiments; 1 pdf file with WB uncropped membranes images) Numerical Source Data_all CP experiments (microscopy): (14.47 GB) - CP015/016/018: NMuMG training set (cellprofiler outputs) - CP017: NMuMG reversal experiment - CP019:NMuMG model validation - CP020: breast cancer cells - CP_INT_03_Normoxia: A549 Normoxia - CP_INT_03_Hypoxia: A549 Hypoxia Images (.ND2 files): - CP015_nd2 (37.24 GB): NMuMG training set.1 - CP016_nd2 (37.24 GB): NMuMG training set.2 - CP018_nd2 (37.24 GB): NMuMG training set.3 - CP017_nd2 (37.24 GB): NMuMG reversal experiment - CP019_nd2 (37.24 GB): NMuMG model validation - CP020_nd2 (37.24 GB): breast cancer cells - CP_INT_03_Normoxia_nd2 (18.62 GB): A549 Normoxia - CP_INT_03_Hypoxia_nd2 (18.62 GB): A549 Hypoxia Image files are in nd2 format, which is Nikon's proprietary format, but can be viewed with open source tools such as ImageJ. Project Description: This project is aimed at modelling dynamic organelle morphology changes in a cellular model of epithelial-mesenchymal transition (EMT). EMT is a developmental process, which is re-activated in cancer and promotes invasion, metastasis and resistance to various therapies. The repository contains raw microscopy images (.nd2 files) and numerical data outputs of all the experiments performed on a variety of cell lines (breast cancer, lung cancer). Cells were stained with the CellPainting kit. Experiments codes are listed below. Categories: Translational and applied bioinformatics; Cellular interactions (incl. adhesion, matrix, cell wall) Numerical Data Source_wet lab + database (782.78 KB) (1 excel file with numerical data source for MS experiments; 1 pdf file with WB uncropped membranes images) Numerical Source Data_all CP experiments (microscopy): (14.47 GB) - CP015/016/018: NMuMG training set (cellprofiler outputs) - CP017: NMuMG reversal experiment - CP019:NMuMG model validation - CP020: breast cancer cells - CP_INT_03_Normoxia: A549 Normoxia - CP_INT_03_Hypoxia: A549 Hypoxia Images (.ND2 files): - CP015_nd2 (37.24 GB): NMuMG training set.1 - CP016_nd2 (37.24 GB): NMuMG training set.2 - CP018_nd2 (37.24 GB): NMuMG training set.3 - CP017_nd2 (37.24 GB): NMuMG reversal experiment - CP019_nd2 (37.24 GB): NMuMG model validation - CP020_nd2 (37.24 GB): breast cancer cells - CP_INT_03_Normoxia_nd2 (18.62 GB): A549 Normoxia - CP_INT_03_Hypoxia_nd2 (18.62 GB): A549 Hypoxia Image files are in nd2 format, which is Nikon's proprietary format, but can be viewed with open source tools such as ImageJ. Sweden Sverige CellsCells CellerCeller This study was performed with established cell lines and did not involve human subjects or animals. Denna studie genomfördes med etablerade cellinjer och involverade inte människor eller djur. Numeric Text Still image Time seriesTime series TidsserieTidsserie Access to data through SND. Data are freely accessible. Åtkomst till data via SND. Data är fritt tillgängliga. openAccess Fuxe, J., Slager, J., Gatto, F., Frey, B., Porebski, B., Carreras-Puigvert, J., Parniewska, M., & Shi, W. (2025). A Morphology-Based Machine Learning Model for Scoring Epithelial-Mesenchymal Plasticity using Organelle Dynamics. In Research Square. https://doi.org/10.21203/rs.3.rs-5859608/v1 Fuxe, J., Slager, J., Gatto, F., Frey, B., Porebski, B., Carreras-Puigvert, J., Parniewska, M., & Shi, W. (2025). A Morphology-Based Machine Learning Model for Scoring Epithelial-Mesenchymal Plasticity using Organelle Dynamics. In Research Square. https://doi.org/10.21203/rs.3.rs-5859608/v1 10.21203/rs.3.rs-5859608/v1 oai:swepub.ki.se:1083116 2025 oai:swepub.ki.se:1083116