PyF2F: a robust and simplified fluorophore-to-fluorophore distance measurement tool for Protein interactions from Imaging Complexes after Translocation experiments
2024
Preuzimanje 🢃
Autori
Hernandez, Altair COrtiz, Sebastian
Betancur, Laura I
Dojčilović, Radovan
Picco, Andrea
Kaksonen, Marko
Oliva, Baldo
Gallego, Oriol
Članak u časopisu (Objavljena verzija)
Metapodaci
Prikaz svih podataka o dokumentuApstrakt
Structural knowledge of protein assemblies in their physiological environment is paramount to understand cellular functions at the molecular level. Protein interactions from Imaging Complexes after Translocation (PICT) is a live-cell imaging technique for the structural characterization of macromolecular assemblies in living cells. PICT relies on the measurement of the separation between labelled molecules using fluorescence microscopy and cell engineering. Unfortunately, the required computational tools to extract molecular distances involve a variety of sophisticated software programs that challenge reproducibility and limit their implementation to highly specialized researchers. Here we introduce PyF2F, a Python-based software that provides a workflow for measuring molecular distances from PICT data, with minimal user programming expertise. We used a published dataset to validate PyF2F’s performance.
Izvor:
NAR Genomics and Bioinformatics, 2024, 6, 1Finansiranje / projekti:
- Spanish funding agency [PID2021-127773NB-I00, FEDER/UE, PRE 2019-088514]
- Unidad de Excelencia Maria de Maeztu [CEX2018-000792-M]
- Human Frontiers Science Program [RGP0017/2020]
Kolekcije
Institucija/grupa
VinčaTY - JOUR AU - Hernandez, Altair C AU - Ortiz, Sebastian AU - Betancur, Laura I AU - Dojčilović, Radovan AU - Picco, Andrea AU - Kaksonen, Marko AU - Oliva, Baldo AU - Gallego, Oriol PY - 2024 UR - https://vinar.vin.bg.ac.rs/handle/123456789/13085 AB - Structural knowledge of protein assemblies in their physiological environment is paramount to understand cellular functions at the molecular level. Protein interactions from Imaging Complexes after Translocation (PICT) is a live-cell imaging technique for the structural characterization of macromolecular assemblies in living cells. PICT relies on the measurement of the separation between labelled molecules using fluorescence microscopy and cell engineering. Unfortunately, the required computational tools to extract molecular distances involve a variety of sophisticated software programs that challenge reproducibility and limit their implementation to highly specialized researchers. Here we introduce PyF2F, a Python-based software that provides a workflow for measuring molecular distances from PICT data, with minimal user programming expertise. We used a published dataset to validate PyF2F’s performance. T2 - NAR Genomics and Bioinformatics T1 - PyF2F: a robust and simplified fluorophore-to-fluorophore distance measurement tool for Protein interactions from Imaging Complexes after Translocation experiments VL - 6 IS - 1 DO - 10.1093/nargab/lqae027 ER -
@article{ author = "Hernandez, Altair C and Ortiz, Sebastian and Betancur, Laura I and Dojčilović, Radovan and Picco, Andrea and Kaksonen, Marko and Oliva, Baldo and Gallego, Oriol", year = "2024", abstract = "Structural knowledge of protein assemblies in their physiological environment is paramount to understand cellular functions at the molecular level. Protein interactions from Imaging Complexes after Translocation (PICT) is a live-cell imaging technique for the structural characterization of macromolecular assemblies in living cells. PICT relies on the measurement of the separation between labelled molecules using fluorescence microscopy and cell engineering. Unfortunately, the required computational tools to extract molecular distances involve a variety of sophisticated software programs that challenge reproducibility and limit their implementation to highly specialized researchers. Here we introduce PyF2F, a Python-based software that provides a workflow for measuring molecular distances from PICT data, with minimal user programming expertise. We used a published dataset to validate PyF2F’s performance.", journal = "NAR Genomics and Bioinformatics", title = "PyF2F: a robust and simplified fluorophore-to-fluorophore distance measurement tool for Protein interactions from Imaging Complexes after Translocation experiments", volume = "6", number = "1", doi = "10.1093/nargab/lqae027" }
Hernandez, A. C., Ortiz, S., Betancur, L. I., Dojčilović, R., Picco, A., Kaksonen, M., Oliva, B.,& Gallego, O.. (2024). PyF2F: a robust and simplified fluorophore-to-fluorophore distance measurement tool for Protein interactions from Imaging Complexes after Translocation experiments. in NAR Genomics and Bioinformatics, 6(1). https://doi.org/10.1093/nargab/lqae027
Hernandez AC, Ortiz S, Betancur LI, Dojčilović R, Picco A, Kaksonen M, Oliva B, Gallego O. PyF2F: a robust and simplified fluorophore-to-fluorophore distance measurement tool for Protein interactions from Imaging Complexes after Translocation experiments. in NAR Genomics and Bioinformatics. 2024;6(1). doi:10.1093/nargab/lqae027 .
Hernandez, Altair C, Ortiz, Sebastian, Betancur, Laura I, Dojčilović, Radovan, Picco, Andrea, Kaksonen, Marko, Oliva, Baldo, Gallego, Oriol, "PyF2F: a robust and simplified fluorophore-to-fluorophore distance measurement tool for Protein interactions from Imaging Complexes after Translocation experiments" in NAR Genomics and Bioinformatics, 6, no. 1 (2024), https://doi.org/10.1093/nargab/lqae027 . .