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Yet, dynamically tracking membrane-cortex associated protein or lipid kinetics from live-cell image series remains challenging, primarily due to the difficulty of accurately extracting and aligning the cell boundary between consecutive frames as the cell continuously deforms and moves. Here, we present Membrane Kymograph Generator, a cross-platform software that accepts multichannel time-lapse live-cell fluorescent imaging datasets and automates boundary tracking, inter-frame alignment, and intensity sampling along the boundary. The software implements a rotational offset minimization algorithm that aligns boundaries across consecutive frames by exhaustively searching for the optimal angular shift that minimizes point-to-point distances, while handling variations in boundary point counts due to cell shape changes. The software outputs kymographs representing spatiotemporal dynamics of membrane-associated proteins or biosensors, allows users to fine-tune visualization parameters through an interactive interface, and provides built-in correlation analysis tools for multi-channel datasets. Furthermore, a native Python API enables programmatic usage for batch processing and further downstream analysis. Validation tests demonstrated that the Membrane Kymograph Generator accurately tracks, visualizes, and quantitates the spatial kinetics of a wide array of membrane proteins and lipid biosensors over extended time periods, in a variety of cell types including Dictyostelium amoeba, human neutrophils, mouse macrophages, and mammalian cancer cells. The GUI-based software is user-friendly, requires no technical expertise, and significantly reduces the manual effort required for kymograph generation and analysis while ensuring high accuracy and reproducibility.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and Implementation<\/jats:title>\n                    <jats:p>Membrane Kymograph Generator is free and open-source, licensed under GNU General Public License 3.0 or later. It can be installed on both x86-64 and AArch64\/ARM64 computers running Windows, macOS, or any standard Linux distribution. The software is distributed as standalone installer files and portable executables targeting specific architectures and operating systems, requiring no dependency resolution. The source code, documentation\/wiki, installers, portable binaries, and test data are freely available at https:\/\/github.com\/tatsatb\/membrane-kymograph-generator. The software can also be installed via PIP (package ID: membrane-kymograph, https:\/\/pypi.org\/project\/membrane-kymograph) and accessed programmatically via a built-in Python API. The source code is also archived on Zenodo (DOI: 10.5281\/zenodo.20318834).<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btag400","type":"journal-article","created":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T11:42:56Z","timestamp":1781782976000},"source":"Crossref","is-referenced-by-count":1,"title":["Membrane Kymograph Generator: a cross-platform GUI software for automated generation and analysis of kymographs along dynamic cell boundaries"],"prefix":"10.1093","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3490-3959","authenticated-orcid":false,"given":"Tatsat","family":"Banerjee","sequence":"first","affiliation":[{"name":"Department of Cell Biology and Center for Cell Dynamics, School of Medicine, Johns Hopkins University , Baltimore, MD 21205,","place":["United States"]},{"name":"Department of Chemical and Biomolecular Engineering, Whiting School of Engineering, Johns Hopkins University , Baltimore, MD 21218,","place":["United 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