An intuitive and user-friendly web application to explore Raman maps
RamApp is a web application that aims to provide a user-friendly solution allowing researchers from various backgrounds to easily and successfully explore hyperspectral data, with a focus on Raman imaging
Import data obtained from different sources, including the most diffused commercial software
RamApp covers the most-used tools and techniques for Raman maps: from cropping and smoothing to spikes detection and baseline correction
Analyse Raman maps using statistical data analysis methods such as clustering, PCA, multivariate curve resolution (MCR) and N-FINDR
Create, as individual or stacked images, intensity maps with a high level of customization
Export publication-quality images or raw data for further analysis
Interactively explore and visualise the data and the results of each processing step with a fast and easy work environment
Once uploaded, your data will be stored in a safe and personal space
Access the app from any browser and operating system without requiring a local installation
RamApp was recently presented at the 12th International Conference on Advanced Vibrational Spectroscopy.
We were thrilled to attend a conference in Dublin to show our most recent app development.
Here are the main people who contributed to the development of RamApp.
We are currently in the process of writing a paper that will detail the development and functionality of our application. In the meanwhile, you can directly cite our website as a reference.
Vernuccio, F., Broggio, E., Sorrentino, S., Bresci, A., Junjuri, R., Ventura, M., Vanna, R., Bocklitz, T., Bregonzio, M., Cerullo, G., Rigneault, H., & Polli, D. (2024). Non-resonant background removal in broadband CARS microscopy using deep-learning algorithms. Scientific Reports, 14(1). 10.1038/s41598-024-74912-5
Junjuri, R., Calvarese, M., Vafaeinezhad, M., Vernuccio, F., Ventura, M., Meyer-Zedler, T., Gavazzoni, B., Polli, D., Vanna, R., Bongarzone, I., Ghislanzoni, S., Negro, M., Popp, J., & Bocklitz, T. (2024). Estimation of biological variance in coherent Raman microscopy data of two cell lines using chemometrics. The Analyst. 10.1039/d4an00648h
Bresci, A., Kobayashi-Kirschvink, K. J., Cerullo, G., Vanna, R., So, P. T. C., Polli, D., & Kang, J. W. (2024). Label-free morpho-molecular phenotyping of living cancer cells by combined Raman spectroscopy and phase tomography. Communications Biology, 7(1). 10.1038/s42003-024-06496-9
Antonacci, G., Vanna, R., Ventura, M., Schiavone, M. L., Sobacchi, C., Behrouzitabar, M., Polli, D., Manzoni, C., & Cerullo, G. (2024). Birefringence-induced phase delay enables Brillouin mechanical imaging in turbid media. Nature Communications, 15(1). 10.1038/s41467-024-49419-2
Vanna, R., Masella, A., Bazzarelli, M., Ronchi, P., Lenferink, A., Tresoldi, C., Morasso, C., Bedoni, M., Cerullo, G., Polli, D., Ciceri, F., De Poli, G., Bregonzio, M., & Otto, C. (2024). High-resolution Raman imaging of >300 cells from human patients affected by nine different leukemia subtypes: a global clustering approach. Analytical Chemistry, 96(23), 9468–9477. 10.1021/acs.analchem.4c00787
Karlo, J., Gupta, A., & Singh, S. P. (2024). In situ monitoring of the Shikimate pathway: A combinatorial approach of Raman reverse stable isotope probing and hyperspectral imaging. The Analyst, 149(10), 2833–2841. 10.1039/d4an00203b
Vernuccio, F., Vanna, R., Ceconello, C., Bresci, A., Manetti, F., Sorrentino, S., Ghislanzoni, S., Lambertucci, F., Motiño, O., Martins, I., Kroemer, G., Bongarzone, I., Cerullo, G., & Polli, D. (2023). Full-Spectrum CARS Microscopy of Cells and Tissues with Ultrashort White-Light Continuum Pulses. The Journal of Physical Chemistry. B, 127(21), 4733–4745. 10.1021/acs.jpcb.3c01443
Ardini, B., Bassi, A., Candeo, A., Genco, A., Trovatello, C., Liu, F., Zhu, X., Valentini, G., Cerullo, G., Vanna, R., & Manzoni, C. (2023). High-throughput multimodal wide-field Fourier-transform Raman microscope. Optica, OPTICA, 10(6), 663. 10.1364/OPTICA.488860
Ghislanzoni, S., Kang, J. W., Bresci, A., Masella, A., Kobayashi-Kirschvink, K. J., Polli, D., Bongarzone, I., & So, P. T. C. (2023). Optical Diffraction Tomography and Raman Confocal Microscopy for the Investigation of Vacuoles Associated with Cancer Senescent Engulfing Cells. Biosensors, 13(11), 973. 10.3390/bios13110973
Don't hesitate to contact us if you have more questions
Start exploring the potential of RamApp now.
