Mathematical Oncology

New feature: List of datasets for MathOnco research

Written by Guillermo Lorenzo, David Hormuth - March 07, 2023

As MathOnco researchers, we often find ourselves in need of specific data to test a new idea, calibrate our models, or validate our patient-specific predictions and novel cancer mechanisms. In order to facilitate the search for data to bring forth our models and as well as to foster the development of new ideas and collaborations, we are glad to introduce a new feature of the MathOnco website: the MathOnco Datasets.

In this section of the website, we will list online datasets featuring diverse types of data that can be of interest for MathOnco researchers. We do not aim to provide a repository service, but rather to offer a first go-to reference of potential sources of information for your next bold research idea. For each of the datasets, we will provide a brief summary, the main types of data included therein, and a link to the dataset webpage.

Bored this weekend? Another long commute? Have you already scrolled all the way down in your twitter or insta feed? Regardless of your specific case, we invite you to visit the current version of this new feature, and browse the listed datasets, which include imaging (e.g., CT, PET, MRI, US, histopathology, radiotherapy plans), genomic, transcriptomic, proteomic, epigenomic, drug sensitivity, incidence, survival, mortality, prevalence, as well as clinical and demographic data.

Are you as thrilled as we are about this new feature? Wonderful, you can also help us in its future development! Do you know of good databases that are available online? Does your group have a database that would like to announce to the MathOnco community? Does your publication have a link to data that might be of interest to this community? If you responded yes to these questions, feel free to send an email to Guillermo Lorenzo and David Hormuth including a link to the database and they'll make things happen from there with the rest of the MathOnco blog team. Also, let us know if you have any questions or feedback to improve the MathOnco Datasets webpage!

Image Credits

The cover image was created by Alexander Zeilmann using openjourney.
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