JOIN US IN SHAPING THE CONNECTIONS BETWEEN CANCER RESEARCH AND AI.

Our mission is to enhance cancer treatment and knowledge by harnessing the power of computer intelligence. Guided by our vision that computers will eventually be able to think and perform similar tasks as humans, we strive to develop cutting-edge artificial intelligence and statistical approaches for building system models of tumors. This way opening the doors to collaboration with experimental labs and pharmaceutical companies . Our lab fosters a diverse, collaborative environment for advancing cancer research.

Our lab is dedicated to developing innovative therapies and identifying predictive biomarkers for late-stage cancers. For this it is crucial that we explore the following areas:

1) Factors that contribute to tumor micro-environments.

2) The potential for reversal

3) The patients who could benefit from these techniques.

The current program focuses on the development and design of new immunotherapies for advanced cancer patient, and tailor our knowledge for pediatric cancers and minority populations.

February 2024: Dr Kushal Virupakshappa gets awarded the 2024 AAI Intersect Fellowship for Computational Scientists and Immunologists: Congratulations!

December 2023: Our New H100 Machine Running:  Happy holidays!

November 2023: David Arredondo Joins the Lab as Postdoctoral Trainee: David earned his degree from the UNM School of Engineering, specializing in DNA Nanotechnology and Molecular computing

November 2023: Explore TumorAI Lab's Research in Avi's Presentation at UNM Grand Rounds. 

See the presentation here 

October 2023: BSGP Student Clara Bertoni Joins TumorAI Lab for Rotation in Single Cell Analysis.

New Pre-Print

We’re thrilled to announce the release of our latest preprint in collaboration with Rafa Irizarry's Lab! We’ve developed a principled approach, scDist, to tackle the challenge of individual and cohort variability in single-cell data. As the adoption of single-cell technologies grows, the importance of rigorous and principled approaches to handle the resulting data variation cannot be overstated. It’s crucial for improving the accuracy of our findings and reducing false positives. Adoption of this rigrous tool allowed us to detect robust perturbations in DC, pDC, and NK cells in COVID-19 and immunotherapy treatment responses.As single-cell datasets continue to expand, we believe that there is even more work to be done by those are passionate about the intersection of AI, statistics, and biology. With collective effort and open discussion, we can drive this field forward. Let’s make a difference together! 

Take a look at our pre-print here.


Photo by National Cancer Institute on Unsplash.

Our Latest Publication in Cancer Discovery

This research publication in Cancer Discovery explores the discovery of bipotent drugs as a new solution for traditional combination therapies through BipotentR to find cancer cell-specific regulators that help modulate tumor immunity and a number of other oncogenic pathways. 

This tool presents relative importance to evaluating patient response to treatment and the identification of new targets for drugs that allows for efficient elimination of tumors and cancerous cells. When this approach is taken and the topmost candidate tumors are inhibited through the suppression of their metabolism, the cancer cells are more likely to be killed/destroyed.  

To learn more about this publication, click here. 

If you are interested in some other of our publications, please refer to our page "Publications".

We believe in diversity and inclusivity for everyone, and that are dedicated to fostering these values inside our many cutting edge projects. A concept that translated directly to all that we do. 

This is one of the reasons why we want to keep our tools and projects available to the public. All of our Artificial Intelligence models and approaches for statistical  representation are publicly available through a number of websites and links. Refer to these links and access instructions through the following link.

This way we can all work together towards this simple goal. 

Photo by National Cancer Institute on Unsplash.