JOIN US IN SHAPING THE CONNECTIONS BETWEEN CANCER RESEARCH AND AI.
JOIN US IN SHAPING THE CONNECTIONS BETWEEN CANCER RESEARCH AND AI.
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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.
At Tumor-AI Lab, we develop artificial intelligence algorithms to advance basic science and cancer treatment. Our lab focuses on three areas:
Broadening the coverage of precision treatment through novel AI tools that transform insights from the transcriptomes of cancer cells into potential drugs and specific gene alterations targeting particular cancers.
Predicting emergent gene and protein traits by extracting multi-modal gene data through a large language model and knowledge injection techniques that combine structured and unstructured databases.
Deconstructing immune responses through imaging and analysis of single-cell and spatial biology.
Jan 2025: Ala will graduate this May and begin his journey as an Assistant Professor in October! He’s the first graduate student from the TumorAI Lab since its move to UNM. Congrats, Ala—we’re so proud of you! Wishing more of our students (I want everyone!) follow in your footsteps!
Jan 2025: Ala will graduate this May and begin his journey as an Assistant Professor in October! He’s the first graduate student from the TumorAI Lab since its move to UNM. Congrats, Ala—we’re so proud of you! Wishing more of our students (I want everyone!) follow in your footsteps!
Nov 2024: Preliminary Protein2text (protein2text.tumorai.org) model is live! It predicts protein function from amino acid sequences. Congrats Ala! Note: This is an early version and may hallucinate. Use with caution—full release coming soon. Stay tuned!
Nov 2024: Preliminary Protein2text (protein2text.tumorai.org) model is live! It predicts protein function from amino acid sequences. Congrats Ala! Note: This is an early version and may hallucinate. Use with caution—full release coming soon. Stay tuned!
Sept 2024: Access to world's most powerful supercomputer. With over 37,000 GPU, we are ready to tackle computational challenges that typical on-premise clusters or cloud cannot handle.
Sept 2024: Access to world's most powerful supercomputer. With over 37,000 GPU, we are ready to tackle computational challenges that typical on-premise clusters or cloud cannot handle.
Sept 2024: Submitted two Manuscripts on Graphs. Congrats Mikaela, Luis, and Yue, and co-authors! Oct is coming!
Sept 2024: Submitted two Manuscripts on Graphs. Congrats Mikaela, Luis, and Yue, and co-authors! Oct is coming!
Sept 2024: Our AI research at thewas recently featured on KOAT News! https://www.koat.com/article/new-mexico-unm-cancer-center-ai-research/62073232
Sept 2024: Our AI research at thewas recently featured on KOAT News! https://www.koat.com/article/new-mexico-unm-cancer-center-ai-research/62073232
Sept 2024: ScDist accepted to Nature Comm! Statistically principled approach for identifying pertubation in single cell data. https://www.nature.com/articles/s41467-024-51649-3
Sept 2024: ScDist accepted to Nature Comm! Statistically principled approach for identifying pertubation in single cell data. https://www.nature.com/articles/s41467-024-51649-3
Aug 2024: LitGene, a transformer leveraging text knowledge for gene representations, predicting disease risk genes, grounding predictions to published literature. In bioArxiv now https://doi.org/10.1101/2024.08.07.606674 . Also the website https://litgene.avisahuai.com/
Aug 2024: LitGene, a transformer leveraging text knowledge for gene representations, predicting disease risk genes, grounding predictions to published literature. In bioArxiv now https://doi.org/10.1101/2024.08.07.606674 . Also the website https://litgene.avisahuai.com/
June 2024: Submitted Four Manuscripts for New Multimodal Approaches from TumorAI. Submitted four new manuscripts featuring innovative multimodal approaches DeepVul, MedGraphNet, Histopath-fusion, and Genen. Congratulations to Kushal, Ala, Macaulay, Yue, Kaibin, David, Luis, Mikaela, and Michael. Your hard work has truly paid off. Fingers crossed!
June 2024: Submitted Four Manuscripts for New Multimodal Approaches from TumorAI. Submitted four new manuscripts featuring innovative multimodal approaches DeepVul, MedGraphNet, Histopath-fusion, and Genen. Congratulations to Kushal, Ala, Macaulay, Yue, Kaibin, David, Luis, Mikaela, and Michael. Your hard work has truly paid off. Fingers crossed!
March 2024: Luis' Expert Guidance Propels Our High School Trainee Ganesh to Prestigious Awards! With Luis' mentorship, Ganesh topped in the Senior Division - Medicine & Health Sciences, also getting Donald Partridge Memorial Neuroscience and Richard Bild Memorial Research Challenge Awards.
March 2024: Luis' Expert Guidance Propels Our High School Trainee Ganesh to Prestigious Awards! With Luis' mentorship, Ganesh topped in the Senior Division - Medicine & Health Sciences, also getting Donald Partridge Memorial Neuroscience and Richard Bild Memorial Research Challenge Awards.
March 2024: GeneLLM accepted at the ICLR 2024. A hearty congratulations to Ala, Macaulay, David, Kushal, and the rest!
March 2024: GeneLLM accepted at the ICLR 2024. A hearty congratulations to Ala, Macaulay, David, Kushal, and the rest!
February 2024: Dr Kushal Virupakshappa gets awarded the 2024 AAI Intersect Fellowship for Computational Scientists and Immunologists: Congratulations!
February 2024: Dr Kushal Virupakshappa gets awarded the 2024 AAI Intersect Fellowship for Computational Scientists and Immunologists: Congratulations!
Jan 2024: Dr. Sarah Adams' project on DOD Ovarian Cancer Clinical Trials Academy has been funded! Our lab is thrilled to be part of the ACCELERATOR, an AI tool for ovarian cancer trials.
Jan 2024: Dr. Sarah Adams' project on DOD Ovarian Cancer Clinical Trials Academy has been funded! Our lab is thrilled to be part of the ACCELERATOR, an AI tool for ovarian cancer trials.
December 2023: Our New H100 Machine Running: Happy holidays!
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: 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.
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.
October 2023: BSGP Student Clara Bertoni Joins TumorAI Lab for Rotation in Single Cell Analysis.
ScDist in nature communication
ScDist in nature communication
Our latest publication in Nature Communications, in collaboration with Rafa Irizarry's Lab, introduces scDist—a principled approach to address variability in single-cell data. This rigorous tool enhances accuracy and uncovers robust perturbations in DC, pDC, and NK cells in COVID-19 and immunotherapy responses. As single-cell datasets grow, we’re excited to advance the intersection of AI, statistics, and biology.
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.
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