Presenting #LitGene! An interpretable transformer for gene representations, integrating unstructured and structured data - unified framework mitigates bias, enhances interpretability, and grounds AI predictions in scientific literature at https://t.co/nuUrm9VCze 1/2

Our humble approach!

Thanks to KOAT-TV for highlighting Dr. Sahu's work. The Lobo Cancer Challenge provides pilot funding to a number of UNMCCC researchers. Pilot funding helps kick-start the new research projects that deepen our understanding of cancer and how to treat it. https://t.co/XXmJj8Rty8

Our lab research highlighted at KOAT TV.

Lobo Cancer Challenge supporting cutting-edge research at UNM | Click on the image to read the full story

(1/n) Excited to announce a new article with @rafalab @AviSahuAI describing our approach scDist for finding cell types with transcriptional changes between conditions in single-cell data! https://t.co/xkZnBtGzSW

LitGene: a transformer-based model that uses contrastive learning to integrate textual information into gene representations

LitGene: a transformer-based model that uses contrastive learning to integrate textual information into gene representations https://t.co/SA4otaHljD #biorxiv_bioinfo

We demonstrated its capability in predicting protein properties & zero-shot risk genes for obesity, asthma, hypertension, & schizophrenia Accessible at https://t.co/oFfGqsufQ8 🌐 #AI #Bioinformatics #MachineLearning #OpenScience #EthicalAI

⚡️🔬📣 Excited to share our new @Nature article building and evaluating PathChat, a multimodal generative AI copilot and chatbot for human pathology. Article: https://t.co/sYSpFCAOkV Open Access Link: https://t.co/ELHb5ly5NE We leverage our previous success in building

Why do the loss of chromosome 10 and the gain of chromosome 7 happen so often in #gliomas? We investigate this over-four-decade-old mystery and shed some new light on this! Our work is now out in bioRxiv! #cancer @theNCI @NCIResearchCtr

The co-occurrence of chromosome 10 loss and 7 gain in #gliomas is the MOST frequent loss-gain co-aneuploidy pair in human #cancers, a phenomenon that has been investigated without resolution since the late 1980s. What is this mystery? We investigate! (1/n) https://t.co/gPKyTnmcrH

Congratulations to Sarah Adams, MD, on being named Dean of the Department of Defense Ovarian Cancer Clinical Trial Academy. This award will also fund an AI-based biomarker discovery project based at UNM with Avinash Sahu, PhD.

Congratulations to @MuradRMamedov and co-author @AviSahuAI, both 2019 #MichelsonPrizes recipients, on a new paper published in @Nature that uncovers unexpected interactions between T cells and cancer cells:

Congrats, @MuradRMamedov and co-author @AviSahuAI, both 2019 #MichelsonPrizes Winners, for their exceptional research published in @Nature. https://t.co/hvLA2Tepzf

How likely is it that an email that begins with "hope you are doing well" and ends with "looking forward to hearing from you" was composed by ChatGPT? 🙃

Just a reminder that you can download the @poe_platform app on your mobile phone and access a lot of artificial intelligence models. In particular, you can access: - Sage - Claude-2-100k - Claude-instant-100k - GPT-4 - Claude-instant - ChatGPT - ChatGPT-16k - GPT-4-32k

Clustering algorithms report clusters even when none exist. In single-cell RNA-Seq pipelines, novel cell types are often identified by clustering algorithms. Expanding on Kimes et al.'s work, we introduce significance analysis for single-cell RNA-Seq data: https://t.co/ut1kPjKVCM

Want to join an AI-based antibody therapeutics company with a 1st-in-class molecule in the clinic and help us solve the antibody code? Please consider GV20!

5/n: The fear has fluctuated over decades, depending on economic conditions and pace of technological change. Are we in a similar place now? Is AI and machine learning our new wave of 'technological unemployment'? Is our fear rational or irrational? 📈📉 #technology #fear