Deep-learning framework advances tissue analysis in spatial transcriptomics
Peer-Reviewed Publication
Updates every hour. Last Updated: 2-May-2025 14:09 ET (2-May-2025 18:09 GMT/UTC)
Spatial transcriptomics techniques, which map gene activity in intact tissues, often face challenges in accurately identifying distinct tissue regions. Now, researchers from Japan have developed STAIG, a deep-learning framework that integrates gene expression, spatial data, and histological images to identify tissue regions with high accuracy. The proposed framework holds much promise for understanding the complexities of cancer development, brain function, and how our bodies are constructed.
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Education experts at the University of South Australia are encouraging schools to consider problem-based learning (PBL) in a move to improve engagement and creativity among high school students. New UniSA research demonstrates how hands-on, community-based projects can deliver successful learning outcomes for disengaged students.
Aerospace engineering senior Philip Wilson attended an American Institute of Aeronautics and Astronautics (AIAA) conference. Rohit Raut, a senior physics major, presented his work at a nuclear research symposium, and senior biology major Jaden Rankin had the opportunity to feature her research at an entomology conference. These and other University of Texas at Arlington students were able to showcase their original research at major symposiums thanks to UTA’s expansion of its popular undergraduate research program that provides funding for select students to present at academic conferences.