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Welcome to DataX Lab
DataX Lab, located in 3237 at SEB@UNLV, is established in 2015 by Dr. Mingon Kang. We aim to develop novel and efficient algorithms to solve challenging computational problems in Bioinformatics and Big Data Analytics, and to devote ourselves to providing computational analysis tools for research use. To be more specific, we are working on:
- Interpretable and Integrative Deep Learning in Bioinformatics
- Next Generation Sequencing data analysis
- Multi-omics data analysis
- Clinical and Translational Research
- Intelligent Systems in Computer Vision
Research Lab
GPU Cluster
DataX Github
DLB2H Workshop
Research Projects
HipoMap
HipoMap propose a novel graphical representation map of whole-slide histopathological images for slide-based analysis. HipoMap generates a fixed size of image-type map that represents comprehensive patterns of interests in a WSI
Hi-LASSO
A High-Dimensional LASSO(Hi-LASSO) improves a LASSO model providing better performance of both prediction and feature selection on extremely high-dimensional data. (Kim et al, IEEE Access, 2019)
Deep-Hipo
The deep learning for Histopathology (Deep-Hipo) can accurately analyze histopathological images by learning multi-scale morphological patterns from various magnification levels of patches in a WSI simultaneously. (Kosaraju et al, 2020)
This page is created by Hyeryeong Seo at April, 2020. ©DataX Lab since 2015.