3/12/2024: Unveiling the Impact of AI in Genomic Medicine – Insights from My Latest Interview by SEQanswers
I recently had the opportunity of being interviewed by SEQanswers, where I delved into the transformative power of Artificial Intelligence in the world of medicine. We’re standing on the brink of a healthcare revolution, and I’m thrilled to share my perspectives on how AI is reshaping our approach to medical challenges, diagnosis, and treatment Link […]
12/8/2023: Jing Huang won 1st place in the Patel-Naik Award
Congratulations to Jing Huang on winning 1st place in the Patel-Naik Award! This achievement is particularly impressive given the highly competitive nature of the award, with many of the contenders being senior BIOS Ph.D. students.
11/5/2023: AI in Genomics Lab attended ASHG 2023
Posters presented by lab members: Chenyang Yuan: Integration of label-free, interpretable image features with spatial molecular profiles.(PB5093) Yefeng Yang: Efficient quantification of pattern similarity between spatial genomics and cell morphology. (PB3369)
10/16/2023: Hu was invited for seminar and workshop in AI and Machine Learning Applications in Bioinformatics Symposium
The meeting will include presentations from renowned speakers on recent developments and applications of deep learning models in bioinformatics, genomics, and structural biology, as well as interactive workshops and networking. Link: 2023 IOB Symposium
05/29/2023: Collaborative publishing in Nature Medicine.
Congratulations on our groundbreaking collaborative publication in Nature Medicine: “Pan-cancer T cell atlas reveals crucial cellular stress response state associated with immunotherapy resistance.” In this remarkable study, we have successfully identified a unique stress response state, TSTR, characterized by heat shock gene expression. TSTR cells are detectable in situ in the tumor microenvironment across various […]
05/09/2023: New Cell Systems paper on machine learning tool to annotate tumor microenvironment at super-resolution.
Glad to share our latest publication in Cell Systems. We developed a method named TESLA, which is a spatially-resolved transcriptomics data analysis tool for integrates gene expression and histology to annotate tumor microenvironment at super-resolution. Link: https://doi.org/10.1016/j.cels.2023.03.008
05/04/2023: Hu received the Kaushal multidisciplinary science publication award 2023 at the Genetics annual Symposium
Hu received the Kaushal multidisciplinary science publication award 2023 at the Genetics annual Symposiumre at Perelman School of Medicine, University of Pennsylvania.
02/01/2023: AI in Genomics Lab is hiring for postdoctoral fellows
JOB DESCRIPTION The AI in Genomics Lab at the Department of Human Genetics at Emory University (PI: Jian Hu, PhD) invites applications for a postdoctoral fellow position in support of research in Statistical Genomics and specifically in the areas of developing statistical and machine learning algorithms to decipher disease mechanism. The initial appointment is for […]
01/30/2023: Hu received ASA statistics in genomics & genetics section best student paper award
Dr. Hu’s paper on spatial transcriptomics data analysis won the 2021 ASA Section of Statistics in Genomics and Genetics best student paper award! Dr. Hu will present his work at JSM in August.
11/14/2022: Hu was invited for guest lecture in the at the University of Saskatchewan
Novel Machine Learning for Genomics Data in course Statistical Machine Learning for Data Science This course provides learning opportunities on statistical software, R, with some focus on data management and wrangling, reproducibility, and visualization. On top of that, there are basic introductions to Machine Learning such as k-NN, Naive Bayes, regression methods, etc. The focus […]