Haopeng Xiao
@haopengxiao.bsky.social
Assistant Professor at Stanford Biochemistry & Stanford Cancer Institute. We combine mass spectrometry, data science, and mechanistic biology to understand protein function and druggability. xiaolab.space
Reposted by Haopeng Xiao
For those who perform thermal proteome profiling (TPP) experiments, you might find this new data analysis approach (and open source Python software) useful. Developed by postdoc @jfhevler.bsky.social 🙏
arxiv.org/abs/2508.096...
arxiv.org/abs/2508.096...
Thermal Tracks: A Gaussian process-based framework for universal melting curve analysis enabling unconstrained hit identification in thermal proteome profiling experiments
Thermal Tracks is a Python-based statistical framework for analyzing protein thermal stability data that overcomes key limitations of existing thermal proteome profiling (TPP) work-flows. Unlike stand...
arxiv.org
October 24, 2025 at 10:18 PM
For those who perform thermal proteome profiling (TPP) experiments, you might find this new data analysis approach (and open source Python software) useful. Developed by postdoc @jfhevler.bsky.social 🙏
arxiv.org/abs/2508.096...
arxiv.org/abs/2508.096...
Reposted by Haopeng Xiao
Excited to share that I’ve started my lab as an assistant professor at the University of Texas Southwestern Medical Center in Dallas.
Thank you to all the mentors, friends, and colleagues who have supported me throughout the years!
Thank you to all the mentors, friends, and colleagues who have supported me throughout the years!
October 1, 2025 at 1:23 PM
Excited to share that I’ve started my lab as an assistant professor at the University of Texas Southwestern Medical Center in Dallas.
Thank you to all the mentors, friends, and colleagues who have supported me throughout the years!
Thank you to all the mentors, friends, and colleagues who have supported me throughout the years!
Reposted by Haopeng Xiao
The results are in: top codes in Stanford #RNA 3D Folding @kaggle.com competition are competitive with CASP16-leading humans Vfold, beat AlphaFold 3. Top team’s trick was template-based modeling, not #DeepLearning. Congrats: john, odat, Eigen, + all 1706 participants! www.kaggle.com/competitions...
September 24, 2025 at 4:21 PM
The results are in: top codes in Stanford #RNA 3D Folding @kaggle.com competition are competitive with CASP16-leading humans Vfold, beat AlphaFold 3. Top team’s trick was template-based modeling, not #DeepLearning. Congrats: john, odat, Eigen, + all 1706 participants! www.kaggle.com/competitions...
We developed a MS and machine learning approach to globally identify protein regulators of metabolism. We found protein LRRC58 controls cellular cysteine catabolism by mediating degradation of CDO1, the rate-limiting enzyme of the catabolic cysteine shunt to taurine. www.nature.com/articles/s41...
Covariation MS uncovers a protein that controls cysteine catabolism - Nature
A mass spectrometry-based approach globally identifies protein regulators of metabolism and reveals the role of LRRC58 in controlling cysteine catabolism.
www.nature.com
September 18, 2025 at 6:38 AM
We developed a MS and machine learning approach to globally identify protein regulators of metabolism. We found protein LRRC58 controls cellular cysteine catabolism by mediating degradation of CDO1, the rate-limiting enzyme of the catabolic cysteine shunt to taurine. www.nature.com/articles/s41...
We are seeking a life science research professional/technician (medcareers.stanford.edu/job/stanford...) and a postdoctoral fellow(postdocs.stanford.edu/prospective/...). If you are interested in using mass spec and machine learning to understand protein function and druggability please reach out!
September 18, 2025 at 5:00 AM
We are seeking a life science research professional/technician (medcareers.stanford.edu/job/stanford...) and a postdoctoral fellow(postdocs.stanford.edu/prospective/...). If you are interested in using mass spec and machine learning to understand protein function and druggability please reach out!