Xingcheng Lin

Assistant Professor at North Carolina State University

[Xingcheng Lin @XingchengLin]

Today, we say goodbye to Thomas Thornton. Thomas is the first undergraduate to graduate from our group. He developed a GPU-accelerated RNA simulation platform (https://t.co/UNxWmyIGnk), received McCormick Outstanding Research Award, and will begin PhD at Northwestern University.

[Xingcheng Lin @XingchengLin]

@MARGARETSCHEUNG Thank you, Margaret! I could not make it without support from people like you. Looking forward to more collaborations!

[Xingcheng Lin @XingchengLin]

I am incredibly excited and grateful for the support from the NSF CAREER Award, and we look forward to bringing new science and discoveries to our community!

[NC State Physics and Astronomy @ncstatephysics]

Congratulations to @XingchengLin on receiving an #NSF CAREER Award! 🎉

Using #AI and physics-based simulations, this project will uncover how epigenetic changes shape DNA organization and gene regulation—advancing our understanding of genome function and human disease.

[Xingcheng Lin @XingchengLin]

We extend our earlier version of the protein-DNA predictive tool (https://t.co/DdWtLOmTMJ) to predict position-specific methylation sensitivity and integrate WGBS data to improve genomic protein–DNA binding site predictions.

[Xingcheng Lin @XingchengLin]

Glad to share our latest work on DNA methylation prediction, focusing on position-specific methylation sensitivity and genomic protein-DNA binding.
https://t.co/x808JEDG0c

[Xingcheng Lin @XingchengLin]

Excited to share our latest pre-print on predicting protein-RNA interactions! We present a biophysics-inspired machine learning framework that predicts sequence-specific binding and identifies strong-binding RNA motifs.
https://t.co/bd8CxBlzQH

[Xingcheng Lin @XingchengLin]

@DvirHarris @eLife Thank you!

[Xingcheng Lin @XingchengLin]

Glad to share that our protein-DNA binding prediction paper is now published in @eLife: Interpretable protein-DNA interactions captured by structure-sequence optimization https://t.co/2Qze74Dstg

Check out Yafan's summary video for the upcoming ISMB/ECCB 2025 conference.

[Xingcheng Lin @XingchengLin]

This work has been published in Biochemistry. Good job, Rina!
https://t.co/mmBObihsMU

[Xingcheng Lin @XingchengLin]

Excited to share our latest manuscript
https://t.co/rrdu9POe3U
In this manuscript, we utilized an explicit-ion chromatin model to quantify the effects of histone 4 acetylation on the higher-order chromatin structure.

[Xingcheng Lin @XingchengLin]

This work is led by Rina Li, a graduate student in Physics in our research group.

[Xingcheng Lin @XingchengLin]

Excited to share our latest manuscript
https://t.co/rrdu9POe3U
In this manuscript, we utilized an explicit-ion chromatin model to quantify the effects of histone 4 acetylation on the higher-order chromatin structure.

[Xingcheng Lin @XingchengLin]

3. This modest reduction in inter-nucleosome interactions is amplified at the chromatin level, leading to nucleosome destacking and exposure of nucleosomal DNA. The destabilization of chromatin structure is driven by fluctuations in the entry-exit angles of linker DNA.

[Xingcheng Lin @XingchengLin]

This work is led by Yafan Zhang, a first-year Bioinformatics graduate student at NCSU. We greatly appreciate fruitful discussions with Dr. Keith Weninger, Dr. Faruck Morcos (@faruckm), Dr. Qin Zhou, and Dr. Arun Kumar Ganesan (@genome_voyager).

[Xingcheng Lin @XingchengLin]

Excited to share our latest manuscript https://t.co/s9W5jlMpgL
In this manuscript, we introduce "IDEA", a predictive biophysical model for quantitative predictions of genome-wide binding sites and binding affinities of DNA-binding proteins.

[Xingcheng Lin @XingchengLin]

3. The trained energy model allows for direct interpretation of physicochemical interactions between individual amino acids and nucleotides and is further incorporated into a coarse-grained simulation framework to accurately predict protein-DNA binding free energies.