ORCID: 0000-0001-9358-9907

Rui Yang

PhD student in Computational Biology

Hi, I am a PhD student in Computational Biology at Tri-Institutional CBM Program. My supervisor is Dr. Christina Leslie.

My research interests are in developing interpretable deep learning models to predict and study the 3D chromatin structures, and to better understand the mechanisms of gene regulations.

In the future, I hope to continue exploring

Develop deep learning models to decipher complex biological mechanisms.
Develop and apply interpretable learning techniques to foster connections between biological systems.
Explore causal relationships in biological systems for a deep understanding of molecular dynamics.

Before joining the PhD program, I was a computational associate at the Broad Institute, working on developing and applying statistical models to study gene expression and drug responses.

Github

Google Scholar

Twitter

Research Highlights

Epiphany

Predicting the Hi-C Contact Map from 1D Epigenomic Data

[paper], [github]

HiC2Self

Self-Supervised Hi-C Contact Map Denoising

[manuscript], [github in progress]

FiTnEss

A Novel Statistical Method for Identification of Essential Genes in Bacteria from Tn-Seq data

[github]

Presentations and Publications

Talks

[Contributed Talk] HiC2Self: Self-supervised Hi-C contact map denoising. Rui Yang, Alireza Karbalaghareh, Christina Leslie. The 2023 ICML Workshop on Computational Biology. Best Paper Award.
[Spotlight Talk] Contrastive learning for decoding the epigenomic dance: SETD2 loss unleashes widespread chromatin remodeling. Rui Yang, Amrita Nargund, Christina Leslie, et al. 2023 NCI Junior Investigator Annual Meeting.

Publications

Epiphany: predicting Hi-C contact maps from 1D epigenomic signals. Rui Y.*, Arnav D.*, Vianne G., et al. Genome Biology, 2023. [link]
ChromaFold predicts the 3D contact map from single-cell chromatin accessibility. Vianne G., Rui Y., Arnav D., et al. bioRxiv. 2023. [link]
Accelerating batch active learning using continual learning techniques. Arnav D., Gantavya B., Megh B., et al. arXiv. 2023 [link]
Efficient detection and assembly of non-reference DNA sequences with synthetic long reads. Dmitry M., Rui Y., Patrick M., et al. Nucleic Acids Research. 2022. [link]
Hybridization-based capture of pathogen mRNA enables paired host-pathogen transcriptional analysis. Viktoria B., Cristina P., Nirmalya B., Rui Y., et al. Scientific Reports, 2019. [link]
Simultaneous detection of genotype and phenotype enables rapid and accurate antibiotic susceptibility determination. Roby B., Nirmalya B., Peijun M., et al. Nature Medicine, 2019. [link]
Defining the core essential genome of Pseudomonas aeruginosa. Bradley E., Rui Y., Anne C., et al. PNAS, 2019. [link]

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