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AI in Cancer Research / AI+癌症研究Multi-omics Integration

Christina S. Leslie

Ph.D.

🏢Memorial Sloan Kettering Cancer Center🌐USA

Computational Biologist

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Key Papers
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Key Contributions

👥Biography 个人简介

Christina Leslie is a computational biologist who develops machine learning methods for understanding gene regulation and epigenomics. Her research has created algorithms for analyzing chromatin accessibility, transcription factor binding, and non-coding regulatory elements that are dysregulated in cancer. Leslie's work advances understanding of how epigenetic changes drive cancer development.

Christina Leslie是计算生物学家,开发用于理解基因调控和表观基因组学的机器学习方法。她的研究创建了分析染色质可及性、转录因子结合和在癌症中失调的非编码调控元件的算法。Leslie的工作推进了对表观遗传变化如何驱动癌症发展的理解。

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🧪Research Fields 研究领域

Machine Learning机器学习
Epigenomics表观基因组学
Gene Regulation基因调控

🎓Key Contributions 主要贡献

Epigenomics ML

Developed machine learning methods for chromatin and regulatory element analysis.

String Kernel Methods

Created kernel methods for biological sequence analysis.

Representative Works 代表性著作

[1]

The spectrum kernel: a string kernel for SVM protein classification

Proceedings of Pacific Symposium on Biocomputing (2002)

Foundational string kernel method for biological sequences.

📄Data Sources 数据来源

Last updated: 2026-03-05 | All information from publicly available academic sources

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