EXP2SL: A Machine Learning Framework for Cell-Line-Specific Synthetic Lethality Prediction-Reference-Cited by-同舟云学术

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EXP2SL: A Machine Learning Framework for Cell-Line-Specific Synthetic Lethality Prediction

Published:2020-02-28 Issue: Volume:11 Page:
ISSN:1663-9812
Container-title:Frontiers in Pharmacology
language:
Short-container-title:Front. Pharmacol.

Author:

Wan Fangping,Li Shuya,Tian Tingzhong,Lei Yipin,Zhao Dan,Zeng Jianyang

Funder

National Natural Science Foundation of China

Publisher

Frontiers Media SA

Subject

Pharmacology (medical),Pharmacology

Reference46 articles.

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2. Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1;Barbie;Nature,2009

3. Exploring genetic interactions and networks with yeast;Boone;Nat. Rev. Genet.,2007

4. Specific killing of BRCA2-deficient tumours with inhibitors of poly (ADP-ribose) polymerase;Bryant;Nature,2005

5. API design for machine learning software: experiences from the scikit-learn project;Buitinck;arXiv preprint arXiv:,2013

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1. Methylation synthetic lethality: Exploiting selective drug targets for cancer therapy;Cancer Letters;2024-08

2. Text-mining-based feature selection for anticancer drug response prediction;Bioinformatics Advances;2024-01-01

3. ELISL: early–late integrated synthetic lethality prediction in cancer;Bioinformatics;2023-12-19

4. Multi-omics Sampling-based Graph Transformer for Synthetic Lethality Prediction;2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM);2023-12-05

5. Synthetic Lethality Screening with Recursive Feature Machines;2023-12-05

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