PublisherDOIYearVolumeIssuePageTitleAuthor(s)Link
Genomics & Informatics10.5808/gi.200762021191e10Machine learning based anti-cancer drug response prediction and search for predictor genes using cancer cell line gene expressionKexin Qiu, JoongHo Lee, HanByeol Kim, Seokhyun Yoon, Keunsoo Kanghttp://genominfo.org/upload/pdf/gi-20076.pdf, http://genominfo.org/journal/view.php?doi=10.5808/gi.20076, http://genominfo.org/upload/pdf/gi-20076.pdf
10.36227/techrxiv.132733192020Personalized drug-response prediction model for lung cancer patients using machine learningRizwan Qureshihttps://ndownloader.figshare.com/files/25562447
10.36227/techrxiv.13273319.v12020Personalized drug-response prediction model for lung cancer patients using machine learningRizwan Qureshihttps://ndownloader.figshare.com/files/25562447
Genes10.3390/genes13122233202213122233Bioinformatics Prediction and Machine Learning on Gene Expression Data Identifies Novel Gene Candidates in Gastric CancerMedi Kori, Esra Govhttps://www.mdpi.com/2073-4425/13/12/2233/pdf
Genes10.3390/genes120608442021126844kESVR: An Ensemble Model for Drug Response Prediction in Precision Medicine Using Cancer Cell Lines Gene ExpressionAbhishek Majumdar, Yueze Liu, Yaoqin Lu, Shaofeng Wu, Lijun Chenghttps://www.mdpi.com/2073-4425/12/6/844/pdf
Genes10.3390/genes1109107020201191070Enhanced Co-Expression Extrapolation (COXEN) Gene Selection Method for Building Anti-Cancer Drug Response Prediction ModelsYitan Zhu, Thomas Brettin, Yvonne A. Evrard, Fangfang Xia, Alexander Partin, Maulik Shukla, Hyunseung Yoo, James H. Doroshow, Rick L. Stevenshttps://www.mdpi.com/2073-4425/11/9/1070/pdf
IEEE Access10.1109/access.2018.2886604201974232-4238Gene Expression Analysis for Early Lung Cancer Prediction Using Machine Learning Techniques: An Eco-Genomics ApproachJayadeep Patihttp://xplorestaging.ieee.org/ielx7/6287639/8600701/08584430.pdf?arnumber=8584430
Nuclear Engineering and Technology10.1016/j.net.2022.03.01920225483027-3033Comparison and optimization of deep learning-based radiosensitivity prediction models using gene expression profiling in National Cancer Institute-60 cancer cell lineEuidam Kim, Yoonsun Chunghttps://api.elsevier.com/content/article/PII:S1738573322001395?httpAccept=text/xml, https://api.elsevier.com/content/article/PII:S1738573322001395?httpAccept=text/plain
2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)10.1109/bibm55620.2022.99956222022Drug response prediction for lung cancer patients using biophysical simulation and machine learningRizwan Qureshi, Tanvir Alam, Jia Wuhttp://xplorestaging.ieee.org/ielx7/9994793/9994847/09995622.pdf?arnumber=9995622
Proceedings of the 2017 International Conference on Computational Biology and Bioinformatics10.1145/3155077.31550782017Individual Drug Treatment Prediction in Oncology Based on Machine Learning Using Cell Culture Gene Expression DataNikolay Borisov, Victor Tkachev, Ilya Muchnik, Anton Buzdinhttps://dl.acm.org/doi/pdf/10.1145/3155077.3155078