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The surge in high-throughput omics data has reshaped the landscape of biological research, underlining the need for powerful, user-friendly data analysis and interpretation tools.
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Allelotype of pancreatic adenocarcinoma using xenograft enrichment
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Rseqc: quality control of rna-seq experiments
Liguo Wang, Shengqin Wang, and Wei Li · 2012
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Normalization and noise reduction for single cell rna-seq experiments
Bo Ding, Lina Zheng, Yun Zhu, Nan Li, Haiyang Jia, Rizi Ai, Andre Wildberg, and Wei Wang · 2015
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From reads to genes to pathways: differential expression analysis of rna-seq experiments using rsubread and the edger quasi-likelihood pipeline
Yunshun Chen, Aaron TL Lun, and Gordon K Smyth · 2016
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Classification of low quality cells from single-cell rna-seq data
Tomislav Ilicic, Jong Kyoung Kim, Aleksandra A Kolodziejczyk, Frederik Otzen Bagger, Davis James McCarthy, John C Marioni, and Sarah A Teichmann · 2016
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Enrichr: a comprehensive gene set enrichment analysis web server 2016 update
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Misuse of RPKM or TPM normalization when comparing across samples and sequencing protocols
Shanrong Zhao, Zhan Ye, and Robert Stanton · 2020
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Data-driven detection of subtype-specific differentially expressed genes
Lulu Chen, Yingzhou Lu, Chiung-Ting Wu, Robert Clarke, Guoqiang Yu, Jennifer E Van Eyk, David M Herrington, and Yue Wang · 2021
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Interpretation of omics data analyses
Ryo Yamada, Daigo Okada, Juan Wang, Tapati Basak, and Satoshi Koyama · 2021
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DDN2.0: R and python packages for differential dependency network analysis of biological systems
Bai Zhang, Yi Fu, Yingzhou Lu, Zhen Zhang, Robert Clarke, Jennifer E Van Eyk, David M Herrington, and Yue Wang · 2021
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Artificial intelligence foundation for therapeutic science
Kexin Huang, Tianfan Fu, Wenhao Gao, Yue Zhao, Yusuf Roohani, Jure Leskovec, Connor W Coley, Cao Xiao, Jimeng Sun, and Marinka Zitnik · 2022
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Scenic: single-cell regulatory network inference and clustering
Sara Aibar, Carmen Bravo González-Blas, Thomas Moerman, Vân Anh Huynh-Thu, Hana Imrichova, Gert Hulselmans, Florian Rambow, Jean-Christophe Marine, Pierre Geurts, Jan Aerts, et al · 2017
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The reactome pathway knowledgebase
Antonio Fabregat, Steven Jupe, Lisa Matthews, Konstantinos Sidiropoulos, Marc Gillespie, Phani Garapati, Robin Haw, Bijay Jassal, Florian Korninger, Bruce May, et al · 2018
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Single-cell rna sequencing technologies and bioinformatics pipelines
Byungjin Hwang, Ji Hyun Lee, and Duhee Bang · 2018
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Multi-omics Data Integration for Identifying Disease Specific Biological Pathways
Yingzhou Lu · 2018
Cited alongside, same era.
Integrated identification of disease specific pathways using multi-omics data
Yingzhou Lu, Yi-Tan Chang, Eric P Hoffman, Guoqiang Yu, David M Herrington, Robert Clarke, Chiung-Ting Wu, Lulu Chen, and Yue Wang · 2019
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Count-based differential expression analysis of rna sequencing data using r and bioconductor
Simon Anders, Davis J McCarthy, Yunshun Chen, Michal Okoniewski, Gordon K Smyth, Wolfgang Huber, and Mark D Robinson
Cited in the paper.
COT: an efficient and accurate method for detecting marker genes among many subtypes
Yingzhou Lu, Chiung-Ting Wu, Sarah J Parker, Zuolin Cheng, Georgia Saylor, Jennifer E Van Eyk, Guoqiang Yu, Robert Clarke, David M Herrington, and Yue Wang · 2022
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Cosbin: cosine score-based iterative normalization of biologically diverse samples
Chiung-Ting Wu, Minjie Shen, Dongping Du, Zuolin Cheng, Sarah J Parker, Yingzhou Lu, Jennifer E Van Eyk, Guoqiang Yu, Robert Clarke, David M Herrington, et al · 2022
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Abds: tool suite for analyzing biologically diverse samples
Dongping Du, Saurabh Bhardwaj, Sarah J Parker, Zuolin Cheng, Zhen Zhang, Yingzhou Lu, Jennifer E Van Eyk, Guoqiang Yu, Robert Clarke, David M Herrington, et al · 2023
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Machine learning for synthetic data generation: a review
Yingzhou Lu, Huazheng Wang, and Wenqi Wei · 2023
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Scientific discovery in the age of artificial intelligence
Hanchen Wang, Tianfan Fu, Yuanqi Du, Wenhao Gao, Kexin Huang, Ziming Liu, et al · 2023
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