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Bioinformatics Advances|November 17, 2022
Alignment-free comparison of metagenomics sequences via approximate string matchingJian Chen, Le Yang, Lu Li, et al.Briefings in Bioinformatics|December 31, 2024
A comprehensive benchmark study of methods for identifying significantly perturbed subnetworks in cancerLe Yang, Runpu Chen, Steve Goodison, et al.Bioinformatics (Oxford, England)|October 12, 2019
Deep-learning approach to identifying cancer subtypes using high-dimensional genomic dataRunpu Chen, Le Yang, Steve Goodison, et al.Nature Computational Science|June 22, 2023
An efficient and effective method to identify significantly perturbed subnetworks in cancerLe Yang, Runpu Chen, Steve Goodison, et al.Cancers|August 26, 2023
Identifying Significantly Perturbed Subnetworks in Cancer Using Multiple Protein-Protein Interaction NetworksLe Yang, Runpu Chen, Thomas Melendy, et al.The Prostate|April 4, 2009
Optimizing molecular signatures for predicting prostate cancer recurrenceYijun Sun, Steve GoodisonCancer Research Communications|September 30, 2024
Prostate Cancer Progression Modeling Provides Insight into Dynamic Molecular Changes Associated with Progressive Disease StatesRunpu Chen, Li Tang, Thomas Melendy, et al.Cancer Research|November 21, 2019
Molecular Profiles of Matched Primary and Metastatic Tumor Samples Support a Linear Evolutionary Model of Breast CancerRunpu Chen, Steve Goodison, Yijun SunBioanalysis|November 19, 2010
Derivation of cancer diagnostic and prognostic signatures from gene expression dataSteve Goodison, Yijun Sun, Virginia UrquidiBreast Cancer Research and Treatment|March 18, 2009
Derivation of molecular signatures for breast cancer recurrence prediction using a two-way validation approachYijun Sun, Virginia Urquidi, Steve GoodisonPageof 1,245