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Steve Goodison

Showing results (21-30 of 119) with videos related to

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Expert Review of Proteomics|October 9, 2009
Urinary proteomic profiling for diagnostic bladder cancer biomarkersSteve Goodison, Charles J Rosser, Virginia Urquidi
Oncoscience|May 20, 2020
Computational disease progression modeling can provide insights into cancer evolutionSteve Goodison, Mark E Sherman, Yijun Sun
Scientific Reports|July 8, 2017
Prognostic cancer gene signatures share common regulatory motifsYing Wang, Steve Goodison, Xiaoman 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.
BMC Genomics|September 25, 2003
The interrelationship between DRIM gene expression and cytogenetic and phenotypic characteristics in human breast tumor cell linesSteve Goodison, Carrie Viars, Maren Grazzini, 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.
Proteomics|September 8, 2004
Identification of metastasis-associated proteins in a human tumor metastasis model using the mass-mapping techniquePaweena Kreunin, Virginia Urquidi, David M Lubman, et al.
Genome Biology|August 27, 2014
Cancer progression modeling using static sample dataYijun Sun, Jin Yao, Norma J Nowak, et al.
Biomarkers in Medicine|February 18, 2010
Urine-based assays for the detection of bladder cancerPatrick Villicana, Bryant Whiting, Steve Goodison, et al.
Pageof 12

Showing results (21-30 of 119) with videos related to

Sort By:
Pageof 12
Expert Review of Proteomics|October 9, 2009
Urinary proteomic profiling for diagnostic bladder cancer biomarkersSteve Goodison, Charles J Rosser, Virginia Urquidi
Oncoscience|May 20, 2020
Computational disease progression modeling can provide insights into cancer evolutionSteve Goodison, Mark E Sherman, Yijun Sun
Scientific Reports|July 8, 2017
Prognostic cancer gene signatures share common regulatory motifsYing Wang, Steve Goodison, Xiaoman 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.
BMC Genomics|September 25, 2003
The interrelationship between DRIM gene expression and cytogenetic and phenotypic characteristics in human breast tumor cell linesSteve Goodison, Carrie Viars, Maren Grazzini, 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.
Proteomics|September 8, 2004
Identification of metastasis-associated proteins in a human tumor metastasis model using the mass-mapping techniquePaweena Kreunin, Virginia Urquidi, David M Lubman, et al.
Genome Biology|August 27, 2014
Cancer progression modeling using static sample dataYijun Sun, Jin Yao, Norma J Nowak, et al.
Biomarkers in Medicine|February 18, 2010
Urine-based assays for the detection of bladder cancerPatrick Villicana, Bryant Whiting, Steve Goodison, et al.
Pageof 12