Multi-Omics Profiling in a Symptomatic Cohort Identifies Coordinated Biomarker Signatures in Ovarian Cancer Serum
Rachel Culp‐Hill, Charles M. Nichols, Shannon Kilkenny, Mattie Goldberg et autres
0 citationsDiagnostics
Rachel Culp‐Hill
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150Publications signalées
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Acute Myeloid Leukemia ResearchMetabolomics and Mass Spectrometry StudiesImmune cells in cancerAdvanced Proteomics Techniques and ApplicationsTryptophan and brain disorders
Publications récentes
A novel serum-based multi-omic machine learning model improves early detection of ovarian cancer in the symptomatic population
Anna Jeter, Rachel Culp‐Hill, Brendan M. Giles, Robert Law et autres
0 citationsGynecologic Oncology
Glutaredoxin 2 is essential for AML survival through mitochondrial permeability transition pore regulation
Tianyi Ling, Cristiana O’Brien, Jonathan St-Germain, Vincent Rondeau et autres
3 citationsBlood
Abstract B019: Serum-based multi-omic signatures of ovarian cancer in women with vague abdominal symptoms: analysis of two independent cohorts
Rachel Culp‐Hill, Brendan M. Giles, Charles M. Nichols, Robert Adger Law et autres
0 citationsCancer Research
Supplemental Figure 6 from Utilizing Serum-Derived Lipidomics with Protein Biomarkers and Machine Learning for Early Detection of Ovarian Cancer in the Symptomatic Population
Brendan M. Giles, Rachel Culp‐Hill, Robert Adger Law, Charles M. Nichols et autres
0 citations
Supplemental Figure 3 from Utilizing Serum-Derived Lipidomics with Protein Biomarkers and Machine Learning for Early Detection of Ovarian Cancer in the Symptomatic Population
Brendan M. Giles, Rachel Culp‐Hill, Robert Adger Law, Charles M. Nichols et autres
0 citations
Supplemental Figure 7 from Utilizing Serum-Derived Lipidomics with Protein Biomarkers and Machine Learning for Early Detection of Ovarian Cancer in the Symptomatic Population
Brendan M. Giles, Rachel Culp‐Hill, Robert Adger Law, Charles M. Nichols et autres
0 citations
Figure 2 from Utilizing Serum-Derived Lipidomics with Protein Biomarkers and Machine Learning for Early Detection of Ovarian Cancer in the Symptomatic Population
Brendan M. Giles, Rachel Culp‐Hill, Robert Adger Law, Charles M. Nichols et autres
0 citations
Supplemental Table 1 from Utilizing Serum-Derived Lipidomics with Protein Biomarkers and Machine Learning for Early Detection of Ovarian Cancer in the Symptomatic Population
Brendan M. Giles, Rachel Culp‐Hill, Robert Adger Law, Charles M. Nichols et autres
0 citations
Supplemental Table 2 from Utilizing Serum-Derived Lipidomics with Protein Biomarkers and Machine Learning for Early Detection of Ovarian Cancer in the Symptomatic Population
Brendan M. Giles, Rachel Culp‐Hill, Robert Adger Law, Charles M. Nichols et autres
0 citations
Table 1 from Utilizing Serum-Derived Lipidomics with Protein Biomarkers and Machine Learning for Early Detection of Ovarian Cancer in the Symptomatic Population
Brendan M. Giles, Rachel Culp‐Hill, Robert Adger Law, Charles M. Nichols et autres
0 citations
Supplemental Table 3 from Utilizing Serum-Derived Lipidomics with Protein Biomarkers and Machine Learning for Early Detection of Ovarian Cancer in the Symptomatic Population
Brendan M. Giles, Rachel Culp‐Hill, Robert Adger Law, Charles M. Nichols et autres
0 citations
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