Anne Cambon‐Thomsen
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View article: Emerging and evolving values in the changing landscape of genomics
Emerging and evolving values in the changing landscape of genomics Open
Recent advances in human genomics have transformed the field, leading to increased integration of genomics into mainstream clinical care, broadening the potential of personalized medicine, and expanding data generation and sharing. From th…
View article: Recommendations on Open Science Rewards and Incentives
Recommendations on Open Science Rewards and Incentives Open
Open Science contributes to the collective building of scientific knowledge and societal progress. However, academic research currently fails to recognise and reward efforts to share research outputs. Yet it is crucial that such activities…
View article: Gaps between Open Science activities and actual recognition systems: Insights from an international survey
Gaps between Open Science activities and actual recognition systems: Insights from an international survey Open
There are global movements aiming to promote reform of the traditional research evaluation and reward systems. However, a comprehensive picture of the existing best practices and efforts across various institutions to integrate Open Scienc…
View article: Bioethics “Laws”: Paradox or Way of the Future?
Bioethics “Laws”: Paradox or Way of the Future? Open
International audience
View article: Gaps between Open Science activities and actual recognition systems: Insights from an international survey
Gaps between Open Science activities and actual recognition systems: Insights from an international survey Open
There are global movements aiming to promote reform of the traditional research evaluation and reward systems. However, a comprehensive picture of the existing best practices and efforts across various institutions to integrate Open Scienc…
View article: Supplementary Table S2 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma
Supplementary Table S2 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma Open
Somatic mutations detected in 12 interrogated genes for cohorts C1-C3
View article: Supplementary Table S2 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma
Supplementary Table S2 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma Open
Somatic mutations detected in 12 interrogated genes for cohorts C1-C3
View article: Supplementary Tables S3-S13 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma
Supplementary Tables S3-S13 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma Open
Supplementary Tables S3-S13
View article: Supplementary Methods S1 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma
Supplementary Methods S1 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma Open
Supplementary Methods
View article: Supplementary Tables S3-S13 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma
Supplementary Tables S3-S13 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma Open
Supplementary Tables S3-S13
View article: Data from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma
Data from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma Open
Purpose:Patients with resected localized clear-cell renal cell carcinoma (ccRCC) remain at variable risk of recurrence. Incorporation of biomarkers may refine risk prediction and inform adjuvant treatment decisions. We explored the role of…
View article: Supplementary Table S1 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma
Supplementary Table S1 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma Open
Clinical information and 12 gene mutation status for cohorts C1-C3
View article: Figure S1 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma
Figure S1 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma Open
Disease-Free Survival outcomes amongst genomic groups when applied to the 247 VHL mutated ccRCCs from the TCGA dataset
View article: Supplementary Table S1 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma
Supplementary Table S1 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma Open
Clinical information and 12 gene mutation status for cohorts C1-C3
View article: Figure S3 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma
Figure S3 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma Open
DFS by tumor stage stratified by genomic classifier
View article: Figure S3 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma
Figure S3 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma Open
DFS by tumor stage stratified by genomic classifier
View article: Figure S2 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma
Figure S2 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma Open
DFS amongst Leibovich risk groups stratified by genomic classifier
View article: Figure S2 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma
Figure S2 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma Open
DFS amongst Leibovich risk groups stratified by genomic classifier
View article: Supplementary Methods S1 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma
Supplementary Methods S1 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma Open
Supplementary Methods
View article: Figure S1 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma
Figure S1 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma Open
Disease-Free Survival outcomes amongst genomic groups when applied to the 247 VHL mutated ccRCCs from the TCGA dataset
View article: Data from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma
Data from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma Open
Purpose:Patients with resected localized clear-cell renal cell carcinoma (ccRCC) remain at variable risk of recurrence. Incorporation of biomarkers may refine risk prediction and inform adjuvant treatment decisions. We explored the role of…
View article: Supplementary Table S1 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma
Supplementary Table S1 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma Open
Clinical information and 12 gene mutation status for cohorts C1-C3
View article: Figure S3 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma
Figure S3 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma Open
DFS by tumor stage stratified by genomic classifier
View article: Figure S2 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma
Figure S2 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma Open
DFS amongst Leibovich risk groups stratified by genomic classifier
View article: Figure S1 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma
Figure S1 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma Open
Disease-Free Survival outcomes amongst genomic groups when applied to the 247 VHL mutated ccRCCs from the TCGA dataset
View article: Supplementary Methods S1 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma
Supplementary Methods S1 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma Open
Supplementary Methods
View article: Supplementary Tables S3-S13 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma
Supplementary Tables S3-S13 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma Open
Supplementary Tables S3-S13
View article: Figure S1 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma
Figure S1 from Application of Genomic Sequencing to Refine Patient Stratification for Adjuvant Therapy in Renal Cell Carcinoma Open
Disease-Free Survival outcomes amongst genomic groups when applied to the 247 VHL mutated ccRCCs from the TCGA dataset