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Identifying Safeguards Disabled by Epstein-Barr Virus Infections in Genomes From Patients With Breast Cancer: Chromosomal Bioinformatics Analysis

Identifying Safeguards Disabled by Epstein-Barr Virus Infections in Genomes From Patients With Breast Cancer: Chromosomal Bioinformatics Analysis

Some genomic similarities between these EBV-associated cancers and breast cancer can be derived from the literature. In NPC, 100% of malignant cells are EBV positive [10]. Over 64% of NPCs are deficient in a pathway that depends on the breast cancer susceptibility genes BRCA1 and BRCA2 [11], which accurately repair DNA crosslinks and breaks via the homologous recombination pathway.

Bernard Friedenson

JMIRx Med 2025;6:e50712

Updated Surveillance Metrics and History of the COVID-19 Pandemic (2020-2023) in Canada: Longitudinal Trend Analysis

Updated Surveillance Metrics and History of the COVID-19 Pandemic (2020-2023) in Canada: Longitudinal Trend Analysis

Next, we used dynamic and genomic surveillance methods to construct a historical narrative of the pandemic within the country. This analysis incorporated the ratio of COVID-19 deaths to the number of transmissions as an indicator of population-level mortality risk from infection. In addition, we integrated historical genomic surveillance data from sequenced viral specimens to trace the emergence and spread of variants of concern within the country.

Scott A Wu, Alan G Soetikno, Egon A Ozer, Sarah B Welch, Yingxuan Liu, Robert J Havey, Robert L Murphy, Claudia Hawkins, Maryann Mason, Lori A Post, Chad J Achenbach, Alexander L Lundberg

JMIR Public Health Surveill 2024;10:e53218

Deep Learning–Based Identification of Tissue of Origin for Carcinomas of Unknown Primary Using MicroRNA Expression: Algorithm Development and Validation

Deep Learning–Based Identification of Tissue of Origin for Carcinomas of Unknown Primary Using MicroRNA Expression: Algorithm Development and Validation

Reference 34: NCI Genomic Data Commons(https://gdc.cancer.gov/developers/gdc-application-programming-interface-apigenomicTheme Issue 2024: Machine Learning-Based Predictive Models Using Genomic Data Cancer genomic data analysis

Ananya Raghu, Anisha Raghu, Jillian F Wise

JMIR Bioinform Biotech 2024;5:e56538

It Is in Our DNA: Bringing Electronic Health Records and Genomic Data Together for Precision Medicine

It Is in Our DNA: Bringing Electronic Health Records and Genomic Data Together for Precision Medicine

While genomic analyses would appear to be a prime candidate for the development of specialized CDSSs to support the use of genomic practice across a range of different areas of health (Table 1), CDSSs that routinely incorporate genetic information are rare [33,34]. There are likely many causes to this deficit; however, a significant factor to this can be attributed to the availability of interoperable genomic data within EHR.

Alan J Robertson, Andrew J Mallett, Zornitza Stark, Clair Sullivan

JMIR Bioinform Biotech 2024;5:e55632

Updated Surveillance Metrics and History of the COVID-19 Pandemic (2020-2023) in Latin America and the Caribbean: Longitudinal Trend Analysis

Updated Surveillance Metrics and History of the COVID-19 Pandemic (2020-2023) in Latin America and the Caribbean: Longitudinal Trend Analysis

Second, we used dynamic and genomic surveillance methods to describe the history of the pandemic in the region and situate the time window around the WHO declaration within the broader history. We included the ratio of COVID-19 deaths to the number of transmissions as a proxy for the mortality risk from infection at the population level. We also included a historical record of genomic surveillance from sequenced viral specimens to identify the appearance and spread of VOCs in the region.

Lori Ann Post, Scott A Wu, Alan G Soetikno, Egon A Ozer, Yingxuan Liu, Sarah B Welch, Claudia Hawkins, Charles B Moss, Robert L Murphy, Maryann Mason, Robert J Havey, Alexander L Lundberg

JMIR Public Health Surveill 2024;10:e44398