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Eco-Evolutionary Drivers of Vibrio parahaemolyticus Sequence Type 3 Expansion: Retrospective Machine Learning Approach

Eco-Evolutionary Drivers of Vibrio parahaemolyticus Sequence Type 3 Expansion: Retrospective Machine Learning Approach

genomicsMicrobial genomics and metagenomics AI applications in genomics and pathology informatics, including ‘Generative AI’

Amy Marie Campbell, Chris Hauton, Ronny van Aerle, Jaime Martinez-Urtaza

JMIR Bioinform Biotech 2024;5:e62747

Exploring the Intersection of Schizophrenia, Machine Learning, and Genomics: Scoping Review

Exploring the Intersection of Schizophrenia, Machine Learning, and Genomics: Scoping Review

Considering the heterogenous nature of schizophrenia, several fields of research, such as genomics, also use the terminology psychotic disorder spectrum to refer to schizophrenia-like disorders [2]. Furthermore, while untreated, this mental health condition can lead to violence and violent offending [3]. A recent review of the literature estimated that schizophrenia has the highest societal cost among all mental health diseases.

Alexandre Hudon, Mélissa Beaudoin, Kingsada Phraxayavong, Stéphane Potvin, Alexandre Dumais

JMIR Bioinform Biotech 2024;5:e62752

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

Data were further filtered by querying the Genomics Data Commons via the Application Programming Interfaces specified [34]. We restricted the tissue type to be one of the primary tumors, solid tissue normal, or metastatic. We further restricted the data to micro RNA transcriptome profiling and picked data corresponding to 18 types of cancer each containing a sufficient number of samples, obtaining 9648 files (Figure 2 and Table S1 in Multimedia Appendix 1).

Ananya Raghu, Anisha Raghu, Jillian F Wise

JMIR Bioinform Biotech 2024;5:e56538

Research Trends and Evolution in Radiogenomics (2005-2023): Bibliometric Analysis

Research Trends and Evolution in Radiogenomics (2005-2023): Bibliometric Analysis

Radiogenomics is an emerging technology that combines radiomics and genomics, with the ultimate goal of improving prognosis and outcomes [1]. Radiogenomics can be used to investigate the relationship between imaging features and gene mutations and expression patterns [2-4].

Meng Wang, Yun Peng, Ya Wang, Dehong Luo

Interact J Med Res 2024;13:e51347

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

The scalability of genomics in the monitoring of infectious diseases has been highlighted by the COVID-19 pandemic. Here, genomics was not only used to diagnose infection at a population scale but also to identify and track novel variants. Specific genetic variants can produce molecules that behave in different ways. Some variants can completely disrupt the function of a gene, while others can change how efficiently it performs its role.

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

JMIR Bioinform Biotech 2024;5:e55632

Extending cBioPortal for Therapy Recommendation Documentation in Molecular Tumor Boards: Development and Usability Study

Extending cBioPortal for Therapy Recommendation Documentation in Molecular Tumor Boards: Development and Usability Study

Therapy recommendations are stored using Health Level Seven Fast Healthcare Interoperability Resources (FHIR) in compliance with the implementation guide “Genomics Reporting” and its German counterpart “Molekulargenetischer Befundbericht” by an FHIR-capable service running alongside c Bio Portal [11]. This enables interoperability with the hospital information system (HIS). The standard c Bio Portal data model is used for the storage of clinical and molecular patient data.

Christopher Renner, Niklas Reimer, Jan Christoph, Hauke Busch, Patrick Metzger, Melanie Boerries, Arsenij Ustjanzew, Dominik Boehm, Philipp Unberath

JMIR Med Inform 2023;11:e50017