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http://dx.doi.org/10.21037/jtd.2017.01.35 | DOI Listing |
Genome Biol
September 2025
Department of Clinical Pharmacy, Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, 90089, USA.
Background: Recent advances in high-throughput sequencing technologies have enabled the collection and sharing of a massive amount of omics data, along with its associated metadata-descriptive information that contextualizes the data, including phenotypic traits and experimental design. Enhancing metadata availability is critical to ensure data reusability and reproducibility and to facilitate novel biomedical discoveries through effective data reuse. Yet, incomplete metadata accompanying public omics data may hinder reproducibility and reusability and limit secondary analyses.
View Article and Find Full Text PDFNat Aging
September 2025
Aging Biomarker Consortium (ABC), Beijing, China.
The global surge in the population of people 60 years and older, including that in China, challenges healthcare systems with rising age-related diseases. To address this demographic change, the Aging Biomarker Consortium (ABC) has launched the X-Age Project to develop a comprehensive aging evaluation system tailored to the Chinese population. Our goal is to identify robust biomarkers and construct composite aging clocks that capture biological age, defined as an individual's physiological and molecular state, across diverse Chinese cohorts.
View Article and Find Full Text PDFMed Eng Phys
October 2025
Department of Bioengineering, Technological University of Havana "José Antonio Echeverría", Cuba.
Congenital hearing loss is a significant health problem, with a worldwide incidence of >6 per 1000 live births. Late diagnosis will delay appropriate treatment, leading to potential neurodevelopment problems. Early diagnosis requires neonatal hearing screening, where one of the most used techniques is automated Auditory Brainstem Responses (aABR).
View Article and Find Full Text PDFCell Syst
September 2025
Ray and Stephanie Lane Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA, USA. Electronic address:
Identifying cell types in highly multiplexed images is essential for understanding tissue spatial organization. Current cell-type annotation methods often rely on extensive reference images and manual adjustments. In this work, we present a tool, the Robust Image-Based Cell Annotator (RIBCA), that enables accurate, automated, unbiased, and fine-grained cell-type annotation for images with a wide range of antibody panels without requiring additional model training or human intervention.
View Article and Find Full Text PDFCell Rep Methods
August 2025
Department of Biomedical Engineering and Computational Biology Program, OHSU, Portland, OR, USA; Knight Cancer Institute, OHSU, Portland, OR, USA. Electronic address:
We present UniFORM, a non-parametric, Python-based pipeline for normalizing multiplex tissue imaging (MTI) data at both the feature and pixel levels. UniFORM employs an automated rigid landmark registration method tailored to the distributional characteristics of MTI, with UniFORM operating without prior distributional assumptions and handling both unimodal and bimodal patterns. By aligning the biologically invariant negative populations, UniFORM removes technical variation while preserving tissue-specific expression patterns in positive populations.
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