Annual Review of Biomedical Data Science最新文献

Data Science at the Interface of Air Pollution and Lung Health: Toward Precision Health. 空气污染与肺部健康界面的数据科学：走向精准健康。

IF 8.1

Annual Review of Biomedical Data Science Pub Date : 2026-08-01 Epub Date: 2026-04-21 DOI: 10.1146/annurev-biodatasci-092724-061536

Kenneth Ofori-Amanfo, Maya Dustin, Emilia L Lim

引用次数: 0

Beyond the Transcriptome: Leveraging Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) for Deeper Cellular Insights. 超越转录组：通过测序（CITE-seq）利用转录组和表位的细胞索引来获得更深入的细胞见解。

IF 8.1

Annual Review of Biomedical Data Science Pub Date : 2026-08-01 Epub Date: 2026-04-21 DOI: 10.1146/annurev-biodatasci-092724-061209

Marina L Fernández, Felipe A Gajardo Escobar, Marcela K Sjöberg-Herrera, Pablo A Romagnoli, Danilo G Ceschin

{"title":"Beyond the Transcriptome: Leveraging Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) for Deeper Cellular Insights.","authors":"Marina L Fernández, Felipe A Gajardo Escobar, Marcela K Sjöberg-Herrera, Pablo A Romagnoli, Danilo G Ceschin","doi":"10.1146/annurev-biodatasci-092724-061209","DOIUrl":"10.1146/annurev-biodatasci-092724-061209","url":null,"abstract":"The advent of single-cell genomics has revealed profound cellular heterogeneity, yet transcriptomic profiling alone often fails to show the functional proteomic state of a cell. Cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) emerged to bridge this critical gap, enabling the simultaneous quantification of RNA and surface protein expression within individual cells. This transformative technology leverages oligonucleotide-conjugated antibodies to assess protein abundance using a panel of marker-specific tags, which are cocaptured with cellular messenger RNA in single-cell sequencing workflows. This review details the methodological principles of CITE-seq, its compatibility with diverse sequencing platforms, and the computational frameworks required for integrated data analysis. We highlight its impact on cell biology, oncology, and infectious disease research, where it has refined cell classification, dissected tumor microenvironments, and decoded host-pathogen interactions. Finally, we discuss persistent technical and computational challenges and outline future directions, including spatial integration and predictive modeling, positioning CITE-seq as a cornerstone of next-generation biomedical discovery.","PeriodicalId":29775,"journal":{"name":"Annual Review of Biomedical Data Science","volume":" ","pages":"197-212"},"PeriodicalIF":8.1,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147783339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Artificial Intelligence in Image-Based Cardiovascular Disease Analysis. 基于图像的心血管疾病分析中的人工智能。

IF 8.1

Annual Review of Biomedical Data Science Pub Date : 2026-08-01 Epub Date: 2026-05-28 DOI: 10.1146/annurev-biodatasci-092624-111837

Xin Wang, Mingcheng Hu, Connie W Tsao, Hongtu Zhu

引用次数: 0

Exploring Genetic Variations Associated with the Immune Response in Underrepresented Populations. 在代表性不足的人群中探索与免疫反应相关的遗传变异。

IF 8.1

Annual Review of Biomedical Data Science Pub Date : 2026-08-01 Epub Date: 2026-05-26 DOI: 10.1146/annurev-biodatasci-092724-034109

Ana Laura Hernández-Ledesma, Evelia Lorena Coss-Navarrete, Grecia Sevilla-Parra, María Fernanda Bravo-García, Alejandra Schäfer, Marion E G Brunck, Alejandra Medina-Rivera

{"title":"Exploring Genetic Variations Associated with the Immune Response in Underrepresented Populations.","authors":"Ana Laura Hernández-Ledesma, Evelia Lorena Coss-Navarrete, Grecia Sevilla-Parra, María Fernanda Bravo-García, Alejandra Schäfer, Marion E G Brunck, Alejandra Medina-Rivera","doi":"10.1146/annurev-biodatasci-092724-034109","DOIUrl":"10.1146/annurev-biodatasci-092724-034109","url":null,"abstract":"The immune system protects the body through tightly coordinated innate and adaptive responses shaped largely by an individual's genetic background. Genetic variants associated with immune responses provide key pathways underlying disease susceptibility. Historically, the large majority of genomic studies have focused on European populations, potentially limiting our understanding of the relation between genetics and immune response in distinct ancestries. To assess this imbalance, we identified and characterized 206 studies from 370 recruitment sites worldwide that investigated immune-related traits in the GWAS Catalog. European cohorts dominated the data, with minimal representation from African, Latin American and Native American, Oceanian, and Asian ancestries. This imbalance limits discovery of ancestry-specific biology, reduces the accuracy of risk prediction outside Europe, and limits clinical translation. Expanding ancestry diversity in genomic research is essential to uncover the full spectrum of genetic architecture that shapes immune traits and diseases and to ensure that discoveries in immunogenomics benefit all populations on Earth.","PeriodicalId":29775,"journal":{"name":"Annual Review of Biomedical Data Science","volume":" ","pages":"501-522"},"PeriodicalIF":8.1,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148035734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Electronic Health Record-Linked Biobank Expansion Reveals Global Health Inequities. 电子健康记录相关生物库的扩张揭示了全球健康不平等。

IF 8.1

Annual Review of Biomedical Data Science Pub Date : 2026-08-01 Epub Date: 2026-03-09 DOI: 10.1146/annurev-biodatasci-092724-030452

Manuel Corpas, Oyesola Ojewunmi, Heinner Guio, Segun Fatumo

{"title":"Electronic Health Record-Linked Biobank Expansion Reveals Global Health Inequities.","authors":"Manuel Corpas, Oyesola Ojewunmi, Heinner Guio, Segun Fatumo","doi":"10.1146/annurev-biodatasci-092724-030452","DOIUrl":"10.1146/annurev-biodatasci-092724-030452","url":null,"abstract":"Electronic health record (EHR)-linked biobanks are transforming biomedical research, enabling population-scale studies that integrate genomic, clinical, and phenotypic data. Yet as these resources proliferate, it remains unclear how their research outputs reflect global health priorities. This article presents a comprehensive review of five globally established EHR-linked biobanks: UK Biobank, the Million Veteran Program, FinnGen, the All of Us Research Program, and the Estonian Biobank. Drawing on 14,142 peer-reviewed publications from 2000 to 2024, we show how each biobank displays a distinct thematic profile, shaped by institutional mandates, population focus, and methodological design. We further evaluate alignment with global disease burden by mapping biobank-linked publications to 25 high-priority disease areas using World Health Organization disability-adjusted life years data. Our burden-adjusted gap scores and opportunity indices reveal striking underrepresentation of conditions such as malaria, tuberculosis, and diarrheal diseases when comparing biobank research output against high-priority diseases.","PeriodicalId":29775,"journal":{"name":"Annual Review of Biomedical Data Science","volume":" ","pages":"27-46"},"PeriodicalIF":8.1,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147391363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Privacy and Security Throughout the Health Data Life Cycle: From Primary Care to Research Networks. 整个健康数据生命周期的隐私和安全：从初级保健到研究网络。

IF 8.1

Annual Review of Biomedical Data Science Pub Date : 2026-08-01 Epub Date: 2026-03-24 DOI: 10.1146/annurev-biodatasci-092724-031932

Bradley A Malin, Chao Yan, Luca Bonomi

{"title":"Privacy and Security Throughout the Health Data Life Cycle: From Primary Care to Research Networks.","authors":"Bradley A Malin, Chao Yan, Luca Bonomi","doi":"10.1146/annurev-biodatasci-092724-031932","DOIUrl":"10.1146/annurev-biodatasci-092724-031932","url":null,"abstract":"Health data are increasingly generated, shared, and analyzed across an ever-growing collection of settings. While these developments enable new forms of biomedical discovery and clinical decision support, they also introduce evolving privacy, security, and trust challenges that extend beyond traditional regulatory and technical frameworks. In this review, we characterize the various risks and protections throughout the health data life cycle, from data generation and primary use in healthcare to secondary use in research and artificial intelligence (AI) model development. We discuss how regulation, organizational practices, and technological choices shape data protection requirements, and we discuss and contextualize emerging threats, such as incidental disclosures through AI tools. We further review technical approaches for mitigating these risks, including access control and auditing, re-identification risk assessment and statistical mechanisms for risk mitigation (e.g., differential privacy), and synthetic data generation. We also consider how collaboration across disparate organizations may be achieved through federated learning mechanisms and cryptographic technologies, such as secure multiparty computation. Throughout, we highlight trade-offs between privacy protection and data utility, and we articulate practical challenges in deploying these methods at scale. We conclude by identifying open issues for the field, including the need for standardized metrics and greater transparency to support trust in data-driven healthcare and research.","PeriodicalId":29775,"journal":{"name":"Annual Review of Biomedical Data Science","volume":" ","pages":"47-67"},"PeriodicalIF":8.1,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147515337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Social Drivers of Health in the Electronic Health Record. 电子健康记录中健康的社会驱动因素。

IF 8.1

Annual Review of Biomedical Data Science Pub Date : 2026-08-01 Epub Date: 2026-05-28 DOI: 10.1146/annurev-biodatasci-092724-023921

Bradley Iott, Matthew Pantell, Julia Adler-Milstein

引用次数: 0

Modeling the Language of Codons with Artificial Intelligence. 用人工智能建模密码子语言。

IF 8.1

Annual Review of Biomedical Data Science Pub Date : 2026-08-01 Epub Date: 2026-05-26 DOI: 10.1146/annurev-biodatasci-092624-105741

Claudèle Lemay-St-Denis, Rachel Kolodny

引用次数: 0

Reclaiming Data, Restoring Health: The Indigenous Biomedical Data Science Renaissance. 回收数据，恢复健康：本土生物医学数据科学复兴。

IF 8.1

Annual Review of Biomedical Data Science Pub Date : 2026-08-01 Epub Date: 2026-05-28 DOI: 10.1146/annurev-biodatasci-092524-121351

Oliver J Bear Don't Walk Iv, Lauren W Yowelunh McLester-Davis, Dornell Pete, Danner Peter, Karina Hernandez-Hernandez, Alec J Calac, Valentín Q de la Sierra, Kelle Dhein, Kimiora Henare, Krystal S Tsosie

{"title":"Reclaiming Data, Restoring Health: The Indigenous Biomedical Data Science Renaissance.","authors":"Oliver J Bear Don't Walk Iv, Lauren W Yowelunh McLester-Davis, Dornell Pete, Danner Peter, Karina Hernandez-Hernandez, Alec J Calac, Valentín Q de la Sierra, Kelle Dhein, Kimiora Henare, Krystal S Tsosie","doi":"10.1146/annurev-biodatasci-092524-121351","DOIUrl":"10.1146/annurev-biodatasci-092524-121351","url":null,"abstract":"Indigenous Peoples are leading a renaissance in biomedical data science. Throughout this narrative review, we highlight advancements from leaders in this renaissance across four phases of biomedical data science: ethics and values that inform research, data harmonization, model development and assessment, and commercialization. In addition, we synthesize five teachings that advance biomedical data science: Indigenous sovereignty, ethical stewardship, relationality and trust, community prioritization, and Indigenous worldviews. We conclude with considerations for all biomedical data scientists, Indigenous People in biomedical data science, and Indigenous leaders leveraging biomedical data science to advance Indigenous health and well-being. This renaissance offers a road map for global biomedical systems to evolve beyond colonial legacies toward practices that uphold self-determination, restore balance, embody relationality, and promote the well-being of human and nonhuman kin.","PeriodicalId":29775,"journal":{"name":"Annual Review of Biomedical Data Science","volume":" ","pages":"523-553"},"PeriodicalIF":8.1,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13349450/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148057129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Genetic Modulators of Disease Penetrance. 疾病外显率的遗传调节因子。

IF 8.1

Annual Review of Biomedical Data Science Pub Date : 2026-08-01 Epub Date: 2026-04-16 DOI: 10.1146/annurev-biodatasci-103123-094547

Yunjun Kang, Theodore G Drivas

引用次数: 0