Genomics, proteomics & bioinformatics最新文献_第8页

Integrated Computational and Functional Screening Identifies G9a Inhibitors for SETD2-mutant Leukemia. 综合计算和功能筛选确定setd2突变白血病的G9a抑制剂。

IF 7.9

Genomics, proteomics & bioinformatics Pub Date : 2025-05-30 DOI: 10.1093/gpbjnl/qzaf035

Ya Zhang, Mengfang Xia, Zhenyi Yi, Pinpin Sui, Xudong He, Liping Wang, Qiyi Chen, Hong-Hu Zhu, Gang Huang, Qian-Fei Wang

{"title":"Integrated Computational and Functional Screening Identifies G9a Inhibitors for SETD2-mutant Leukemia.","authors":"Ya Zhang, Mengfang Xia, Zhenyi Yi, Pinpin Sui, Xudong He, Liping Wang, Qiyi Chen, Hong-Hu Zhu, Gang Huang, Qian-Fei Wang","doi":"10.1093/gpbjnl/qzaf035","DOIUrl":"10.1093/gpbjnl/qzaf035","url":null,"abstract":"SETD2, a frequently mutated epigenetic tumor suppressor gene in acute leukemia, is associated with chemotherapy resistance and poor patient outcomes. To explore potential therapeutics for SETD2-mutant leukemia, we employed an integrated approach combining computational prediction with epigenetic compound library screening. This approach identified G9a inhibitors as promising candidates, capable of reversing gene expression signatures associated with Setd2 deficiency and selectively inhibiting SETD2-deficient cells. RNA sequencing analysis revealed that the G9a inhibitor significantly downregulated Myc and Myc-regulated genes involved in translation, DNA replication, and G1/S transition in Setd2-mutant cells. Further chromatin immunoprecipitation sequencing analysis showed that G9a inhibition reduced H3K9me2 levels at the long non-coding RNA Mir100hg locus, coinciding with specific upregulation of the embedded microRNA let-7a-2 in Setd2-mutant cells. Given the established role of let-7a in MYC suppression, these findings suggest a potential mechanism by which G9a inhibitors induce MYC downregulation in SETD2-mutant leukemia. Additionally, correlation analysis between computational predictions and phenotypic outcomes highlighted the MYC signature as a key predictor of drug efficacy. Collectively, our study identifies G9a inhibitors as a promising therapeutic avenue for SETD2-mutant leukemia and provides novel insights into refining drug prediction strategies.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":7.9,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12373973/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144039579","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

Unveiling Neonatal Pneumonia Microbiome by High-Throughput Sequencing and Droplet Culturomics. 通过高通量测序和液滴培养揭示新生儿肺炎微生物组。

Genomics, proteomics & bioinformatics Pub Date : 2025-05-29 DOI: 10.1093/gpbjnl/qzaf047

Zerui Wang, Xin Cheng, Yibin Xu, Zhiyi Wang, Liyan Ma, Caiming Li, Shize Jiang, Yuchen Li, Shuilong Guo, Wenbin Du

{"title":"Unveiling Neonatal Pneumonia Microbiome by High-Throughput Sequencing and Droplet Culturomics.","authors":"Zerui Wang, Xin Cheng, Yibin Xu, Zhiyi Wang, Liyan Ma, Caiming Li, Shize Jiang, Yuchen Li, Shuilong Guo, Wenbin Du","doi":"10.1093/gpbjnl/qzaf047","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzaf047","url":null,"abstract":"Neonatal pneumonia is a leading cause of infant mortality worldwide; however, a lack of microbial profiling, especially of low-abundance species, makes accurate diagnosis challenging. Traditional methods can fail to capture the complexity of the neonatal respiratory microbiota, thereby obscuring its role in disease progression. We describe a novel approach that combines high-throughput sequencing with droplet-based microfluidic cultivation to investigate microbiome shifts in neonates with pneumonia. Using 16S ribosomal RNA (rRNA) gene sequencing of 71 pneumonia cases and 49 controls, we identified 1009 genera, including 930 low-abundance taxa, which showed significant compositional differences between groups. Linear Discriminant Analysis Effect Size analysis identified key pneumonia-associated genera, such as Streptococcus, Rothia, and Corynebacterium. Droplet-based cultivation recovered 299 strains from 94 taxa, including rare species and ESKAPE pathogens, thereby supporting targeted antimicrobial management. Host-pathogen interaction assays showed that Rothia and Corynebacterium induced inflammation in lung epithelial cells, likely via dysregulation of the PI3K-Akt pathway. Integrating these marker taxa with clinical factors, such as gestational age and delivery type, offers the potential for precise diagnosis and treatment. The recovery of diverse species can support the construction of a biobank of neonatal respiratory microbiota to advance mechanistic studies and therapeutic strategies.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144176288","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

GDBIG: A Pioneering Birth Cohort Genomic Platform Facilitating Intergenerational Genetic Research. GDBIG：促进代际遗传研究的开创性出生队列基因组平台。

Genomics, proteomics & bioinformatics Pub Date : 2025-05-15 DOI: 10.1093/gpbjnl/qzaf045

Shujia Huang, Chengrui Wang, Mingxi Huang, Jinhua Lu, Jian-Rong He, Shanshan Lin, Siyang Liu, Huimin Xia, Xiu Qiu

{"title":"GDBIG: A Pioneering Birth Cohort Genomic Platform Facilitating Intergenerational Genetic Research.","authors":"Shujia Huang, Chengrui Wang, Mingxi Huang, Jinhua Lu, Jian-Rong He, Shanshan Lin, Siyang Liu, Huimin Xia, Xiu Qiu","doi":"10.1093/gpbjnl/qzaf045","DOIUrl":"https://doi.org/10.1093/gpbjnl/qzaf045","url":null,"abstract":"High-quality genome databases derived from large-scale, family-based birth cohorts are vital resources for investigating the genetic determinants of early-life traits and the impact of early-life environments on the health of both parents and offspring. Here, we established the genomic platform of the Born in Guangzhou Cohort Study (BIGCS), named the Genome Database of BIGCS (GDBIG), which represents the first birth cohort-based genomic database in China and is designed to facilitate intergenerational genetic research. Based on the phase I results of the BIGCS, GDBIG includes low-coverage (∼ 6.63×) whole genome sequencing (WGS) data and extensive pregnancy phenotypes from 4053 Chinese participants. These participants are from 30 of China's 34 administrative divisions, encompassing Han and 12 minority ethnic groups. Currently, GDBIG provides a range of services, including allele frequency queries for 56.23 million variants across two generations, a genotype imputation server featuring a high-quality family-based reference panel, and a genome-wide association study (GWAS) meta-analysis interface for various maternal and infant phenotypes. The GDBIG database addresses the lack of Asian birth cohort-based genomic resources and provides a valuable platform for conducting genetic analysis, accessible online or via application programming interfaces (API) at http://gdbig.bigcs.com.cn/.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144083031","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

PIGOME: An Integrated and Comprehensive Multi-omics Database for Pig Functional Genomics Studies. PIGOME：猪功能基因组学研究的综合多组学数据库。

Genomics, proteomics & bioinformatics Pub Date : 2025-05-10 DOI: 10.1093/gpbjnl/qzaf016

Guohao Han 韩郭皓, Peng Yang 杨朋, Yongjin Zhang 张永进, Qiaowei Li 李巧伟, Xinhao Fan 范新浩, Ruipu Chen 陈锐朴, Chao Yan 闫超, Mu Zeng 曾木, Yalan Yang 杨亚岚, Zhonglin Tang 唐中林

{"title":"PIGOME: An Integrated and Comprehensive Multi-omics Database for Pig Functional Genomics Studies.","authors":"Guohao Han 韩郭皓, Peng Yang 杨朋, Yongjin Zhang 张永进, Qiaowei Li 李巧伟, Xinhao Fan 范新浩, Ruipu Chen 陈锐朴, Chao Yan 闫超, Mu Zeng 曾木, Yalan Yang 杨亚岚, Zhonglin Tang 唐中林","doi":"10.1093/gpbjnl/qzaf016","DOIUrl":"10.1093/gpbjnl/qzaf016","url":null,"abstract":"In addition to being a major source of animal protein, pigs are an important model for studying development and diseases in humans. Over the past two decades, thousands of high-throughput sequencing studies in pigs have been performed using a variety of tissues from different breeds and developmental stages. However, multi-omics databases specifically designed for pig functional genomics research are still limited. Here, we present PIGOME, a user-friendly database of pig multi-omes. PIGOME currently contains seven types of pig omics datasets, including whole-genome sequencing (WGS), RNA sequencing (RNA-seq), microRNA sequencing (miRNA-seq), chromatin immunoprecipitation sequencing (ChIP-seq), assay for transposase-accessible chromatin sequencing (ATAC-seq), bisulfite sequencing (BS-seq), and methylated RNA immunoprecipitation sequencing (MeRIP-seq), from 6901 samples and 392 projects with manually curated metadata, integrated gene annotation, and quantitative trait locus information. Furthermore, various \"Explore\" and \"Browse\" functions have been established to provide user-friendly access to omics information. PIGOME implements several tools to visualize genomic variants, gene expression, and epigenetic signals of a given gene in the pig genome, enabling efficient exploration of spatiotemporal gene expression/epigenetic patterns, functions, regulatory mechanisms, and associated economic traits. Collectively, PIGOME provides valuable resources for pig breeding and is helpful for human biomedical research. PIGOME is available at https://pigome.com.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12122082/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560323","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

NSUN2-mediated HCV RNA m5C Methylation Facilitates Viral RNA Stability and Replication. nsun2介导的HCV RNA m5C甲基化促进病毒RNA的稳定性和复制。

Genomics, proteomics & bioinformatics Pub Date : 2025-05-10 DOI: 10.1093/gpbjnl/qzaf008

Zhu-Li Li, Yan Xie, Yafen Wang, Jing Wang, Xiang Zhou, Xiao-Lian Zhang

{"title":"NSUN2-mediated HCV RNA m5C Methylation Facilitates Viral RNA Stability and Replication.","authors":"Zhu-Li Li, Yan Xie, Yafen Wang, Jing Wang, Xiang Zhou, Xiao-Lian Zhang","doi":"10.1093/gpbjnl/qzaf008","DOIUrl":"10.1093/gpbjnl/qzaf008","url":null,"abstract":"RNA modifications have emerged as new efficient targets against viruses. However, little is known about 5-methylcytosine (m5C) modification in the genomes of flaviviruses. Herein, we demonstrate that hepatitis C virus (HCV), dengue virus, and Zika virus exhibit high levels of viral RNA m5C modification. We identified an m5C site at C7525 in the NS5A gene of the HCV RNA genome. HCV infection upregulates the expression of the host m5C methyltransferase NSUN2 via the transcription factor E2F1. NSUN2 deficiency decreases HCV RNA m5C methylation levels, which further reduces viral RNA stability, replication, and viral assembly and budding. A C7525-specific m5C-abrogating mutation in the HCV RNA genome similarly reduces viral replication, assembly, and budding by decreasing viral RNA stability. Notably, NSUN2 deficiency also reduces host global messenger RNA (mRNA) m5C levels during HCV infection, which upregulates the expression of antiviral innate immune response genes and further suppresses HCV RNA replication. Supported by both cellular and mouse infection models, our findings reveal that NSUN2-mediated m5C methylation of HCV RNA and host mRNAs facilitates viral RNA replication. HCV infection promotes host NSUN2 expression to facilitate HCV replication, suggesting a positive feedback loop. NSUN2 could be a potential therapeutic target for flavivirus therapeutics.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12233092/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143434801","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

A Single-cell Atlas of Developing Mouse Palates Reveals Cellular and Molecular Transitions in Periderm Cell Fate. 发育中的小鼠上颚单细胞图谱揭示了外周细胞命运的细胞和分子转变。

Genomics, proteomics & bioinformatics Pub Date : 2025-05-10 DOI: 10.1093/gpbjnl/qzaf013

Wenbin Huang 黄文斌, Zhenwei Qian 钱振伟, Jieni Zhang 张杰铌, Yi Ding 丁毅, Bin Wang 王斌, Jiuxiang Lin 林久祥, Xiannian Zhang 张先念, Huaxiang Zhao 赵华翔, Feng Chen 陈峰

{"title":"A Single-cell Atlas of Developing Mouse Palates Reveals Cellular and Molecular Transitions in Periderm Cell Fate.","authors":"Wenbin Huang 黄文斌, Zhenwei Qian 钱振伟, Jieni Zhang 张杰铌, Yi Ding 丁毅, Bin Wang 王斌, Jiuxiang Lin 林久祥, Xiannian Zhang 张先念, Huaxiang Zhao 赵华翔, Feng Chen 陈峰","doi":"10.1093/gpbjnl/qzaf013","DOIUrl":"10.1093/gpbjnl/qzaf013","url":null,"abstract":"Cleft palate is one of the most common congenital craniofacial disorders that affects children's appearance and oral functions. Investigating the transcriptomes during palatogenesis is crucial for understanding the etiology of this disorder and facilitating prenatal molecular diagnosis. However, there is limited knowledge about the single-cell differentiation dynamics during mid-palatogenesis and late-palatogenesis, specifically regarding the subpopulations and developmental trajectories of periderm, a rare but critical cell population. Here, we explored the single-cell landscape of mouse developing palates from embryonic day (E) 10.5 to E16.5. We systematically depicted the single-cell transcriptomes of mesenchymal and epithelial cells during palatogenesis, including subpopulations and differentiation dynamics. Additionally, we identified four subclusters of palatal periderm and constructed two distinct trajectories of cell fates for periderm cells. Our findings reveal that claudin-family coding genes and Arhgap29 play a role in the non-stick function of the periderm before the palatal shelves contact, and Pitx2 mediates the adhesion of periderm during the contact of opposing palatal shelves. Furthermore, we demonstrate that epithelial-mesenchymal transition (EMT), apoptosis, and migration collectively contribute to the degeneration of periderm cells in the medial epithelial seam. Taken together, our study suggests a novel model of periderm development during palatogenesis and delineates the cellular and molecular transitions in periderm cell determination.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12240470/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560327","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

Mass Spectrometry-based Solutions for Single-cell Proteomics. 基于 MS 的单细胞蛋白质组学解决方案。

Genomics, proteomics & bioinformatics Pub Date : 2025-05-10 DOI: 10.1093/gpbjnl/qzaf012

Siqi Li, Shuwei Li, Siqi Liu, Yan Ren

引用次数: 0

Long and Accurate: How HiFi Sequencing is Transforming Genomics. 长而准确：高保真测序如何改变基因组学。

Genomics, proteomics & bioinformatics Pub Date : 2025-05-10 DOI: 10.1093/gpbjnl/qzaf003

Bo Wang 王博, Peng Jia 贾鹏, Shenghan Gao 高胜寒, Huanhuan Zhao 赵焕焕, Gaoyang Zheng 郑高洋, Linfeng Xu 许林峰, Kai Ye 叶凯

{"title":"Long and Accurate: How HiFi Sequencing is Transforming Genomics.","authors":"Bo Wang 王博, Peng Jia 贾鹏, Shenghan Gao 高胜寒, Huanhuan Zhao 赵焕焕, Gaoyang Zheng 郑高洋, Linfeng Xu 许林峰, Kai Ye 叶凯","doi":"10.1093/gpbjnl/qzaf003","DOIUrl":"10.1093/gpbjnl/qzaf003","url":null,"abstract":"Recent developments in PacBio high-fidelity (HiFi) sequencing technologies have transformed genomic research, with circular consensus sequencing now achieving 99.9% accuracy for long (up to 25 kb) single-molecule reads. This method circumvents biases intrinsic to amplification-based approaches, enabling thorough analysis of complex genomic regions [including tandem repeats, segmental duplications, ribosomal DNA (rDNA) arrays, and centromeres] as well as direct detection of base modifications, furnishing both sequence and epigenetic data concurrently. This has streamlined a number of tasks including genome assembly, variant detection, and full-length transcript analysis. This review provides a comprehensive overview of the applications and challenges of HiFi sequencing across various fields, including genomics, transcriptomics, and epigenetics. By delineating the evolving landscape of HiFi sequencing in multi-omics research, we highlight its potential to deepen our understanding of genetic mechanisms and to advance precision medicine.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12257948/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143371457","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

Living on the Rocks: Genomic Analysis of Limestone Langurs Provides Novel Insights into the Adaptive Evolution in Extreme Karst Environments. 生活在岩石上：石灰岩叶猴的基因组分析为极端喀斯特环境下的适应性进化提供了新的见解。

Genomics, proteomics & bioinformatics Pub Date : 2025-05-10 DOI: 10.1093/gpbjnl/qzaf007

Zhijin Liu, Xiongfei Zhang, Peipei Wang, Minheng Hong, Xiaochan Yan, Xiaoqiu Qi, Qian Zhao, Zhenghao Chen, Huajian Nie, Hui Li, Ziwen Li, Liye Zhang, Jiwei Qi, Chaolei He, Nguyen Van Truong, Minh D Le, Tilo Nadler, Hiroo Imai, Christian Roos, Ming Li

{"title":"Living on the Rocks: Genomic Analysis of Limestone Langurs Provides Novel Insights into the Adaptive Evolution in Extreme Karst Environments.","authors":"Zhijin Liu, Xiongfei Zhang, Peipei Wang, Minheng Hong, Xiaochan Yan, Xiaoqiu Qi, Qian Zhao, Zhenghao Chen, Huajian Nie, Hui Li, Ziwen Li, Liye Zhang, Jiwei Qi, Chaolei He, Nguyen Van Truong, Minh D Le, Tilo Nadler, Hiroo Imai, Christian Roos, Ming Li","doi":"10.1093/gpbjnl/qzaf007","DOIUrl":"10.1093/gpbjnl/qzaf007","url":null,"abstract":"Understanding how organisms adapt to their environments is a central question in evolutionary biology. Limestone langurs are unique among primates, as they are exclusively found in karst limestone habitats and have evolved mechanisms to tolerate high levels of mineral ions, which are typically associated with metal toxicity affecting organs, cells, and genetic material. We generated a high-quality reference genome (Tfra_5.0) for the limestone langur (Trachypithecus francoisi), along with genome resequencing data for 48 langurs representing 15 Trachypithecus species. Genes encoding ion channels (e.g., Na+, K+, and Ca2+) exhibited significantly accelerated evolution in limestone langurs. Limestone langur-specific mutations in Na+ and Ca2+ channels were experimentally confirmed to modify inward ion currents in vitro. Unexpectedly, scans for positive selection also identified genes involved in DNA damage response/repair pathways, a previously unknown adaptation. This finding highlights an evolutionary adaptation in limestone langurs that mitigates the increased risk of DNA damage posed by elevated metal ion concentrations. Notably, a limestone langur-specific mutation (E94D) of the melanocortin 1 receptor (MC1R) was associated with increased basal cyclic adenosine monophosphate (cAMP) production, contributing to the species' darker coat color, which likely serves as camouflage on limestone rocks. Our findings reveal novel adaptive evolutionary mechanisms of limestone langurs and offer broader insights into organismal adaptation to extreme environments, with potential implications for understanding human health, biological evolution, and biodiversity conservation.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12231542/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143401039","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

Challenges in AI-driven Biomedical Multimodal Data Fusion and Analysis. 人工智能驱动的生物医学多模态数据融合与分析中的挑战。

Genomics, proteomics & bioinformatics Pub Date : 2025-05-10 DOI: 10.1093/gpbjnl/qzaf011

Junwei Liu 刘俊伟, Xiaoping Cen 岑萧萍, Chenxin Yi 伊晨昕, Feng-Ao Wang 王烽傲, Junxiang Ding 丁俊翔, Jinyu Cheng 程瑾瑜, Qinhua Wu 吴沁桦, Baowen Gai 盖宝文, Yiwen Zhou 周奕雯, Ruikun He 贺瑞坤, Feng Gao 高峰, Yixue Li 李亦学

{"title":"Challenges in AI-driven Biomedical Multimodal Data Fusion and Analysis.","authors":"Junwei Liu 刘俊伟, Xiaoping Cen 岑萧萍, Chenxin Yi 伊晨昕, Feng-Ao Wang 王烽傲, Junxiang Ding 丁俊翔, Jinyu Cheng 程瑾瑜, Qinhua Wu 吴沁桦, Baowen Gai 盖宝文, Yiwen Zhou 周奕雯, Ruikun He 贺瑞坤, Feng Gao 高峰, Yixue Li 李亦学","doi":"10.1093/gpbjnl/qzaf011","DOIUrl":"10.1093/gpbjnl/qzaf011","url":null,"abstract":"The rapid development of biological and medical examination methods has vastly expanded personal biomedical information, including molecular, cellular, image, and electronic health record datasets. Integrating this wealth of information enables precise disease diagnosis, biomarker identification, and treatment design in clinical settings. Artificial intelligence (AI) techniques, particularly deep learning models, have been extensively employed in biomedical applications, demonstrating increased precision, efficiency, and generalization. The success of the large language and vision models further significantly extends their biomedical applications. However, challenges remain in learning these multimodal biomedical datasets, such as data privacy, fusion, and model interpretation. In this review, we provide a comprehensive overview of various biomedical data modalities, multimodal representation learning methods, and the applications of AI in biomedical data integrative analysis. Additionally, we discuss the challenges in applying these deep learning methods and how to better integrate them into biomedical scenarios. We then propose future directions for adapting deep learning methods with model pretraining and knowledge integration to advance biomedical research and benefit their clinical applications.","PeriodicalId":94020,"journal":{"name":"Genomics, proteomics & bioinformatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12231560/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560401","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