Briefings in Functional Genomics最新文献

{"title":"Language model-based self-training reduces labeled data requirements by 99% for biological sequence classification.","authors":"Jingwen Liu, Danmo Gao, Yan Yuan, Ziying Wu, Weidong Li, Chao Wei","doi":"10.1093/bfgp/elag005","DOIUrl":"10.1093/bfgp/elag005","url":null,"abstract":"<p><p>The prediction of a biological sequence's function is an exploding field that could prove to be an invaluable tool in deciphering molecular mechanisms of diseases and genetic variation. However, existing techniques suffer from a very low number of experimentally verified labels as well as the complexity of modeling sequence context. Previous work only focuses on semi-supervised learning (SSL) or pre-trained language models (PLMs) individually and does not consider their complementarity: whereas PLMs capture syntactic conservatism and long-range dependency from huge unlabeled sequence data as features, SSL updates label-level certainty via confidence-weighted pseudo-label selection. To realize integrating these benefits, we make a creative use of PLMs as strong feature extractors to make the sequence semantics extracted, and meanwhile leverage the SSL to constrain the decision boundary by selecting reliable pseudo-labels. We show that our framework achieves competitive performance compared to full supervision while using far fewer labeled samples, on two biological prediction tasks: DNA-binding protein (DBP) and non-coding RNA (ncRNA) detection. In general, our approach, developed here, not only offers an efficient solution for discovering new DBP and ncRNA in low-resource settings where experimental verification is infeasible, but also lays a solid methodological foundation for biological sequence classification in computational biology. Key points Unlabeled data significantly improves model accuracy in semi-supervised learning. The language model-based self-training method outperforms traditional semi-supervised approaches like TSVM. It achieves competitive performance against state-of-the-art fully supervised methods, requiring only 1% labeled data for effective classification and accurately identifying novel biomolecules.</p>","PeriodicalId":55323,"journal":{"name":"Briefings in Functional Genomics","volume":"25 ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13267906/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148260677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AGRN activates GPX4 via the Wnt/beta-catenin signaling pathway to suppress ferroptosis in cervical cancer cells.","authors":"Aizhen Fu, Jiayi Cai, Ruitao Chen, Xinxin Zou, Yongfeng Chen, Fengping Fu, Wen Zhang, Lin Huang, Yuan Ye, Renhe Li, Bingfang Mai","doi":"10.1093/bfgp/elag010","DOIUrl":"10.1093/bfgp/elag010","url":null,"abstract":"<p><p>Cervical cancer remains a leading cause of cancer-related deaths among women worldwide. Targeting ferroptosis, a regulated form of cell death driven by lipid peroxidation, has emerged as a promising therapeutic strategy. This study aimed to elucidate the mechanisms by which cervical cancer cells acquire resistance to ferroptosis. AGRN expression and its prognostic significance were analyzed in cervical cancer using TCGA and GTEx data. In vitro, AGRN levels were measured in HeLa, CaSki, and Ect1/E6E7 cells via qRT-PCR. mRNA and protein expression levels of AGRN, beta-catenin, and ferroptosis-related markers were evaluated by qRT-PCR and western blot (WB). Cell viability, RSL3 sensitivity (IC50), and lipid ROS were assessed via CCK-8 assay and flow cytometry. In a xenograft model, RSL3's effect on tumor growth was examined. Immunohistochemistry (IHC) and molecular analyses (qRT-PCR, WB, and flow cytometry) were performed on tumor tissues to evaluate AGRN, beta-catenin, Ki-67, ferroptosis-related genes, and lipid ROS. It is found through research that, AGRN was significantly upregulated in cervical cancer tissues and cell lines. Its overexpression activated Wnt/beta-catenin signaling, resulting in elevated GPX4 and SLC7A11 levels and reduced CHAC1 and PTGS2 expression levels. These alterations decreased lipid ROS accumulation and enhanced resistance to RSL3-induced ferroptosis, an effect further confirmed in xenograft models. In short, In short, AGRN promotes ferroptosis resistance in cervical cancer by activating the Wnt/beta-catenin signaling pathway and upregulating GPX4 expression. Targeting the AGRN-Wnt/beta-catenin-GPX4 axis may represent a novel therapeutic approach for cervical cancer.</p>","PeriodicalId":55323,"journal":{"name":"Briefings in Functional Genomics","volume":"25 ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13575931/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148972332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Combining co-expression analysis and machine learning to explore the diagnostic value of complement and coagulation cascade-related genes in asthma and the functional role of SERPINB2.","authors":"Jingjing Feng, Chengfang Xie, Weiduo Jin, Yanhong Huang, Yan Wang","doi":"10.1093/bfgp/elag007","DOIUrl":"10.1093/bfgp/elag007","url":null,"abstract":"<p><strong>Background: </strong>Optimizing diagnostic strategies for asthma is crucial for alleviating its high global disease burden. In recent years, the complement and coagulation cascades (CCC), as a central hub of innate immunity and inflammatory responses, has gained increasing attention for its association with asthma.</p><p><strong>Methods: </strong>Asthma-related datasets (GSE67472, GSE4302, and GSE76262) were downloaded from the Gene Expression Omnibus database. Subsequently, weighted gene co-expression network analysis and four machine learning algorithms-Decision Tree, K-Nearest Neighbors, Random Forest (RF), and Gradient Boosting Machine-were employed to identify key genes and construct a diagnostic model. SERPINB2 expression was then detected in clinical samples. The functional mechanisms of the key genes were validated using Transforming Growth Factor Beta 1 (TGF-β1)-treated Human Bronchial Epithelial Cells (BEAS-2B) cells through Quantitative Reverse Transcription Polymerase Chain Reaction (qRT-PCR), western blot, CCK-8 assay, and Co-IP experiments.</p><p><strong>Results: </strong>This research identified seven key genes: Serpin Family B Member 2 (SERPINB2), Complement C3 (C3), Complement C6 (C6), Colony Stimulating Factor 2 Receptor Subunit Beta (CSF2RB), Death Associated Protein Kinase 1 (DAPK1), Solute Carrier Family 16 Member 6 (SLC16A6), and CD69 Molecule (CD69). The diagnostic model constructed based on the RF algorithm exhibited robust discriminatory performance in both the training and validation sets. qRT-PCR assays on clinical tissue samples revealed significantly upregulated SERPINB2 expression in asthmatic tissues. In vitro experiments further revealed that SERPINB2 expression was upregulated in TGF-β1-treated BEAS-2B cells. Knockdown of SERPINB2 suppressed the expression of proteins related to epithelial-mesenchymal transition, inflammatory responses, and airway remodeling. Co-immunoprecipitation (Co-IP) assays indicated an association between SERPINB2 and C3 at the protein level.</p><p><strong>Conclusion: </strong>The RF model constructed based on seven CCC-related candidate genes exhibited promising diagnostic value for asthma. SERPINB2 may participate in airway epithelial inflammation and remodeling and may be associated with complement C3 at the protein level. These findings provide novel evidence for further elucidating the potential roles and clinical implications of the CCC cascade in the initiation and progression of asthma.</p><p><strong>Key points: </strong></p>","PeriodicalId":55323,"journal":{"name":"Briefings in Functional Genomics","volume":"25 ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13513769/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148835045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unraveling risk factors and transcriptomic signatures in liver cancer progression and mortality through machine learning and bioinformatics.","authors":"Tania Akter Asa, Md Ali Hossain, Md Shahjahan Ali, Md Zulfiker Mahmud, A K M Azad, Mohammad Zahidur Rahman, Mohammad Ali Moni","doi":"10.1093/bfgp/elaf019","DOIUrl":"10.1093/bfgp/elaf019","url":null,"abstract":"<p><p>Liver cancer (LC) is the second leading cause of cancer-related deaths globally, yet the molecular mechanisms linking its progression with associated risk factors (RFs) remain poorly understood. To address this, we developed an integrative multi-stage framework combining bioinformatics, machine learning-based feature selection, survival modeling, and network analysis to identify robust biomarkers and pathways involved in LC progression. Unlike conventional biomarker discovery approaches, our strategy integrates multi-cohort transcriptomic and clinical datasets, enhancing robustness and reliability of findings. Initially, differentially expressed genes were identified from three Gene Expression Omnibus datasets for LC and its RFs. Next, using shared biomarkers, we constructed a gene-disease association (diseasome) network, revealing 230 unique genes, including 126 shared between LC and liver cirrhosis. Subsequently, RNA-seq and clinical data from The Cancer Genome Atlas (TCGA) were analyzed through combined and multivariate Cox survival models, identifying 70 prognostic genes. Among these, we identified RGS5, SULT1C2, CSM3, and CXCL14 as consistent survival-associated markers. Functional investigation of the 70 genes using enrichment and protein-protein interaction networks uncovered ten hub genes involved in key oncogenic pathways, including Oocyte meiosis, Lysine degradation and cell cycle regulation. These findings were further validated through literature and expression-level analysis. Additionally, an independent survival analysis using the full TCGA transcriptomic dataset identified 76 significant genes, with 18 overlapping the risk-associated gene set, reinforcing their prognostic value. Overall, this study demonstrates the potential of an integrative computational approach to uncover meaningful biomarkers and pathways in LC, offering valuable insights for future clinical and therapeutic strategies.</p>","PeriodicalId":55323,"journal":{"name":"Briefings in Functional Genomics","volume":"25 ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12785888/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145947008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Retraction and replacement of: An integrated complete-genome sequencing and systems biology approach to predict antimicrobial resistance genes in the virulent bacterial strains of Moraxella catarrhalis.","authors":"","doi":"10.1093/bfgp/elaf026","DOIUrl":"10.1093/bfgp/elaf026","url":null,"abstract":"","PeriodicalId":55323,"journal":{"name":"Briefings in Functional Genomics","volume":"25 ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12862486/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146108527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Whole-transcriptome sequencing reveals hypoxic esophageal squamous cell carcinoma-derived migrasomes driving cancer-associated fibroblast activation.","authors":"Guan'en Qiao, Zhongping Wang, Meng Wang, Le Feng, Zixuan You, Bing Meng, Kui Dong, Yanping Cao, Pan Li, Junhai Wang, Xinqing Lu, Chunfang Xu","doi":"10.1093/bfgp/elag002","DOIUrl":"10.1093/bfgp/elag002","url":null,"abstract":"<p><p>Cancer-associated fibroblasts (CAFs) activated by intercellular communication contribute to the progression of esophageal squamous cell carcinoma (ESCC). Migrasomes represent a novel mode of intercellular communication. However, the characteristics of ESCC-derived migrasomes in tumor hypoxic microenvironments and their effects on CAFs remain unclear. Migrasomes were isolated from ESCC cells under normoxia/hypoxia, with TSPAN4-GFP labeling, transmission electron microscopy, nanoparticle tracking analysis, and western blot for validation. Whole-transcriptome sequencing analyzed hypoxic migrasome RNA profiles, and ceRNA networks were predicted via RNAhybrid and Miranda. The effect of migrasomes on CAFs was assessed using fluorescence tracing, reverse transcription‑quantitative polymerase chain reaction, Transwell migration, enzyme‑linked immunosorbent assay, and western blot. ESCC cells produced migrasomes. Although hypoxia did not alter their quantity or structure, it significantly altered their RNA cargo, changing the composition of mRNA, lncRNA, and circRNA. Differentially expressed mRNAs were enriched in \"Response to hypoxia\" and \"HIF-1 signaling pathway.\" DElncRNAs were enriched in \"Golgi to plasma membrane protein transport\" and \"Cell adhesion molecules pathway,\" while DEcircRNAs were enriched in \"ubiquitin binding\" and \"chromatin remodeling.\" Predicted ceRNA networks were constructed using RNAhybrid and Miranda, involving 659 miRNAs, 24 lncRNAs, and 132 mRNAs. Fibroblasts internalized migrasomes and acquired a CAF-like phenotype, showing enhanced migration, elevated secretion of IL-1β/TGF-β, and increased CAF marker expression (α-SMA, COL1A1, COL3A1, FAP, PDGFRβ), with effects most pronounced under hypoxic migrasome treatment. This study characterized hypoxic migrasome whole transcriptome landscapes and suggested that hypoxic migrasomes may promote CAF-like changes in vitro, uncovering a novel ESCC-tumor microenvironment interaction mechanism and offering new perspectives for ESCC research.</p>","PeriodicalId":55323,"journal":{"name":"Briefings in Functional Genomics","volume":"25 ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13229262/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148152126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An integrated complete-genome sequencing and systems biology approach to predict antimicrobial resistance genes in the virulent bacterial strains of Moraxella catarrhalis.","authors":"Sadia Afrin Bristy, Md Arju Hossain, Md Imran Hasan, S M Hasan Mahmud, Mohammad Ali Moni, Md Habibur Rahman","doi":"10.1093/bfgp/elaf027","DOIUrl":"10.1093/bfgp/elaf027","url":null,"abstract":"<p><p>Moraxella catarrhalis is a symbiotic as well as mucosal infection-causing bacterium unique to humans. Currently, it is considered as one of the leading factors of acute middle ear infection in children. As M. catarrhalis is resistant to multiple drugs, the treatment is unsuccessful; therefore, innovative and forward-thinking approaches are required to combat the problem of antimicrobial resistance (AMR). To better comprehend the numerous processes that lead to antibiotic resistance in M. catarrhalis, we have adopted a computational method in this study. From the NCBI-Genome database, we investigated 12 strains of M. catarrhalis. We explored the interaction network comprising 74 antimicrobial-resistant genes found by analyzing M. catarrhalis bacterial strains. Moreover, to elucidate the molecular mechanism of the AMR system, clustering and the functional enrichment analysis were assessed employing AMR gene interactions networks. According to the findings of our assessment, the majority of the genes in the network were involved in antibiotic inactivation; antibiotic target replacement, alteration and antibiotic efflux pump processes. Additionally, rpoB, atpA, fusA, groEL and rpoL have the highest frequency of relevant interactors in the interaction network and are therefore regarded as the hub nodes. These hub genes only reflects their centrality in cellular function, rather than direct or selective targets for antimicrobial development without reservation. Finally, we believe that our findings could be useful to advance knowledge of the AMR system present in M. catarrhalis via a series of phenotypic assays including MIC testing, and gene expression analysis (RT-qPCR) to confirm the functional expression of AMR genes.</p>","PeriodicalId":55323,"journal":{"name":"Briefings in Functional Genomics","volume":"25 ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12930093/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146108521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An integrative meta-analysis of SARS-CoV-2 RNA-protein interactomes identifies conserved host factors shared with other RNA viruses.","authors":"Kuerbannisha Amahong, Yuhong Liu, Zheng Zhang, Lin Tao, Aishe A Sarshad, Feng Zhu","doi":"10.1093/bfgp/elag001","DOIUrl":"10.1093/bfgp/elag001","url":null,"abstract":"<p><p>RNA viruses cause substantial global disease burden and depend on host RNA-binding proteins and translation machinery. However, it remains unclear which host factors are robustly engaged across independent Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) RNA interactome studies and to what extent these factors are shared with other RNA viruses. Here, we perform an integrative meta-analysis of eight published SARS-CoV-2 RNA-protein interactomes and compare them with corresponding Influenza A virus, Zika virus, and Dengue virus datasets to define conserved host networks and prioritize candidate host-directed antiviral targets. By integrating multiple datasets and applying ClusterProfiler together with curated pathway resources (KEGG, Reactome, WikiPathways, and Gene Ontology), we systematically characterize the functional landscape of SARS-CoV-2 RNA-protein interactions. The consensus SARS-CoV-2 interactome is enriched for mRNA processing, translation, RNA surveillance and innate immune functions. Cross-viral comparison identifies 275 host proteins shared across all four RNA viruses, forming interconnected modules that include key translation factors (EEF1A1, EIF4A1, EIF3H) and RNA-binding proteins (Nucleolin, ILF3). Drug-target annotation prioritizes 21 proteins with 35 approved or investigational modulators for host-directed antiviral repurposing. Together, these findings generate a consensus map of conserved host dependencies and highlight prioritized targets for future mechanistic and translational studies. Research Highlights Integrated SARS-CoV-2 datasets and compared with, Influenza A virus, Zika virus, Dengue virus. Identified 275 host proteins shared across these four pathogens. Conserved proteins were enriched in translation, RNA processing, and innate immune pathways. Prioritized 21 host targets and 35 drugs for antiviral repurposing.</p>","PeriodicalId":55323,"journal":{"name":"Briefings in Functional Genomics","volume":"25 ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13182571/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147977511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"KaryoExplorer: an automated digital karyotyping pipeline with interactive visualizations.","authors":"Ugur Dura, Xavier Pastor Hostench, Peter Lichtner, Alena Boos, Thomas Walzthoeni","doi":"10.1093/bfgp/elag012","DOIUrl":"10.1093/bfgp/elag012","url":null,"abstract":"<p><p>Routine genomic quality control (QC) is essential for ensuring the integrity of induced pluripotent stem cells used in disease modeling, regenerative medicine, and related cell line applications. However, digital karyotyping workflows based on single nucleotide polymorphism genotyping arrays are often fragmented, requiring separate tools for copy number variation (CNV) detection, loss of heterozygosity (LOH) analysis, and result visualization. This fragmentation complicates interpretation, limits reproducibility, and creates practical barriers for routine use and collaborative review. Here, we present KaryoExplorer, an automated Nextflow-based pipeline for digital karyotyping of genotyping array data that generates an easy-to-use, self-contained interactive HTML report. CNV calling and runs of homozygosity (ROH)-based detection of candidate copy-neutral loss of heterozygosity (cnLOH) regions are integrated into a unified, reproducible workflow. The resulting browser-based report combines genome-wide karyograms, chromosome-level B-allele frequency (BAF), log-R ratio (LRR), copy number (CN) tracks, QC summaries, event tables, and synchronized interactive views that support intuitive navigation from sample overview to signal-level inspection. Validation on a 36-sample genotyping dataset, evaluated in both single-sample and paired analysis modes, showed that deletion events ($mathrm{CN} leq 1$) overlapped ROH segments with a median of 99.2%, supporting the biological consistency of the integration strategy. Candidate cnLOH regions defined by ROH overlapping diploid copy number states ($mathrm{CN}=2$) showed increased BAF deviation relative to diploid non-ROH regions, and were highly reproducible across paired technical replicates. KaryoExplorer therefore streamlines digital karyotyping by coupling automated analysis with accessible, interactive, and shareable reporting for genomic QC workflows.</p>","PeriodicalId":55323,"journal":{"name":"Briefings in Functional Genomics","volume":"25 ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13715436/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149290123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Retraction of: Integration of single cell multiomics data by deep transfer hypergraph neural network.","authors":"","doi":"10.1093/bfgp/elaf024","DOIUrl":"10.1093/bfgp/elaf024","url":null,"abstract":"","PeriodicalId":55323,"journal":{"name":"Briefings in Functional Genomics","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12848942/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146054971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}