Frontiers in Genetics | Computational Genomics section | New and Recent Articles https://www.frontiersin.org/journals/genetics/sections/computational-genomics RSS Feed for Computational Genomics section in the Frontiers in Genetics journal | New and Recent Articles en-us Frontiers Feed Generator,version:1 2026-05-03T19:30:43.769+00:00 60 https://www.frontiersin.org/articles/10.3389/fgene.2026.1787544 https://www.frontiersin.org/articles/10.3389/fgene.2026.1787544 <![CDATA[Application of integrated nested Laplace approximation to identify hot spots of methylation heterogeneity in healthy individuals from the MAMELI cohort]]> 2026-04-29T00:00:00Z Brief Research Report Tiago NardiEva DariolRachele MatsaganiDonya ZojajiStefano GustincichLuca PandolfiniElia BiganzoliValentina Bollati https://www.frontiersin.org/articles/10.3389/fgene.2026.1845666 https://www.frontiersin.org/articles/10.3389/fgene.2026.1845666 <![CDATA[Correction: BRMDA: prediction model for potential microbe-drug associations based on bilinear attention networks and random forest]]> 2026-04-21T00:00:00Z Correction Ge YuFang ChenHui ChenShichang TangMingmin LiangXianzhi LiuBin ZengLei Wang https://www.frontiersin.org/articles/10.3389/fgene.2026.1793277 https://www.frontiersin.org/articles/10.3389/fgene.2026.1793277 <![CDATA[Exploring Ebola virus-associated gene expression through comparative analysis]]> 2026-04-17T00:00:00Z Original Research Mostafa RezapourSean V. MurphyDavid A. OrnellesThomas D. ShupeStephen J. WalkerAlan R. JacobsonMetin Nafi GurcanPatrick M. McNuttAnthony Atala https://www.frontiersin.org/articles/10.3389/fgene.2026.1688627 https://www.frontiersin.org/articles/10.3389/fgene.2026.1688627 <![CDATA[A deep learning model for predicting essential proteins based on an attention mechanism]]> 2026-04-15T00:00:00Z Original Research Shunxian ZhouHaodong ZhouSisi ChenYangtai XuLei Wang https://www.frontiersin.org/articles/10.3389/fgene.2026.1803456 https://www.frontiersin.org/articles/10.3389/fgene.2026.1803456 <![CDATA[MoJKNet: a jumping knowledge graph framework for multi-omics cancer subtype prediction]]> 2026-04-07T00:00:00Z Original Research Jiangjie LouXiaoguang PanXuanlong Wang https://www.frontiersin.org/articles/10.3389/fgene.2026.1819270 https://www.frontiersin.org/articles/10.3389/fgene.2026.1819270 <![CDATA[Federated, governed, and interoperable? The emerging architecture of public human genomic data infrastructures: a European perspective]]> 2026-04-01T00:00:00Z Mini Review Marco Antonio TangaroMatteo ChiaraGraziano PesoleFederico Zambelli https://www.frontiersin.org/articles/10.3389/fgene.2026.1780660 https://www.frontiersin.org/articles/10.3389/fgene.2026.1780660 <![CDATA[A single-cell multi-omics atlas of human eyelid skin]]> 2026-03-31T00:00:00Z Data Report Weiguang MaYanwen XuJunjie ChenYue YuanXiaoyu WeiQiuting DengRuikang LiJiaxin DuZhongjin ZhangZhentao ZhouQuhuan LiHaiyan ShenJufang ZhangJufang WangPengfei CaiPengcheng Guo https://www.frontiersin.org/articles/10.3389/fgene.2026.1785259 https://www.frontiersin.org/articles/10.3389/fgene.2026.1785259 <![CDATA[Genomic and transcriptomic insights into aflatoxin-induced intrahepatic cholangiocarcinoma: an integrated pathway and meta-analysis study]]> 2026-03-31T00:00:00Z Original Research Fengping LiYuanyang MaYan ChengShanshan Zou 50%, p < 0.05) and downregulation of F2 and BUB1B (reduced expression >60%, p < 0.014). Co-expression analysis indicated strong interactions among these regulators (Fisher’s Z > 0.53, p < 0.05), suggesting coordinated molecular responses associated with ICC progression. Functional annotation further highlighted inflammatory responses, cytokine dysregulation, and kinase-related signaling as key processes potentially linking aflatoxin exposure to ICC development.DiscussionThese findings provide a systems-level view of the genomic mechanisms underlying aflatoxin-associated ICC carcinogenesis and identify candidate molecular mediators linking environmental toxin exposure to tumor development. This integrative framework may facilitate exposure-informed biomarker discovery and potential preventive or therapeutic strategies, particularly in regions where aflatoxin exposure remains prevalent.]]> https://www.frontiersin.org/articles/10.3389/fgene.2026.1770432 https://www.frontiersin.org/articles/10.3389/fgene.2026.1770432 <![CDATA[A graph clustering algorithm with hypergraph learning and a core-attachment strategy for protein complex identification]]> 2026-03-30T00:00:00Z Original Research Jie WangXiancan YangPengbo YangJian YangYangyang Miao https://www.frontiersin.org/articles/10.3389/fgene.2026.1762055 https://www.frontiersin.org/articles/10.3389/fgene.2026.1762055 <![CDATA[Advances in algorithms for normalizer gene selection in qRT-PCR: implications for cancer biology and precision medicine]]> 2026-03-27T00:00:00Z Mini Review Abhay Kumar PathakSukhad KuralLalit KumarSumit SainiManjari Gupta https://www.frontiersin.org/articles/10.3389/fgene.2026.1757318 https://www.frontiersin.org/articles/10.3389/fgene.2026.1757318 <![CDATA[BRMDA: prediction model for potential microbe-drug associations based on bilinear attention networks and random forest]]> 2026-03-26T00:00:00Z Methods Ge YuFang ChenHui ChenShichang TangMingmin LiangXianzhi LiuBin ZengLei Wang https://www.frontiersin.org/articles/10.3389/fgene.2026.1723592 https://www.frontiersin.org/articles/10.3389/fgene.2026.1723592 <![CDATA[Identifying mitochondrial genes and potential biological functions in pre-eclampsia: bioinformatics and experimental insights]]> 2026-03-24T00:00:00Z Original Research Yaohui WangZhixin DuLiping YangJunlin HouXiaolin LiMengyang FanChenyang YuJianhua SunLi ZhouLingling LiPengbei Fan https://www.frontiersin.org/articles/10.3389/fgene.2026.1723401 https://www.frontiersin.org/articles/10.3389/fgene.2026.1723401 <![CDATA[Integrating dual convolutional networks and BiLSTM for precision prediction of chronic myeloid leukemia from protein sequences]]> 2026-03-23T00:00:00Z Original Research Hend Khalid AlkahtaniAyman Qahmash https://www.frontiersin.org/articles/10.3389/fgene.2026.1769896 https://www.frontiersin.org/articles/10.3389/fgene.2026.1769896 <![CDATA[BioMutation: a portable graphical user interface for mutagenesis and feature analysis in proteins, nucleic acids, and their complexes]]> 2026-03-17T00:00:00Z Original Research Tushar GuptaPradeep Pant https://www.frontiersin.org/articles/10.3389/fgene.2026.1742595 https://www.frontiersin.org/articles/10.3389/fgene.2026.1742595 <![CDATA[An in silico protocol for predicting genetic biomarkers in rare diseases: a case study in sporadic amyotrophic lateral sclerosis]]> 2026-03-12T00:00:00Z Methods Ali AguerdBadreddine NouadiAbdelkarim EzaouineImad FenjarFaiza BennisFatima Chegdani https://www.frontiersin.org/articles/10.3389/fgene.2026.1685927 https://www.frontiersin.org/articles/10.3389/fgene.2026.1685927 <![CDATA[An auxiliary diagnosis model for the pathological classification of cervical cancer based on radiomics biomarkers]]> 2026-03-11T00:00:00Z Original Research Mei WangYu CaoMengchen ZhuPeilin ZhaoQin ZhouHongxiang LanJizhao LiuJunqiang Lei https://www.frontiersin.org/articles/10.3389/fgene.2026.1738448 https://www.frontiersin.org/articles/10.3389/fgene.2026.1738448 <![CDATA[Identification of the PFK gene family in Solanum species and expression analysis in the fruitof Solanum lycopersicum]]> 2026-03-09T00:00:00Z Original Research Zepeng WangZhongyu WangRuiqiang XuQingyuan MengJintao WangNing LiQinghui Yu https://www.frontiersin.org/articles/10.3389/fgene.2026.1766223 https://www.frontiersin.org/articles/10.3389/fgene.2026.1766223 <![CDATA[Multiscale computational genomics in Wilson disease: from atomic dynamics to clinical prediction]]> 2026-03-03T00:00:00Z Review Moujun LuanQingkai XueYujie CaoGangli ChengXingxing Huo https://www.frontiersin.org/articles/10.3389/fgene.2026.1715155 https://www.frontiersin.org/articles/10.3389/fgene.2026.1715155 <![CDATA[Case Report: Association of a rare single nucleotide variant in the KCNH2 gene with drug-induced QT prolongation]]> 2026-02-24T00:00:00Z Case Report Tianci WangCharlene R. Norgan RadlerMohanakrishnan Sathyamoorthy T (p.Arg356Cys) associated with drug-induced QT prolongation and to assess its pathogenicity risk using in silico tools and protein structural modeling in accordance with American College of Medical Genetics and Genomics (ACMG) guidelines.MethodsNext-generation sequencing was performed for a patient presenting with drug-induced QT prolongation who was found to carry the rare KCNH2 1066C>T variant. Thirteen established gene discovery computational tools were employed to analyze the variant in silico. Additionally, structural modeling of the variant’s region within the wild-type protein was performed utilizing AlphaFold.ResultsThe clinical phenotype associated with the KCNH2 1066C>T variant has not been previously described in literature, except in combination with a variant in the KCNQ1 gene. Computational analysis with a meta-predictor, REVEL, supported variant pathogenicity, while predictive modeling and AlphaMissense illustrated the uncertainty of structural impacts in a disordered region. Risk analysis of the variant performed utilizing ACMG guidelines and ClinGen criteria-specific recommendations resulted in an overall classification of “uncertain significance”.ConclusionTo our knowledge, this is the first study reporting a direct phenotype-to-genotype association between the KCNH2 1066C>T variant and drug-induced QT prolongation, supplemented by in silico analyses and ACMG-based variant risk stratification. Our study underscores the importance of recognizing genetic predisposition in drug-induced QT prolongation and motivate further investigation of KCNH2 variants within the N-linker region.]]> https://www.frontiersin.org/articles/10.3389/fgene.2026.1807544 https://www.frontiersin.org/articles/10.3389/fgene.2026.1807544 <![CDATA[Editorial: Advancements in sequencing technologies for epigenomic and transcriptomic analysis: from bulk to single-cell resolution]]> 2026-02-18T00:00:00Z Editorial Laura VeschettiMassimiliano CoccaDougba Noel DagoGiovanni Malerba