Ask about this productRelated genes to: WBP11 antibody
- Gene:
- WBP11 NIH gene
- Name:
- WW domain binding protein 11
- Previous symbol:
- -
- Synonyms:
- NPWBP, SIPP1, PPP1R165
- Chromosome:
- 12p12.3
- Locus Type:
- gene with protein product
- Date approved:
- 2001-08-28
- Date modifiied:
- 2014-11-19
Related products to: WBP11 antibody
Related articles to: WBP11 antibody
- In this study, we systematically investigated bladder cancer-related gene signatures using a toxicogenomics-informed framework, with particular attention to genes associated with lactylation-related pathways. Multi-omics data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) were integrated, and Weighted Gene Co-expression Network Analysis (WGCNA), a toxicology database, and lactylation-related gene sets were combined for intersection screening. Machine learning algorithms, including LASSO, SVM, and random forest, were then applied to identify key genes. Four prioritized BPA-lactylation-associated candidate genes-ENO1, WBP11, GTF2F1, and SPR-were ultimately identified and showed consistent associations with metabolic, immune, and transcription-related features. Multi-level validation, including immune infiltration analysis, single-cell transcriptome localization, proteomic validation, and molecular docking and kinetic simulation, supported the structural plausibility of BPA-protein interactions at the molecular level. This study proposes a toxicogenomics-informed, hypothesis-generating framework that prioritizes candidate genes and pathways potentially linking BPA-related signatures with lactylation-associated processes in bladder cancer. - Source: PubMed
Publication date: 2026/05/05
Wang HaoLiu HongquanSun FengzeWu Jitao - - Source: PubMed
Wei YuanChen ZhongshaoLi YingweiSong Kun - - Source: PubMed
Publication date: 2026/04/13
Ma TingbinLiu JinyuWang YuqiZhu HaiboQin YihongLiu RuizhiYuan HongtaoYe BaoyingHua RenyiLi ShuyuanXi HuiWang JianLi Niu - Orofacial clefts (OFCs) are the most common craniofacial congenital anomalies, with complex aetiology involving both genetic and environmental factors. Most genetic studies on the condition have focused on the contribution of single nucleotide variants (SNVs) and small insertions and deletions (indels). However, the contribution of copy number variants (CNVs), especially in African populations, remains underexplored despite their known contribution to congenital anomalies. This study aimed to identify high-confidence CNVs contributing to the aetiology of syndromic OFCs in Ghanaian case parent trios using whole exome sequencing (WES) datasets. - Source: PubMed
Publication date: 2026/04/01
Quaynor Samuel KanorMensah Gideon OkyereBusch TamaraTsri BruceObiri-Yeboah SolomonSabbah Daniel KwesiAgbenorku PiusDonkor PeterButali AzeezGowans Lord Jephthah Joojo - Micro-CT has become the standard for the assessment of malformations in mouse embryos because it allows the visualisation of internal structures in the context of the intact embryo. Statistical comparison of volume differences is possible via manual segmentation of organs of interest from micro-CT scans, but this process is slow and laborious. Automated registration-based methods now exist that make the volumetric analysis of all organs feasible. Here, we expand the available atlases for use with the LAMA registration and analysis pipeline to include high-resolution population averages derived from phosphotungstic acid-stained C57BL/6J embryos and corresponding manually segmented atlases at embryonic stage (E) 12.5, E15.5, and E17.5. We report application of these population averages and atlases with the LAMA phenotyping pipeline to Wbp11 heterozygous null embryos, identifying defects previously reported in the cervical vertebrae, brain, nasal cavity, palate, liver and kidneys as well as a right aortic arch defects missed by manual analysis, and volume differences in the eyes and spinal cord. Finally, we report a high-resolution isolated E18.5 mouse heart population average and corresponding atlas that when applied to the Wbp11 line identified significant differences. These findings highlight the advantages of unbiased, volumetric and quantitative approaches in the analysis of mouse models of human disease. - Source: PubMed
Publication date: 2026/01/23
Martin Ella M M ADrover KyleShpak AntonHorner Neil RO'Reilly VictoriaCocking EmmaGreasby Joelene AIyer Kavitha R Arkell RuthDunwoodie Sally LChapman Gavin