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ATCC
human liver tumor derived cell lines snu387 ![]() Human Liver Tumor Derived Cell Lines Snu387, supplied by ATCC, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more https://www.bioz.com/product/liver+neoplasms/pmc13003555-38-0-17?v=ATCC Average 96 stars, based on 1 article reviews
human liver tumor derived cell lines snu387 - by Bioz Stars,
2026-07
96/100 stars
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Kaggle Inc
liver tumor classification dataset ![]() Liver Tumor Classification Dataset, supplied by Kaggle Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more https://www.bioz.com/product/liver+neoplasms/pmc13268880-185-4-9?v=Kaggle+Inc Average 86 stars, based on 1 article reviews
liver tumor classification dataset - by Bioz Stars,
2026-07
86/100 stars
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Covance
rodent liver tumors ![]() Rodent Liver Tumors, supplied by Covance, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more https://www.bioz.com/product/liver+neoplasms/pm42086044-36-4-28?v=Covance Average 86 stars, based on 1 article reviews
rodent liver tumors - by Bioz Stars,
2026-07
86/100 stars
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Covance
liver tumor incidence ![]() Liver Tumor Incidence, supplied by Covance, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more https://www.bioz.com/product/liver+neoplasms/pm42086044-43-3-1?v=Covance Average 86 stars, based on 1 article reviews
liver tumor incidence - by Bioz Stars,
2026-07
86/100 stars
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Kaggle Inc
liver tumor segmentation challenge dataset ![]() Liver Tumor Segmentation Challenge Dataset, supplied by Kaggle Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more https://www.bioz.com/product/liver+neoplasms/pm41945655-56-16-22?v=Kaggle+Inc Average 86 stars, based on 1 article reviews
liver tumor segmentation challenge dataset - by Bioz Stars,
2026-07
86/100 stars
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Kaggle Inc
liver tumor segmentation dataset ![]() Liver Tumor Segmentation Dataset, supplied by Kaggle Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more https://www.bioz.com/product/liver+neoplasms/pm41945655-48-10-15?v=Kaggle+Inc Average 86 stars, based on 1 article reviews
liver tumor segmentation dataset - by Bioz Stars,
2026-07
86/100 stars
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Charles River Laboratories
liver tumors ![]() Liver Tumors, supplied by Charles River Laboratories, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more https://www.bioz.com/product/liver+neoplasms/pm41744804-58-2-27?v=Charles+River+Laboratories Average 86 stars, based on 1 article reviews
liver tumors - by Bioz Stars,
2026-07
86/100 stars
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Biomax Inc
human liver tumor tissue microarray ![]() Human Liver Tumor Tissue Microarray, supplied by Biomax Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more https://www.bioz.com/product/liver+neoplasms/pmc13282892-81-1-9?v=Biomax+Inc Average 86 stars, based on 1 article reviews
human liver tumor tissue microarray - by Bioz Stars,
2026-07
86/100 stars
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Journal: Journal of Cancer
Article Title: FAM188B promotes progression of hepatocellular carcinoma by regulating YAP/TAZ via interaction with USP10
doi: 10.7150/jca.125659
Figure Lengend Snippet: FAM188B expression is upregulated and associated with poor prognosis in hepatocellular carcinoma (HCC). (A) Expression of FAM188B mRNA in tumor and non-tumor tissues and its association with cancer stage and tumor grade in UALCAN database. (B) The expression of FAM188B protein was evaluated in normal hepatocytes (LX-2) and in hepatocellular carcinoma (HCC) cells (MHCC97H, Huh7, Hep3B and SNU387) by western blot. (C) Validation of FAM188B expression after overexpression in the indicated cell lines using western blotting (n = 3). (D) Proliferation of MHCC97H and Huh7 cells, as detected by performing CCK-8 assays (n = 10). (E) Migratory and invasive capacities of MHCC97H and Huh7 cells within 24 hours, as evaluated using Transwell assays (scale bar, 50 μm) (n = 3). *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001, ns, not significant. The data are expressed as the mean ± SD of three independent experiments.
Article Snippet:
Techniques: Expressing, Western Blot, Biomarker Discovery, Over Expression, CCK-8 Assay
Journal: Journal of Cancer
Article Title: FAM188B promotes progression of hepatocellular carcinoma by regulating YAP/TAZ via interaction with USP10
doi: 10.7150/jca.125659
Figure Lengend Snippet: FAM188B interacts with USP10. (A) Schematic illustration of IP and GO enrichment of identified proteins (using all proteins in the species database as the background). Fisher's exact test was used to analyze the significance and P value < 0.05 were considered significant. (B) Expression levels of USP10 mRNA in tumor (n = 374) and non-tumor (n = 50) tissues and its relationship with FAM188B, based on a public database. (C) The protein expression level of USP10 was evaluated in normal hepatocytes (LX-2) and hepatocellular carcinoma (HCC) cells (MHCC97H, Huh7, Hep3B and SNU387) by western blot. (D) Localization of USP10 in HCC cells (scale bar, 20 μm). (E) Co-IP assays to confirm the protein-protein interaction between FAM188B and USP10 in vitro . **p < 0.01, ***p < 0.001. The data are expressed as the mean ± SD of three independent experiments. IP, immunoprecipitation. Co-IP, co-immunoprecipitation.
Article Snippet:
Techniques: Expressing, Western Blot, Co-Immunoprecipitation Assay, In Vitro, Immunoprecipitation
Journal: Frontiers in Oncology
Article Title: Leveraging deep learning and explainable AI for effective liver tumor classification from CT scan images
doi: 10.3389/fonc.2026.1836325
Figure Lengend Snippet: Overall workflow of the proposed liver tumor classification framework. It illustrates the two major components of the system: classification of CT liver images and the integration of explainable AI methods for interpretability.
Article Snippet: The first is the
Techniques:
Journal: Frontiers in Oncology
Article Title: Leveraging deep learning and explainable AI for effective liver tumor classification from CT scan images
doi: 10.3389/fonc.2026.1836325
Figure Lengend Snippet: Classification methodology workflow. Step-by-step pipeline for liver tumor classification, including dataset preparation, preprocessing, augmentation, model training, evaluation, and explainability.
Article Snippet: The first is the
Techniques: