jackson clinical knowledgebase (jax-ckb) (Jackson Laboratory)
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Jackson Clinical Knowledgebase (Jax Ckb), supplied by Jackson Laboratory, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/clinical+knowledgebase+(jax-ckb)/jackson+clinical+knowledgebase/pmc11566986-182-3-7
Average 90 stars, based on 1 article reviews
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1) Product Images from "Precision oncology platforms: practical strategies for genomic database utilization in cancer treatment"
Article Title: Precision oncology platforms: practical strategies for genomic database utilization in cancer treatment
Journal: Molecular Cytogenetics
doi: 10.1186/s13039-024-00698-w
Figure Legend Snippet: Databases and their respective websites. Databases are separated into three categories described in methods (left column)
Techniques Used: Variant Assay, Clinical Proteomics, Biomarker Discovery
Related Articles
other:Article Title: Interpreting and integrating genomic tests results in clinical cancer care: Overview and practical guidance. Article Snippet: Affiliated institute OncoKB Hybrid Yes (if registered) Memorial Sloan Kettering Cancer Center, US Knowledge Base for Precision Oncology Hybrid Yes (partial if registered) The University of Texas MD Anderson Cancer Center, US Clinical Interpretation of Variants in Cancer (CIViC) Academic Yes Washington University St Louis, US Database of Curated Mutations (DoCM) Academic Yes Washington University St Louis, US MyCancerGenome Hybrid Yes (partial if registered) Vanderbilt University, US Cancer Genome Interpreter Academic Yes Barcelona Biomedical Genomics Laboratory, Article Title: Integrating Formalin-Fixed, Paraffin-Embedded-Derived Whole-Genome Sequencing into Routine Molecular Pathology: Validation and First Experiences in Metastatic Melanoma. Article Snippet: opyright a 2025 Association for Molecular his is an open access article under the CC B ttps://doi.org/10.1016/j.jmoldx.2025.04.011 Formalin-fixed, paraffin-embedded (FFPE) tumor tissue is the standard in pathology due to logistical and quality constraints of fresh-frozen samples.. Although whole-genome sequencing (WGS) offers diagnostic promise, its validity and utility in FFPE samples remain underexplored.. This study bridges the gap by comparing FFPE-derived tumor WGS with next-generation sequencing results from FoundationOneCDx (F1CDx) and a melanoma-specific panel (MelArray) in 78 metastatic melanoma samples from the Swiss Tumor Profiler Study. Article Title: Insights into gemcitabine resistance in pancreatic cancer: association with metabolic reprogramming and TP53 pathogenicity in patient derived xenografts Article Snippet: TP53 mutational information is from the supplementary data of Yang et al.; TP53 status of each model was classified as non-pathogenic, pathogenic, or having conflicting evidence based on annotations from OncoKB, Article Title: Insights into gemcitabine resistance in pancreatic cancer: association with metabolic reprogramming and TP53 pathogenicity in patient derived xenografts Article Snippet: Briefly, information about functional effects of TP53 mutation variants was obtained from the OncoKB and compared to the information from ClinVar, CiViC, and the Article Title: Pediatric precision oncology: “better three hours too soon than a minute too late” Article Snippet: Our criteria for pairing genomic biomarkers with targeted drugs is based upon the verified gene-drug lists available from the NCI ( https://www.cancer.gov/about-cancer/treatment/drugs/childhood-cancer-fda-approved-drugs ), the Memorial Sloan Kettering Cancer Center Precision Oncology Knowledge Base (OncoKB) ( ) and the Article Title: Precision oncology platforms: practical strategies for genomic database utilization in cancer treatment Article Snippet: They host the Mutagenesis:Article Title: SGCLMD: Signed graph-based contrastive learning model for predicting somatic mutation-drug association. Article Snippet: Somatic mutations could influence critical cellular processes, leading to uncontrolled cell growth and tumor formation.. Understanding the intricate interactions between somatic mutations and drugs was crucial for advancing our knowledge of the underlying biological mechanisms of cancer.. This knowledge, in turn, could drive advancements in cancer detection, diagnosis, and treatment. Variant Assay:Article Title: SGCLMD: Signed graph-based contrastive learning model for predicting somatic mutation-drug association. Article Snippet: Somatic mutations could influence critical cellular processes, leading to uncontrolled cell growth and tumor formation.. Understanding the intricate interactions between somatic mutations and drugs was crucial for advancing our knowledge of the underlying biological mechanisms of cancer.. This knowledge, in turn, could drive advancements in cancer detection, diagnosis, and treatment. Biomarker Discovery:Article Title: SGCLMD: Signed graph-based contrastive learning model for predicting somatic mutation-drug association. Article Snippet: Somatic mutations could influence critical cellular processes, leading to uncontrolled cell growth and tumor formation.. Understanding the intricate interactions between somatic mutations and drugs was crucial for advancing our knowledge of the underlying biological mechanisms of cancer.. This knowledge, in turn, could drive advancements in cancer detection, diagnosis, and treatment. |