Dataset Information

The scaffold protein AXIN1: gene ontology, signal network, and physiological function.

ABSTRACT: AXIN1, has been initially identified as a prominent antagonist within the WNT/β-catenin signaling pathway, and subsequently unveiled its integral involvement across a diverse spectrum of signaling cascades. These encompass the WNT/β-catenin, Hippo, TGFβ, AMPK, mTOR, MAPK, and antioxidant signaling pathways. The versatile engagement of AXIN1 underscores its pivotal role in the modulation of developmental biological signaling, maintenance of metabolic homeostasis, and coordination of cellular stress responses. The multifaceted functionalities of AXIN1 render it as a compelling candidate for targeted intervention in the realms of degenerative pathologies, systemic metabolic disorders, cancer therapeutics, and anti-aging strategies. This review provides an intricate exploration of the mechanisms governing mammalian AXIN1 gene expression and protein turnover since its initial discovery, while also elucidating its significance in the regulation of signaling pathways, tissue development, and carcinogenesis. Furthermore, we have introduced the innovative concept of the AXIN1-Associated Phosphokinase Complex (AAPC), where the scaffold protein AXIN1 assumes a pivotal role in orchestrating site-specific phosphorylation modifications through interactions with various phosphokinases and their respective substrates.

SUBMITTER: Qiu L

PROVIDER: S-EPMC10826278 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature

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The scaffold protein AXIN1: gene ontology, signal network, and physiological function.

Qiu Lu L Sun Yixuan Y Ning Haoming H Chen Guanyu G Zhao Wenshan W Gao Yanfeng Y

Cell communication and signaling : CCS 20240130 1

AXIN1, has been initially identified as a prominent antagonist within the WNT/β-catenin signaling pathway, and subsequently unveiled its integral involvement across a diverse spectrum of signaling cascades. These encompass the WNT/β-catenin, Hippo, TGFβ, AMPK, mTOR, MAPK, and antioxidant signaling pathways. The versatile engagement of AXIN1 underscores its pivotal role in the modulation of developmental biological signaling, maintenance of metabolic homeostasis, and coordination of cellular stre ...[more]

PMID: 38291457

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Project description:MotivationDespite advances in the gene annotation process, the functions of a large portion of gene products remain insufficiently characterized. In addition, the in silico prediction of novel Gene Ontology (GO) annotations for partially characterized gene functions or processes is highly dependent on reverse genetic or functional genomic approaches. To our knowledge, no prediction method has been demonstrated to be highly accurate for sparsely annotated GO terms (those associated to fewer than 10 genes).ResultsWe propose a novel approach, information theory-based semantic similarity (ITSS), to automatically predict molecular functions of genes based on existing GO annotations. Using a 10-fold cross-validation, we demonstrate that the ITSS algorithm obtains prediction accuracies (precision 97%, recall 77%) comparable to other machine learning algorithms when compared in similar conditions over densely annotated portions of the GO datasets. This method is able to generate highly accurate predictions in sparsely annotated portions of GO, where previous algorithms have failed. As a result, our technique generates an order of magnitude more functional predictions than previous methods. A 10-fold cross validation demonstrated a precision of 90% at a recall of 36% for the algorithm over sparsely annotated networks of the recent GO annotations (about 1400 GO terms and 11,000 genes in Homo sapiens). To our knowledge, this article presents the first historical rollback validation for the predicted GO annotations, which may represent more realistic conditions than more widely used cross-validation approaches. By manually assessing a random sample of 100 predictions conducted in a historical rollback evaluation, we estimate that a minimum precision of 51% (95% confidence interval: 43-58%) can be achieved for the human GO Annotation file dated 2003.AvailabilityThe program is available on request. The 97,732 positive predictions of novel gene annotations from the 2005 GO Annotation dataset and other supplementary information is available at http://phenos.bsd.uchicago.edu/ITSS/.Supplementary informationSupplementary data are available at Bioinformatics online.

Dataset Information

The scaffold protein AXIN1: gene ontology, signal network, and physiological function.

Publications

The scaffold protein AXIN1: gene ontology, signal network, and physiological function.

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