MCC regulator of WNT signaling pathway

Gene Context Sentence

Table 2. Analysis of context sentence of MCC gene in 11 abstracts.

PMID Gene Context Sentence
32209118 The predictive model achieved the maximum ACC of 98.18% coupled with the Matthews correlation coefficient (MCC) of 0.9638.
32793981 They are accuracy (ACC), F1 score, error rate and Matthews correlation coefficient (MCC) that are 100%, 100%, 0 and 1, respectively, for the KNN algorithm and 98.89%, 98.34%, 0.0111 and 0.9754, respectively, for the cascade-forward network.
33001828 Results are reported as sensitivity, specificity, F1 score, and Matthews correlation coefficient (MCC). […] The classification task between COVID-19-positive and COVID-19-negative for “high risk” cases among the 460 test cases yielded (sorted by F1 score): Symptoma (F1=0.92, MCC=0.85), Infermedica (F1=0.80, MCC=0.61), US Centers for Disease Control and Prevention (CDC) (F1=0.71, MCC=0.30), Babylon (F1=0.70, MCC=0.29), Cleveland Clinic (F1=0.40, MCC=0.07), Providence (F1=0.40, MCC=0.05), Apple (F1=0.29, MCC=-0.10), Docyet (F1=0.27, MCC=0.29), Ada (F1=0.24, MCC=0.27) and Your.MD (F1=0.24, MCC=0.27). […] For “high risk” and “medium risk” combined the performance was: Symptoma (F1=0.91, MCC=0.83) Infermedica (F1=0.80, MCC=0.61), Cleveland Clinic (F1=0.76, MCC=0.47), Providence (F1=0.75, MCC=0.45), Your.MD (F1=0.72, MCC=0.33), CDC (F1=0.71, MCC=0.30), Babylon (F1=0.70, MCC=0.29), Apple (F1=0.70, MCC=0.25), Ada (F1=0.42, MCC=0.03), and Docyet (F1=0.27, MCC=0.29).
33085645 The model also performed well in the external validation cohort with an area under the receiver operating characteristic curve of 0.93 (95% CI: 0.79 - 1.00), an F1 score of 0.80, and a Matthews correlation coefficient (MCC) of 0.76.
33089824 Due to the small size and easy handling, ion mobility spectrometry coupled with a multicapillary column (MCC-IMS) is a very promising, sensitive method for the on-site identification of infectious pathogens based on scents, representing volatile organic compounds (VOCs). […] The purpose of this study was to prospectively assess whether identification of Influenza-A-infection based on VOCs by MCC-IMS is possible in breath. […] Nasal breath was investigated in 24 consecutive persons with and without Influenza-A-infection by MCC-IMS. […] For picking up relevant VOCs in MCC-IMS spectra, software based on cluster analysis followed by multivariate statistical analysis was applied. […] This present proof-of-concept-study yields encouraging results showing a rapid diagnosis of viral infections in nasal breath within 5 min by MCC-IMS.
33259879 The Afr-SARCoV-2 sequences diversified into two lineages A and B, with B being more diverse with multiple sub-lineages confirmed by both maximum clade credibility (MCC) tree and PANGOLIN software.
33262241 The newly formed Microbiome Centers Consortium (MCC) surveyed its membership and identified four ways to leverage the strengths and experience of microbiome centers in the response to the COVID-19 pandemic. […] To meet these needs, the MCC will provide a platform to coordinate clinical and environmental research, assist with practical obstacles, and help communicate the connections between the microbiome and COVID-19.
33356151 As a result, the DeepDILI model outperformed the five conventional ML algorithms and two state-of-the-art ensemble methods with a Matthews correlation coefficient (MCC) value of 0.331. […] For question 2, we demonstrated that the DeepDILI model’s performance was significantly improved (i.e., a MCC improvement of 25.86% in test set) compared with deep neural networks based on molecule-based representation.
33390874 Other advanced parameters such as, MCC (Matthews Correlation Coefficient), ROC (Receiver Operating Characteristics) and PRC (Precision Recall) have also been considered for validation and the graphs are illustrated using Jupyter notebook.
33472571 The performance is measured using the metrics such as Accuracy, Recall, Precision, Specificity, F1 score, AUROC and MCC.
33578396 Recently we could demonstrate that ion mobility spectrometry coupled with a multicapillary column (MCC-IMS) is able to identify Influenza-A infections in patients’ breath. […] In this study, nasal breath of 75 patients (34m, 41f, aged 64.4 ± 15.4 years) was investgated by MCC-IMS for viral infections. 14 were positively diagnosed for Influenza-A infection and 16 for SARS-CoV-2 by reverse transcription polymerase chain reaction (RT-PCR) of nasopharyngeal swabs. […] Conclusion: MCC-IMS is able to detect SARS-CoV-2 infection and Influenza-A infection in breath in this pilot study.