Developing the novel bioinformatics algorithms to systematically investigate the connections among survival time, key genes and proteins for Glioblastoma multiforme

You, Yujie; Ru, Xufang; Lei, Wanjing; Li, Tingting; Xiao, Ming; Zheng, Huiru; Chen, Yujie; Zhang, Le

doi:10.1186/s12859-020-03674-4

Cited by 10 publications

(9 citation statements)

References 52 publications

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“…It is found that AEBP1 can promote the occurrence and development of tumors [32][33][34]. We found that AEBP1 is upregulated in CRC, which is the same as the results of previous studies [34,35].…”

Section: Discussionsupporting

confidence: 90%

AEBP1 Predicts Clinical Prognosis and is Associated with Immunocyte Infiltration in Gastric Cancer

Deng¹,

Zhan²,

Chen³

et al. 2021

Preprint

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AEBP1 is differentially expressed in various tumors. However, the correlation between AEBP1 and immune cell infiltration in gastric cancer remains unclear. Kaplan-Meier survival curves were used to evaluate the relationship between AEBP1 expression and overall survival and progression-free survival. The relationship between AEBP1 expression and infiltrating immune cells, and their corresponding gene marker sets was examined using the TIMER database.The expression of AEBP1 was lower in gastric cancer (GC) tumor tissues than in normal tissues (P < 0.05). High AEBP1 gene expression and high levels of AEBP1 gene methylation were correlated with high-grade malignant tumor and old TNM stage. In addition, in gastric cancer, there was a positive correlation between AEBP1 expression and immune infiltrating cells, including neutrophils, CD8 + T cells, and CD4 + T cells, as well as immune-related genes, including CD2, CD3D, and CD3E. Methylation sites such as cg00009293, cg08495088, cg12955216, cg10480062, cg06852744 and cg12978582 were positively correlated with low expression of AEBP1. AEBP1 may be a potential tumor suppressor gene in GC and a potential novel therapeutic target and predictive biomarker for GC. AEBP1 likely plays an important role in immune cell infiltration.

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Section: Discussionsupporting

confidence: 90%

AEBP1 Predicts Clinical Prognosis and is Associated with Immunocyte Infiltration in Gastric Cancer

Deng¹,

Zhan²,

Chen³

et al. 2021

Preprint

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“…where k represents the lag order and is the error term. We use the F-test [23,[31][32][33][34][35][36][37][38][39] to verify the null hypothesis (Eq. ( 6)).…”

Section: Stationarity Test For Time Series Data Of Anthrax Casesmentioning

confidence: 99%

ASTM: Developing the web service for anthrax related spatiotemporal characteristics and meteorology study

Fan,

Xiao,

Sun

et al. 2022

Quant. Biol.

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Background: Anthrax is a zoonotic infectious disease caused by Bacillus anthracis. Investigating the spatiotemporal characteristics of anthrax and the impact of meteorological factors on the incidence of anthrax is helpful for the prevention and control of anthrax. Methods: At first, we applied the Granger causality test to explore the spatiotemporal characteristics of anthrax transmission between the counties and cities of Gannan Tibetan Autonomous Prefecture, Gansu Province of China. Then, we constructed three generalized linear models to analyze the impact of meteorological factors on the monthly number of anthrax cases in Gannan Tibetan Autonomous Prefecture. Finally, we developed an easy-to-use online web server that integrates the above functions. Results: This study developed an online service website (ASTM Anthrax in Gannan, Zhang Lab) for the analysis and visualization of anthrax, which not only can investigate the correlation of anthrax among different regions in Gannan Tibetan Autonomous Prefecture, but also can analyze the correlation between meteorological factors and the number of anthrax cases. Conclusions: Our study not only explored spatiotemporal characteristics of anthrax transmission, but also analyzed the impact of seven meteorological factors on the monthly number of anthrax cases. Meanwhile, the online service website which integrates the above functions is useful for the prevention and control of anthrax.

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“…Furthermore, the second analysis in Ramsden's [4] publication implemented a Cox regression model [13][14][15] for survival analysis to test for the relationship between cholesterol level reduction and risks of death. The recovered data was split into two groups depending on whether the participant's cholesterol level decreased at the end of the MCE.…”

Section: Introductionmentioning

confidence: 99%

Re‐examination of statistical relationships between dietary fats and other risk factors, and cardiovascular disease, based on two crucial datasets

Ou,

Zhang,

2024

Quant. Biol.

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Cardiovascular disease (CVD) is the major cause of death in many regions around the world, and several of its risk factors might be linked to diets. To improve public health and the understanding of this topic, we look at the recent Minnesota Coronary Experiment (MCE) analysis that used t‐test and Cox model to evaluate CVD risks. However, these parametric methods might suffer from three problems: small sample size, right‐censored bias, and lack of long‐term evidence. To overcome the first of these challenges, we utilize a nonparametric permutation test to examine the relationship between dietary fats and serum total cholesterol. To address the second problem, we use a resampling‐based rank test to examine whether the serum total cholesterol level affects CVD deaths. For the third issue, we use some extra‐Framingham Heart Study (FHS) data with an A/B test to look for meta‐relationship between diets, risk factors, and CVD risks. We show that, firstly, the link between low saturated fat diets and reduction in serum total cholesterol is strong. Secondly, reducing serum total cholesterol does not robustly have an impact on CVD hazards in the diet group. Lastly, the A/B test result suggests a more complicated relationship regarding abnormal diastolic blood pressure ranges caused by diets and how these might affect the associative link between the cholesterol level and heart disease risks. This study not only helps us to deeply analyze the MCE data but also, in combination with the long‐term FHS data, reveals possible complex relationships behind diets, risk factors, and heart disease.

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Developing the novel bioinformatics algorithms to systematically investigate the connections among survival time, key genes and proteins for Glioblastoma multiforme

Cited by 10 publications

References 52 publications

AEBP1 Predicts Clinical Prognosis and is Associated with Immunocyte Infiltration in Gastric Cancer

AEBP1 Predicts Clinical Prognosis and is Associated with Immunocyte Infiltration in Gastric Cancer

ASTM: Developing the web service for anthrax related spatiotemporal characteristics and meteorology study

Re‐examination of statistical relationships between dietary fats and other risk factors, and cardiovascular disease, based on two crucial datasets

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