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Network Modeling and Analysis in Health Informatics and Bioinformatics最新文献

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A comprehensive review of global alignment of multiple biological networks: background, applications and open issues 多种生物网络的全球对齐:背景、应用和开放性问题综述
IF 2.3 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY Pub Date : 2022-01-28 DOI: 10.1007/s13721-022-00353-7
M. N. Girisha, Veena P. Badiger, S. Pattar
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引用次数: 1
Computer-aided diagnosis of digestive tract tumor based on deep learning for medical images 基于医学图像深度学习的消化道肿瘤计算机辅助诊断
IF 2.3 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY Pub Date : 2022-01-28 DOI: 10.1007/s13721-021-00343-1
Guanghua Zhang, Jing Pan, Changyuan Xing
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引用次数: 2
Identification of glycophorin C as a prognostic marker for human breast cancer using bioinformatic analysis 利用生物信息学分析鉴定糖蛋白C作为人类乳腺癌预后标志物
IF 2.3 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY Pub Date : 2022-01-03 DOI: 10.1007/s13721-021-00352-0
Md. Shahedur Rahman, Polash Kumar Biswas, S. K. Saha, M. Moni
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引用次数: 1
Mathematical modeling of the outbreak of COVID-19. 新冠肺炎爆发的数学模型。
IF 2.3 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY Pub Date : 2022-01-01 Epub Date: 2021-12-10 DOI: 10.1007/s13721-021-00350-2
Arvind Kumar Sinha, Nishant Namdev, Pradeep Shende

The novel coronavirus SARS-Cov-2 is a pandemic condition and poses a massive menace to health. The governments of different countries and their various prohibitory steps to restrict the virus's expanse have changed individuals' communication processes. Due to physical and financial factors, the population's density is more likely to interact and spread the virus. We establish a mathematical model to present the spread of the COVID-19 in India and worldwide. By the simulation process, we find the infected cases, infected fatality rate, and recovery rate of the COVID-19. We validate the model by the rough set method. In the method, we obtain the accuracy for the infected case is 90.19%, an infection-fatality of COVID-19 is 94%, and the recovery is 85.57%, approximately the same as the actual situation reported WHO. This paper uses the generalized simulation process to predict the outbreak of COVID-19 for different continents. It gives the way of future trends of the COVID-19 outbreak till December 2021 and casts enlightenment about learning the drifts of the outbreak worldwide.

新型冠状病毒SARS-Cov-2是一种大流行性疾病,对健康构成巨大威胁。不同国家的政府及其限制病毒传播的各种禁止措施改变了个人的沟通过程。由于物理和经济因素,人口密度更容易相互作用并传播病毒。我们建立了一个数学模型来呈现新冠肺炎在印度和世界范围内的传播。通过模拟过程,我们发现了新冠肺炎的感染病例、感染致死率和康复率。我们用粗糙集方法对模型进行了验证。在该方法中,我们获得感染病例的准确率为90.19%,新冠肺炎的感染致死率为94%,恢复率为85.57%,与世界卫生组织报告的实际情况大致相同。本文采用广义模拟过程对不同大陆新冠肺炎疫情进行预测。它为新冠肺炎疫情到2021年12月的未来趋势指明了方向,并为了解全球疫情的变化提供了启示。
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引用次数: 7
Factors affecting the difference of protein supplements on physical fitness 蛋白质补充剂对体质差异的影响因素
IF 2.3 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY Pub Date : 2021-12-07 DOI: 10.1007/s13721-021-00335-1
D. Li
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引用次数: 0
The impact of pre-clustering on classification of heterogeneous protein data 预聚类对异质蛋白质数据分类的影响
IF 2.3 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY Pub Date : 2021-12-07 DOI: 10.1007/s13721-021-00336-0
Haneen Altartouri, H. Tamimi, Y. Ashhab
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引用次数: 0
Empirical mode decomposition based adaptive noise canceller for improved identification of exons in eukaryotes 基于经验模态分解的自适应噪声消除方法改进真核生物外显子的识别
IF 2.3 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY Pub Date : 2021-11-24 DOI: 10.1007/s13721-021-00346-y
M. Hota
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引用次数: 1
In silico chemical profiling and identification of neuromodulators from Curcuma amada targeting acetylcholinesterase 针对乙酰胆碱酯酶的姜黄神经调节剂的硅化学分析和鉴定
IF 2.3 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY Pub Date : 2021-11-07 DOI: 10.1007/s13721-021-00334-2
M. Ali, Y. A. Munni, Raju Das, N. Akter, K. Das, Sarmistha Mitra, M. Hannan, R. Dash
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引用次数: 0
An effective feature extraction with deep neural network architecture for protein-secondary-structure prediction 基于深度神经网络的蛋白质二级结构预测特征提取方法
IF 2.3 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY Pub Date : 2021-10-23 DOI: 10.1007/s13721-021-00340-4
Aditya Jayasimha, Rahul Mudambi, P. Pavan, B. M. Lokaksha, Sanjay S. Bankapur, Nagamma Patil
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引用次数: 2
Identification of key genes, pathways, and associated comorbidities in chikungunya infection: insights from system biology analysis 鉴定基孔肯雅感染的关键基因、途径和相关合并症:来自系统生物学分析的见解
IF 2.3 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY Pub Date : 2021-09-12 DOI: 10.1007/s13721-021-00331-5
Lingjun Zhu, Xiaodong Wang, T. Asa, Md. Ali Hossain
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引用次数: 0
期刊
Network Modeling and Analysis in Health Informatics and Bioinformatics
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