In present, more and more attention has been put on the effort of protection of personal data and also new encryption technologies are derived. In this article, we introduce a personal information protection technolog...
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SIR (susceptible, infectious, removed) epidemic models are commonly used in infectious disease study. These models use systems of differential equations to estimate epidemiological parameters. However, differential eq...
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ISBN:
(纸本)9789881925305
SIR (susceptible, infectious, removed) epidemic models are commonly used in infectious disease study. These models use systems of differential equations to estimate epidemiological parameters. However, differential equations often suffer from numerical challenges. Here, we proposed simple, effective and robust innovative methods for estimating key infectious disease parameters. Our methods are reformed from the SIR models, by adjusting components of model compartments. We illustrated the methods using the recent large disease outbreaks, Ebola virus disease and Middle East respiratory syndrome Coronavirus.
Networks of gene regulation control many aspects of cellular biology, ranging from development and differentiation to the cell cycle and apoptosis. However, the precise control of genetic regulation is poorly understo...
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Networks of gene regulation control many aspects of cellular biology, ranging from development and differentiation to the cell cycle and apoptosis. However, the precise control of genetic regulation is poorly understood for whole cells and large systems. Technical achievements in the genome-wide measurement of DNA, mRNA and proteins - and their assorted interactions - have enabled systematic approaches to regulation in molecular biology, which promise to shed new light on the complex architecture of gene regulatory networks. Detailed knowledge of such systems is crucial for our understanding of molecular phenotypes;similarly, our ability to treat and cure many diseases will depend on our understanding of molecular disease at its regulatory and mechanistic roots.
High-throughput data such as microarrays make it possible to investigate the molecular-level mechanism of cancer more efficiently. Computational methods boost the microarray analysis by managing large and complex data...
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Single-nucleotide polymorphism (SNP) analysis has become a pivotal strategy for drug discovery within bioinformatics, especially for incurable diseases like cancer. With the increasing number of researchers starting t...
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Numerous research on stunting supplementation interventions in Indonesia have been published. The information can be extracted through data mining, especially from academic research databases. In this paper, we presen...
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Transformer models, originally successful in natural language processing, are now being applied to chemical and biological studies, excelling in areas such as molecular property prediction, material science, and drug ...
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The growing number of medical images has led to radiologist burnout, which seriously impacts the radiologist's performance. To address the previously mentioned issue, an Auxiliary Signal Guided Knowledge (ASGK) mu...
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Segmentation is manually performed by physicians, which takes considerable time and may be subject to observers. Automating this task can increase efficiency and consistency. Existing studies on meningioma segmentatio...
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A wide variety of disciplines contribute to bioinformatics research, including computer science, biology, chemistry, mathematics, and physics. This study determines the number of research articles published on arXiv c...
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