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Integrating Phylodynamics and Epidemiology to Estimate Transmission Diversity in Viral Epidemics

Mathematical epidemiology describes the spread of infectious diseases and aims to aid in the design of effective public health interventions [1]–[3]. Central to this endeavour is the basic reproductive number (R0) of an infectious disease, the mean number of secondary infections per primary infection in a completely susceptible population [4] (for notations see Table 1). Under simple epidemiological scenarios, in which all infected individuals behave identically, R0depends on the transmission probability per contact with a susceptible individual, the duration of infectiousness and the rate at which new contacts are made.

Ribosome Traffic on mRNAs Maps to Gene Ontology: Genome-wide Quantification of Translation Initiation Rates and Polysome Size Regulation

The expression of genes can be considered as a two-stage process, beginning with transcription and the production of an mRNA, followed by translation of that mRNA into protein by the cell’s ribosome population. Gene expression must be tightly regulated to control protein composition, enabling the cell to rapidly respond to a wide range of environmental conditions. For this reason, cells exert fine control over gene expression, both at the transcriptional, and post-transcriptional level.

Integrating Phylodynamics and Epidemiology to Estimate Transmission Diversity in Viral Epidemics

Mathematical epidemiology describes the spread of infectious diseases and aims to aid in the design of effective public health interventions. Central to this endeavour is the basic reproductive number (R0) of an infectious disease, the mean number of secondary infections per primary infection in a completely susceptible population

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Integrating Phylodynamics and Epidemiology to Estimate Transmission Diversity in Viral Epidemics

Mathematical epidemiology describes the spread of infectious diseases and aims to aid in the design of effective public health interventions. Central to this endeavour is the basic reproductive number (R0) of an infectious disease, the mean number of secondary infections per primary infection in a completely susceptible population

Integrating Phylodynamics and Epidemiology to Estimate Transmission Diversity in Viral Epidemics

Mathematical epidemiology describes the spread of infectious diseases and aims to aid in the design of effective public health interventions [1]–[3]. Central to this endeavour is the basic reproductive number (R0) of an infectious disease, the mean number of secondary infections per primary infection in a completely susceptible population [4] (for notations see Table 1). Under simple epidemiological scenarios, in which all infected individuals behave identically, R0depends on the transmission probability per contact with a susceptible individual, the duration of infectiousness and the rate at which new contacts are made.

Ribosome Traffic on mRNAs Maps to Gene Ontology: Genome-wide Quantification of Translation Initiation Rates and Polysome Size Regulation

The expression of genes can be considered as a two-stage process, beginning with transcription and the production of an mRNA, followed by translation of that mRNA into protein by the cell’s ribosome population. Gene expression must be tightly regulated to control protein composition, enabling the cell to rapidly respond to a wide range of environmental conditions. For this reason, cells exert fine control over gene expression, both at the transcriptional, and post-transcriptional level.

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Integrating Phylodynamics and Epidemiology to Estimate Transmission Diversity in Viral Epidemics

Mathematical epidemiology describes the spread of infectious diseases and aims to aid in the design of effective public health interventions [1]–[3]. Central to this endeavour is the basic reproductive number (R0) of an infectious disease, the mean number of secondary infections per primary infection in a completely susceptible population [4] (for notations see Table 1). Under simple epidemiological scenarios, in which all infected individuals behave identically, R0depends on the transmission probability per contact with a susceptible individual, the duration of infectiousness and the rate at which new contacts are made.

Ribosome Traffic on mRNAs Maps to Gene Ontology: Genome-wide Quantification of Translation Initiation Rates and Polysome Size Regulation

The expression of genes can be considered as a two-stage process, beginning with transcription and the production of an mRNA, followed by translation of that mRNA into protein by the cell’s ribosome population. Gene expression must be tightly regulated to control protein composition, enabling the cell to rapidly respond to a wide range of environmental conditions. For this reason, cells exert fine control over gene expression, both at the transcriptional, and post-transcriptional level.

Integrating Phylodynamics and Epidemiology to Estimate Transmission Diversity in Viral Epidemics

Mathematical epidemiology describes the spread of infectious diseases and aims to aid in the design of effective public health interventions. Central to this endeavour is the basic reproductive number (R0) of an infectious disease, the mean number of secondary infections per primary infection in a completely susceptible population

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