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In the late 2000's, scale-free and small-world networks began shaping the emergence of systems biology, network biology, and network medicine. [3] In 2014, graph theoretical methods were used by Frank Emmert-Streib to analyze biological networks. [4]
Most data visualization in systems biology is done using mathematically generated models. Researchers will diagram all of the protein, gene, or metabolic pathways in a given biological system, then determine the speed of the reactions in that system using mass action kinetics or enzyme kinetics .
In ecology, the species discovery curve (also known as a species accumulation curve or collector's curve [1]) is a graph recording the cumulative number of species of living things recorded in a particular environment as a function of the cumulative effort expended searching for them (usually measured in person-hours).
The Systems Biology Graphical Notation (SBGN) is a standard graphical representation intended to foster the efficient storage, exchange and reuse of information about signaling pathways, metabolic networks, and gene regulatory networks amongst communities of biochemists, biologists, and theoreticians.
The species–area relationship for a contiguous habitat. The species–area relationship or species–area curve describes the relationship between the area of a habitat, or of part of a habitat, and the number of species found within that area.
Then an identification key is used to help determine which category or group the organism belongs in and allows a numerical value be assigned to that organism. A worksheet is then used to calculate the final value or score of all the organisms found. Depending upon the worksheet's equations, the score determines the condition of the water quality.
A graph of this equation creates an S-shaped curve, which demonstrates how initial population growth is exponential due to the abundance of resources and lack of competition. When factors that limit an organisms growth are not available in constant supply to meet the growing demand, such as RNA and protein amounts in bacteria, the growth of the ...
For a clustering example, suppose that five taxa (to ) have been clustered by UPGMA based on a matrix of genetic distances.The hierarchical clustering dendrogram would show a column of five nodes representing the initial data (here individual taxa), and the remaining nodes represent the clusters to which the data belong, with the arrows representing the distance (dissimilarity).