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Swarm is an open-source agent-based modeling simulation package, useful for simulating the interaction of agents (social or biological) and their emergent collective behavior. Swarm was initially developed at the Santa Fe Institute in the mid-1990s, and since 1999 has been maintained by the non-profit Swarm Development Group .
Examples of swarm intelligence in natural systems include ant colonies, bee colonies, bird flocking, hawks hunting, animal herding, bacterial growth, fish schooling and microbial intelligence. The application of swarm principles to robots is called swarm robotics while swarm intelligence refers to the more general set of algorithms.
As beekeeping technology has advanced, beekeeping has become more accessible, and urban beekeeping was described as a growing trend as of 2016. [3] Some studies have found city-kept bees are healthier than those in rural settings because there are fewer pesticides and greater biodiversity in cities. [4]
Environmental DNA or eDNA describes the genetic material present in environmental samples such as sediment, water, and air, including whole cells, extracellular DNA and potentially whole organisms. [13] [14] The analysis of eDNA starts with capturing an environmental sample of interest. The DNA in the sample is then extracted and purified.
Natural computing, [1] [2] also called natural computation, is a terminology introduced to encompass three classes of methods: 1) those that take inspiration from nature for the development of novel problem-solving techniques; 2) those that are based on the use of computers to synthesize natural phenomena; and 3) those that employ natural materials (e.g., molecules) to compute.
The alternative, known as automated annotation, is to use the power of computers to do the complex pattern-matching of protein to DNA. [ 5 ] [ 6 ] The Ensembl project was launched in 1999 in response to the imminent completion of the Human Genome Project , with the initial goals of automatically annotate the human genome, integrate this ...
A population (swarm) of candidate solutions (particles) moves in the search space, and the movement of the particles is influenced both by their own best known position and swarm's global best known position. Like genetic algorithms, the PSO method depends on information sharing among population members.
Primer walking is a method to determine the sequence of DNA up to the 1.3–7.0 kb range whereas chromosome walking is used to produce the clones of already known sequences of the gene. [2] Too long fragments cannot be sequenced in a single sequence read using the chain termination method. This method works by dividing the long sequence into ...