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Thus, parallel MCMC computing by virtue of running multiple chains is rewarding only when ρ is small.
Therefore, the average Bayesian information criterion (BIC) of multiple chains is higher than that of a single chain, which resulted in lower AUCPRs.
Given that running multiple chains is simple and that they scale well with the number of available processors (or CPU cores), this type of "multiple-chain" parallelism is usually the strategy to strive for in the first instance.
An appealing advantage of running multiple chains is that these processes can be conducted concurrently with minimal coordination among tasks, as in the case of parallel Monte Carlo simulation.
Similar(56)
Sampling efficiency due to the use of multiple chains was also checked and was found to have almost linear scalability.
This unexpected level of structural polymorphism is potentially caused by the sophisticated pattern of hydrogen-bonding through the N H and C=O groups in chitin when multiple chains are put together outside the plasma membrane after the biosynthesis.
It also can be applied only when multiple chains are used.
In addition, the occurrence of domains singly (single domain in a single chain or single domain in multiple chains), repeating domains (multiple copies of a domain i.e., domain repeats in a single or multiple chains) and in their domain associations (single/multiple copies of a domain in association with neighboring/partnering domains in a single or multiple chains) was also noted.
Multiple chains are displayed as disconnected graphs.
If multiple chains were found in a cluster then the highest resolution chain without breaks was chosen.
Multiple chains were then combined after a 10% burn-in using LogCombiner v1.8.0 included in the BEAST package.
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