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Alignment-free methods can broadly be classified into five categories: a) methods based on k-mer/word frequency, b) methods based on the length of common substrings, c) methods based on the number of (spaced) word matches, d) methods based on micro-alignments, e) methods based on information theory and f) methods based on graphical representation.
A global alignment performs an end-to-end alignment of the query sequence with the reference sequence. Ideally, this alignment technique is most suitable for closely related sequences of similar lengths. The Needleman-Wunsch algorithm is a dynamic programming technique used to conduct global alignment. Essentially, the algorithm divides the ...
Bringing forward farmland sites to receive biodiversity offset credits will create the investment needed to improve biodiversity across large areas.. Biodiversity offsetting is a system used predominantly by planning authorities and developers to fully compensate for biodiversity impacts associated with economic development, through the planning process.
To meet the objective of rate adequacy, the rates should be responsive over time in comparison with changing economic conditions and loss exposures. Finally, to reduce the frequency and severity of losses, the rating system should encourage loss control activities. Loss control is important in insurance because it tends to keep insurance ...
The Cost-loss model considers one forecast prior to an event, while the Extended cost-loss model considers two forecasts at different times prior to the event. The Extended cost-loss model is an example of a dynamic decision model, and links the cost-loss model to the Bellman equation and Dynamic programming.
The chain-ladder or development [1] method is a prominent [2] [3] actuarial loss reserving technique. The chain-ladder method is used in both the property and casualty [1] [4] and health insurance [5] fields. Its intent is to estimate incurred but not reported claims and project ultimate loss amounts. [5]
The above analysis of one target variable and one policy tool can readily be extended to multiple targets and tools. [2] In this case a key result is that, unlike in the absence of multiplier uncertainty, it is not superfluous to have more policy tools than targets: with multiplier uncertainty, the more tools are available the lower expected loss can be driven.
Free AMAP: Sequence annealing: Both: Global: A. Schwartz and L. Pachter: 2006: BAli-Phy: Tree+multi-alignment; probabilistic-Bayesian; joint estimation: Both + Codons: Global: BD Redelings and MA Suchard: 2005 (latest version 2018) Free, GPL: Base-By-Base Java-based multiple sequence alignment editor with integrated analysis tools: Both: Local ...