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Tatsuya and Fukagawa [35, 36] proposed a dynamic programming algorithm for inferring a chemical structure from a descriptor.
Is this also true of those cladists who see a particular algorithm for inferring phylogenies from phenotypic data as the one way to practice objective taxonomy?
Closely related to our work is that of Gomez et al. [13], who develop an algorithm for inferring the topology of the network over which a diffusion propagates.
This approach has two significant novel features: a fully automatic ontology-based query expansion algorithm for inferring and aggregating user intention based on their original short query, and another "ambiguity removal" procedure for correcting inappropriate user query terms.
Although (absent horizontal gene transfer and speciation by hybridization) Hennig's goal is objective and unambiguous, using the algorithm for inferring such phylogenies requires subjective judgments ranging from assessing simplicity to selecting appropriate outgroups and characteristics to analyze.
In this paper, we prove that τ is a suffix tree if and only if it is realized by a string S of length n−1, and we give a linear-time algorithm for inferring S when the first letter on each edge is known.
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Results: In this article, we present an algorithmic framework, which we term DELISHUS, that implements three exact algorithms for inferring regions of hemizygosity containing genomic deletions of all sizes and frequencies in SNP genotype data.
The use of mathematical algorithms for inferring rheological parameters from properties of flow field statistics is explored.
Algorithms for inferring ancestral sequences and general considerations for designing synthetic genes are discussed in detail in the chapter.
In order to capitalize on pre-existing efficient algorithms for inferring the most likely derivation of a string for a given grammar, all SCFGs were expressed in Chomsky normal form (CNF) such that a non-terminal symbol could be replaced only by either a pair of non-terminal symbols or a single terminal symbol [20].
Using real data, we also compared the proposed method with various reverse-engineering algorithms for inferring gene networks.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com