Your English writing platform
Discover LudwigSuggestions(5)
Exact(2)
Cluster analysis is a fundamental problem in pattern recognition where objects are categorized into groups or clusters based on pairwise similarities between those objects such that two criteria, homogeneity and separation, are achieved [21].
In contrast, TRIBES and OFAM use the Markov Cluster (MCL) algorithm for protein family assignment based on pairwise similarities [ 27].
Similar(58)
There are many different algorithms for computing similarity measures between compounds and for aggregating compounds into clusters based on pairwise similarity measures, leading to arbitrarily many different classification hierarchies, even given the same compound collection as input.
Recently, Gray et al. [112] proposed a multi-modality classification framework, in which manifolds are constructed based on pairwise similarity measures derived from random forest classifiers, and achieved classification accuracies of 89 % between AD and NC, and 75%% between MCI and NC.
The algorithm for detecting orthologous relationships is based on pairwise similarity scores which are by default calculated with BLASTP.
In this approach, sequences are grouped ("clustered") based on pairwise similarity measures such as BLAST E-values [ 18].
Inparanoid is based on pairwise similarity values calculated in four ways: A/B, B/A, A/A, B/B.
CLANS is a Java tool to visualize and analyze protein sequence similarity based on pairwise similarity (BLAST) and well suited for the analysis of large sets of sequences.
Since SSIM is based on pairwise similarity values of genes, there is room for further improvement by integrating additional quantitative similarity measures.
The algorithm for assigning orthologous relationships is based on pairwise similarity scores which are by default calculated with the BLASTP program.
The algorithm for detecting orthologous relationships is based on pairwise similarity scores which are by default calculated with the BLASTP program.
More suggestions(2)
Write better and faster with AI suggestions while staying true to your unique style.
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