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In principle, both techniques use a competitive reaction between two different genomic DNA sources.
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To examine the relationships between five different genomic variables, we used an artificial neural-learning-based approach, the self-organizing map (SOM) [ 46].
Based on two different genomic search methods we have found between 1200 and 1300 LTR REs of four distinct families within the Silurana genome, containing at least LTRs and a retrotranscriptase ORF.
Because there were already two different genomic assemblies of G. raimondii (14, 15), syntenic blocks between them were scanned with SyMAP (53).
They detected two different genomic signatures.
Of these, 1000 involve a single random genomic location, and 500 combine fragments from two different genomic locations.
This has been identified in earlier Giardia genome sequencing projects [ 9– 11] and the mismatches represent heterozygous bases due to sequence differences between the four different genomic copies of the Giardia genome, distributed in two nuclei [ 20].
The technique allows for the parallel interrogation of thousands of single feature polymorphisms (SFPs), i.e. differences in the binding intensity to a particular oligonucleotide probe between two different samples of genomic DNA.
As an example, Amaral et al. [ 12] found very different LD patterns between a LW population, Ningxiang (a Chinese breed), and the European wild boar, across three different genomic regions.
Fusion transcripts included many other portions of chr8q, with up to four different genomic loci mapping to a single transcript, a pattern reminiscent of chromothripsis28,29 (Fig. 5d).
Eight different genomic conformations were predicted from the initial finished assembly by assuming that homologous recombination occurs between copies of large repeats in the genome.
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