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In this paper, we review the recent endeavours in this direction, and summarize the existing methodologies and computational tools for network-based analysis of complex diseases and molecular relationships among apparently different disorders and human disease network.
The introduction of molecular markers has facilitated the genetic association analysis of complex diseases in humans, animals and plants.
ReliefF has previously been used in the genetic analysis of complex diseases in this fashion [ 25].
Phenotypic network analysis of complex diseases could provide novel insights into disease susceptibility, disease severity, and genetic mechanisms.
Identification of candidate genes associated with physiological disorders are a fundamental task in the analysis of complex diseases [ 10].
In short, pathway-based analysis has gradually become an advanced way to the analysis of complex diseases [22].
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The plenary lecture by Goncalo Abecasis provided insights into the computational analysis of complex disease loci and finding rare variants associated with disease in human populations.
The contextualisation of high-throughput data sets using large-scale molecular interaction networks is emerging as an increasingly popular bioinformatics approach for the analysis of complex disease.
Results: Olorin is a tool, which integrates gene flow within families with next generation sequencing data to enable the analysis of complex disease pedigrees.
Finally, 25 out of 43 meta-analysis of complex disease-associated variants showed heterogeneity in allelic frequency among human populations [ 18].
In addition, this phenomenon has been observed in other complex diseases, as reported in a recent meta-analysis on the genetic association of complex diseases [ 45].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com