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Combinatorial Drug Assembler CDAA) was developed to identify drug combinations based on enrichment analysis of genomic profile data.
The signatures are comprised of biologically relevant genes and have been evaluated on genomic profile data obtained by multiple institutions using multiple microarray types, reflecting real-world usage.
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One of the central challenges confronting high-throughput cancer genomics is the ability to sift through the deluge of genomic profiling data and discern the true cancer signals from a general background of overall genomic instability.
Future studies would also benefit from the collection of the genomic profiling data, which may provide methods for treatment selection.
We use publically available genomic profiling data generated by the TCGA, together with data on known risk factors for kidney cancer extracted from medical records.
In addition, recent human genomic profiling data also revealed frequent abnormalities in signalling molecules such as EGFR, SPRY2, and PTEN (Taylor et al, 2010).
Finally, most model-based clustering algorithms assume a Gaussian distribution for variation that may not generally be appropriate for genomic profiling data.
High heterogeneity in cancer has been evident since early studies, and approaches to reveal such heterogeneity embedded in genomic profiling data are showing promising results.
The drug functional network is firstly reconstructed based on genomic profiling data of drugs that are available in the Connectivity Map (CMAP) database.
A major challenge in the interpretation of genomic profiling data generated from breast cancer samples is the identification of driver genes as distinct from bystander genes which do not impact tumorigenesis.
Along with the alarming increase in ASD prevalence in the last few decades has come an accumulation of genetic and genomic profiling data [ 42, 49, 50, 74, 81], and yet the group difference between ASD and non-ASD is not obvious by any measure.
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