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These biomarker discovery methodologies are based on the idea of finding statistically-detectable differences between phenotypes using patterns of gene expression observed in specific molecular pathways.
Several pharmaceutical companies have developed drug discovery methodologies based on high-throughput in vivo drug screening using small fish models of human diseases.
Scientific complexity of discovery methodologies must therefore increase, which results in increasingly risky, time-consuming, and expensive discovery programs just at a time when economics and regulatory forces are converging to make antibiotics a poor vehicle for R&D investment.
This strategy, if validated, may develop established drug discovery methodologies and also can be helpful for assisted reproductive technology to avoid IVF failure with a remarkable reduction in investment of time and resources.
T-cell antigen discovery methodologies have not kept pace, and there is now an extreme mismatch between our ability to recognize unique antigen-experienced T cells by TCR-seq and our ability to identify their cognate antigens.
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We here describe an in silico, pocket-based drug discovery methodology utilizing the crystal structure of the Ku70/80 heterodimer.
High-throughput screening (HTS) tools have become an important part of drug discovery methodology, allowing parallel performance testing of numerous compounds.
We developed a novel interactive drug discovery methodology known as Protein Chip technology (ProteoChip) as a cutting-edge PPI assay system applicable for unique PPI-targeting therapeutics integrated with computer-aided drug design (CADD).
The relatively recent paradigm of granular computing (GrC) offers an ideal opportunity for a transparent knowledge discovery methodology to be combined with fuzzy logic thereby towards a systematic modelling framework with a focus on the overall transparency of the system.
We previously applied the gene discovery methodology, known as in vivo-induced antigen technology (IVIAT), to identify B. abortus virulence genes up-regulated during infection in elk (Cervis elaphus), and as a result have identified ten loci with gene products potentially important to survival of the pathogen in this host [20].
Includes details on the microsatellite discovery methodology, along with primer sequences.
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