Sentence examples for microbial detection arrays from inspiring English sources

Microbial detection arrays can also be used to check isolate stocks and vaccines for adventitious contaminants [ 9].

Statistical algorithms that can analyze data from microbial detection arrays and provide easily interpretable results are absolutely required in order for these efforts to succeed.

Also, the requirement that parameters be fitted to data from arrays hybridized to each candidate target limits its usefulness for broad-spectrum microbial detection arrays.

These microbial detection arrays occupy a middle ground between low cost, narrowly focused assays such as multiplex PCR and more expensive, broad-spectrum technologies like high-throughput sequencing.

The analysis method described here differs in several key ways from previous statistical approaches to analyze microbial detection arrays, such as E-Predict [ 24] and GreeneLAMP [ 12].

Analysis and visualization software will become especially important as microbial detection arrays move from the research environment to widespread medical, industrial and military use.

Microbial Detection Array (MDA) detects viruses using probes against genomic DNA sequence within 24 hours.

Several promising approaches to microbial detection array design and analysis have been tested during the past decade.

Initial versions of the Lawrence Livermore Microbial Detection Array (LLMDA) contained target probes for all bacteria and viruses (pathogenic and otherwise) for which full genome sequences were available.

We designed a pan-Microbial Detection Array (MDA) to detect all known viruses (including phages), bacteria and plasmids and developed a novel statistical analysis method to identify mixtures of organisms from complex samples hybridized to the array.

Currently, most microarrays used for microbial detection are spotted arrays that use redundant oligonucleotides as independent probes.