The phrase "ability to generate large" is correct and usable in written English.
It can be used when discussing someone's or something's capacity to produce significant quantities or outputs, often in a technical or analytical context.
Example: "The software's ability to generate large datasets allows researchers to conduct more comprehensive analyses."
Alternatives: "capacity to produce substantial" or "capability to create extensive".
One of the great advantages of next generation sequencing is the ability to generate large genomic datasets for virtually all species, including non-model organisms.
With the advent of Next Generation Sequencing (NGS) technologies, the ability to generate large amounts of sequence data has revolutionized the genomics field.
It was demonstrated that the 624 port design presented in this paper is a high throughput, area time efficient FPGA optimized pseudouniform random number generator with a large period and with the ability to generate large quantities of uniform random numbers from a single seed.
The ability to generate large amounts of genomic data at ever decreasing costs through next-generation sequencing approaches makes it feasible for investigators to move past constraints on genomic information in the early stages of a research project; thus, enabling them to conduct more effective molecular studies in non-model groups.
The ability to generate large numbers of PC skin-engrafted mice will enable the testing of novel pharmacological or gene-based therapies for this as yet untreatable disease.
Modern 3D-digitization systems, which are employed by reverse engineering (RE), feature the ever-growing scanning speed, with the ability to generate large quantity of points in a unit of time.
The performance of a thickener feedwell depends not only on its ability to generate large-sized aggregates from feed particles but also on aggregate density.
Reducing the sample volume from previously hundreds of μl [22,41] to a few μl enables the ability to generate larger volumes of data from the same total sample volume and hence the conservation of precious samples.
The increasing ability to generate large-scale, quantitative proteomic data has brought with it the challenge of analyzing such data to discover the sequence elements that underlie systems-level protein behavior.
However, the development of tools to analyze high-throughput data has lagged behind our ability to generate larger and larger data-sets, and despite some standardization efforts, custom file formats continue to proliferate.
Clearly, our technological abilities to generate large amounts of data from molecular systems have advanced enormously, but the ability to translate this information for use in the clinic remains elusive due to a number of factors.
