The phrase "alternative module" is correct and usable in written English.
It can be used in contexts where you are referring to a different option or version of a module, often in educational or technical settings.
Example: "The course offers an alternative module for students who wish to explore a different area of study."
Alternatives: "substitute module" or "replacement module".
Several alternative module detection approaches have therefore been developed in order to alleviate these three limitations.
However, the performance of these measures on alternative module detection methods was generally worse than randomly selecting parameters.
Because of limitations of classical clustering methods, numerous alternative module detection methods have been proposed, which improve upon clustering by handling co-expression in only a subset of samples, modelling the regulatory network, and/or allowing overlap between modules.
The alternative module searches for the roadside markings by extracting lines on a dynamic threshold image.
In practice, it is advisable to study how robust the results are with respect to alternative module detection methods.
In our online R software tutorial, we show that our findings are highly robust with respect to alternative module definitions.
For the combined or branched component of a cause-effect (CE) model, multiple alternative modules have been proposed.
We propose a method of generating alternative modules for a plant alarm system based on first-out alarm alternative signals for the combined or branched component of a CE model.
Because polyphenism is the extreme example of how development deviates from a linear genetic blueprint, it demands a genetic explanation for how environmental cues shunt development to hypothetically alternative modules.
All the tissue-related modules were identified using the ISA algorithm proposed by Bergmann et al. [20] which over-performs many traditional clustering approaches in two main aspects: 1) the modules identified by ISA are highly self-consistent; 2) the genes within a module are allowed to be involved in alternative modules [19].
We attempted to identify coexpression modules using an alternative module-finding algorithm developed by Ogata et al. This algorithm detects coexpression modules not only by using PCC cutoff, but also by evaluating density and connectivity of networks.
