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.
We are currently working on an alternative module that will enable the student's to ask open-ended questions also in Web-SP, but still allowing an easy case creation.
In contrast to the traditional concept of a module as a group of cohesively interacting proteins, Pinkert et al. presented an alternative module finding approach of decomposing a network into functional roles, which based on a self-consistent definition independent of any prior knowledge of functional modules [ 8].
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].
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.
