The phrase "alternative peaks" is correct and usable in written English.
It can be used in contexts discussing different options or choices, particularly in fields like geography, data analysis, or metaphorical discussions about goals or achievements.
Example: "In our analysis, we identified several alternative peaks that could represent different outcomes for the project."
Alternatives: "alternative summits" or "different peaks".
Inside the NWs, the distribution along the NW radial direction is not uniform, i.e., alternative peaks and valleys appear along the NW axial direction.
We conclude that our pipeline is an effective tool to automatically discover alternative peaks and their differential usage among samples.
Even when there is evidence that populations have reached alternative peaks [ 13, 14], it can be difficult to determine key attributes of the adaptive landscape.
Metaphorically, the transition from juvenile to adult may be viewed as movement between alternative peaks on an individual's adaptive landscape [ 15, 16], where peaks represent correspondence between an individual's phenotypic traits and the local maximum probability of survival.
The pipeline's modularity makes it straightforward to replace PICS with an alternative peak caller, and rGADEM with an alternative motif finder.
Only by changing the environment, such that movement toward the alternative peak became strongly beneficial, did we observe the peak shift.
To assess the face validity of the alternative peak summaries, we assumed that learning could be described by formal learning theory.
Applying our approach to the FANTOM5 dataset [ 10] comprising 156 human primary, HeLa and THP-1 cells [ 11], whose properties are described in Additional file 1, reveals complex patterns of alternative peak usage.
However, MUSCLE has been programmed to enable the user to add alternative peak detection algorithms from a drop-down box, should the current implementation not work well for a particular dataset.
Our SVM classifier can partly solve both these problems, as the SVM is a better alternative than peak height alone for identifying TFBS that are common between cell types, when sufficient training data are available.
Gradualistic evolution (Darwinian evolution, Synthetic Theory) will prevent selection towards such alternative fitness peaks as the lowered fitness associated with allele frequency changes and subsequent phenotypic changes in "valleys" between peaks would prevent directional evolution.
