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In our research, we saw methods that have been used for centuries, such as gardening techniques like grafting inoculated matter together to form different types of structures.
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In each of the three models we studied (see Methods), we assume a maximum distance dmax between the two bound factors, beyond which there is no interaction.
This figure presents the average F1 of positive and negative class and as we can see, methods use to achieve better prediction performance on positive messages.
Most of the edge-effect variables we evaluated (see Methods) exhibited pronounced spatial and temporal variability.
We assembled (see Methods) 5×12 = 60 groups of genes (one for each of 5 motifs M studied over 12 non-over lapping windows W of 100 bp).
A small minority of this group also includes species found in the Atlantic Ocean with greater geographic ranges, an artifact of the conservative linear approach we utilize (see methods).
Note that in the model we use (see Methods) the transition from subthreshold oscillations to spikes in isolated cells also occurs via a canard mechanism [10], [11].
Under the assumptions we make (see Methods), our decoder is optimal in the maximum likelihood sense.
Specifically, we first identified FCSs from 1000 in silico metabolic genotypes viable in all of the 89 carbon source environments we consider (see Methods).
Genome compaction among fish is readily observable (Additional file 2: Figure S2) for both protein-coding and mixed blocks, hence we normalise (see Methods) for total genome size.
We present our results using the method that we found to be most interpretable, which we summarize here (see Methods for full details on the different methods).
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