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Describing complex ecosystems as networks of interacting components and explaining the structure of those interaction networks is an essential part of understanding the role of biodiversity in the function and robustness of ecological communities [1], [2].
In those interaction networks, neurons typically have very diverse projection target specificity.
In addition, those interaction coefficients mentioned in the above studies were not tested against experimental data.
We identify those interaction issues necessary to foster creativity in automated process design.
Those turn out to be quite useful in this study to analyze the relative importance of those interaction energies in determining the solvation energy.
We included all those interaction types with more than 10 distinct human domain-peptide pairs and, at least, one peptide of 10 or more residues, namely Cyclin_N, Hormone_recep, MATH, PDZ, SH2, SH3_1 class I and SH3_1 class II.
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Robots are walking, mobile sensors that can sense their environment, interact, and learn from those interactions.
Scientists studying the Earth's climate work out descriptions of how humans are interacting with the environment, how those interactions cause changes, and how measurements can be made.
From these relations, we extracted the interacting entity (the second term in those interactions).
To what degree do the characters interact with younger people, and how would you characterize those interactions?
People and organizations, he said, are increasingly choosing to interact with one another through digital means that record traces of those interactions.
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