The variety of antagonistic, predator prey, or competitive effects portrayed in food web analysis are among the multiple types of interactions that occur in natural systems (Thompson 1982) and not necessarily the most important ones.
Fig. 4 The post docking interaction map of most potent antifungal compound 4o (magenta) exhibiting multiple types of interactions involving hydrophobic, π π and electrostatic interactions (red lines) with the significant residues of antifungal target protein N-myristoyl transferase enzyme (light blue) from C. albicans.
Recent research shows that polypyrrole (PPy) has a high extraction efficiency for polar adsorbates because multiple types of interactions with the target compounds are involved, such as the π-π interactions, hydrogen bonding, acid base property, ion-exchange properties, and electrostatic attractions [26-28 [26-28
Characterization of the ethylene receptors indicates that multiple types of interactions play roles in formation of the protein complex.
To what extent signaling is initiated through a single type of receptor ligand interaction versus multiple types of interactions is poorly understood.
In summary, GIENA generalizes the gene-based enrichment method to detect pathways that are dysregulated in diseases based on changes in multiple types of interactions.
In addition, we demonstrate that integrating multiple types of DTIs can significantly outperform other predictions either by simply mixing multiple types of interactions without distinction or using only a single interaction type.
This framework provides a basis for interrogating both the dynamics of multiple types of interactions and gives clues to the regulatory logic of the perturbed networks, both within pathways and across pathways, as opposed to simply identifying the dysregulated players.
How alcohol was addressed by clinic staff How alcohol was addressed by clinic staff Entering into care for HIV/AIDS at the ISS Clinic was a process for patients, involving multiple types of interactions with clinic staff in sequence.
In particular, our results show that integrating different types of DTIs into prediction with distinction can achieve the area under precision-recall curve (AUPR) up to 89.6, which can significantly outperform other predictions either by simply mixing multiple types of interactions without distinction or using only a single interaction type.
