Sentence examples for interaction verification from inspiring English sources

This work is inspired by our previous work that performs comparative study of classification methods for protein interaction verification system [33].

We attempted two independent approaches to verify select interaction from the Y2H assays, i.e., 1) one bait-one prey interaction verification by recombinant expression of bait and prey genes followed by co-immunoprecipitation and LUminescence-based Mammalian IntERactome (LUMIER) assays and 2) affinity purification/mass spectrometry (AP/MS) assays.

The Ntapi gAHA1 transgenic plants reported here will provide an important tool for AHA1 isoform-specific biochemical analysis, identification of new protein interactions, and verification of interactions previously identified using heterologous techniques.

Because of its natural and non-intrusive interaction, identity verification and recognition using facial information are among the most active and challenging areas in computer vision research.

No interaction: location verification and data access processes are independent, i.e. the Verifier does not rely on data accesses to verify the location.

The approach focuses on modeling of system functions, formalization of functional variability and interactions, and verification whether the preset safety requirements are violated.

Such an attack is implemented differently depending on interactions between the verification process and the data access process: No interaction: location verification and data access processes are independent, i.e. the Verifier does not rely on data accesses to verify the location.

Using RP as a screening tool to find potential multigene interactions, followed by verification by LR, our data demonstrate that multigene interactions predict depression with a greater certainty than single main factor associations.

In summary, diversifying selection in Fusarium is strongly reflected as genomic footprints and can be used to predict a small gene set likely to be involved in host pathogen interactions for experimental verification.

Fig. 4 Block diagram of the proposed scheme: an initial onset detection is performed on the input signal (Data) in the initial onset detection block; static evaluation assesses the performance of the stand-alone algorithm; the user interaction block introduces human verification, interaction and correction; interactive evaluation assesses the performance of the interactive scheme.

Table 3 Technique for Inspecting MoLIC Interaction Diagrams (IMID) E# Verification Items for the MoLIC Element vs Software Requirements Opening point Closing point Verification item 1: Was the element used in the model to represent the start/end of the interaction?