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This application compares predicted secondary structures derived from primary protein sequence to a database of solved tertiary structures to predict likelihood of structural match [ 52, 53].
Methods that use static structures to predict function do not take structural dynamics into account.
Structural engineers rely on measurable parameters of corroding RC structures to predict their residual load-bearing capacities.
This work aim to develop a novel computational model based on dislocation structures to predict the flow stress properties of metallic materials.
The method exploits a small random sample of realised FRFs obtained from nominally identical structures to predict corresponding FRF bounds for a substantially larger batch.
For example, clustering algorithms search for groups of similar records, and classification algorithms find data structures to predict the class label of a previously unseen data record according to annotated (classified) training data.
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When comparing our partial gene structures to predicted gene structures based on short read sequencing technologies, however, we find that many of our mappings cannot be reconstructed from short read cDNA sequencing.
Furthermore, we used the resolved ASIC structure to predict structural models for all individual Drosophila ppk subunits.
These standard techniques do not have the high resolution required to measure molecular mobility and structure to predict stability and rank-order.
The second case study examines a discrete periodic structure to predict the acoustic performance of a sonic crystal noise barrier.
For this analysis, a thermal resistor network model was combined with a 3D finite element submodel of an LED structure to predict system and die level temperatures.
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