Here we evaluate the performance of a molecular dynamics based method for predicting the binding affinities of different types of human thrombin inhibitors.
Considering limited available information on uncertainties in structural - acoustic coupled systems, two methods namely the vertex method and the Legendre orthogonal polynomial based method for predicting their dynamic behavior are developed based on the Statistical Energy Analysis SEAapproachapproach
In this paper, we first propose GM-SMCC, an effective and novel semi-supervised multi-label collective classification based method for predicting functional properties of proteins.
We show that very different structure and ligand based methods for predicting drug-target interactions can be combined effectively using data fusion, outperforming any single method in ranking of actives.
We believe that many of the existing k-mer based methods for predicting TF-DNA interactions, which often involve filtering, normalization, and transformation of the binding data, can be combined with the key idea proposed in this paper to obtain a more accurate model.
Results: This study presents a novel constraint-based method for predicting subcellular localization of enzymes based on their embedding metabolic network, relying on a parsimony principle of a minimal number of cross-membrane metabolite transporters.
For example, Weib and Menzel (2008) compared the Priestley–Taylor (PT) method, two methods based on the Penman Monteith (PM) equation and the Hargreaves method, a temperature-based method for predicting PET in a global-scale hydrologic method.
Here, we present a docking-based method for predicting protein-peptide complex structures, referred to as MDockPeP, which starts with the peptide sequence and globally docks the all-atom, flexible peptide onto the protein structure.
This paper develops a simple, finite element-based method for predicting the elastic flexural-torsional buckling loads of steel I-section members that contain tapered webs, which are fabricated by welding.
In this paper, a homogenization-based method for predicting the viscoelastic properties of layered materials is presented, and the explicit formulae for predicting the viscoelastic relaxation modulus of layered materials are obtained.
