Browsing by Subject "pairs"

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Collision-Induced Absorption By Supermolecular Complexes From A New Potential Energy And Induced Dipole Surface, Suited For Calculations Up To Thousands Of Kelvin
(2010-06) Abel, M.; Frommhold, L.; Wang, F.; Gustafsson, M.; Li, X. P.; Hunt, K. L. C.; Abel, Martin; Frommhold, Lothar
Absorption by pairs of H-2 molecules is an important opacity source in the atmospheres of the outer planets, and thus of special astronomical interest. The emission spectra of cool white dwarf stars differ significantly from the expected blackbody spectra, amongst other reasons due to absorption by H-2 H-2, H-2 He, and H-2-H collisional complexes in the stellar atmospheres. To model the radiative processes in these atmospheres, which have temperatures of several thousand kelvin, one needs accurate knowledge of the induced dipole (ID) and potential energy surfaces (PES) of such collisional complexes. These come from quantum-chemical calculations with the H-2 bonds stretched or compressed far from equilibrium. Laboratory measurements of collision-induced (CI) absorption exist only at much lower temperature. For H-2 pairs at room temperature, the calculated spectra of the rototranslational band, the fundamental band, and the first overtone match the experimental data very well. In addition, with the newly obtained IDS it became possible to reproduce the measurements in the far blue wing of the rototranslational spectrum of H-2 at 77.5 K, as well as at 300 K. Similarly good agreement between theory and measurement is seen in the fundamental band of molecular deuterium at room temperature. Furthermore, we also show the calculated absorption spectra of H-2-He at 600 K and of H-2-H-2 at 2,000 K, for which there are no experimental data for comparison.
Critical Assessment of Sequence-Based Protein-Protein Interaction Prediction Methods that do not Require Homologous Protein Sequences
(2009-12) Park, Yungki; Park, Yungki
Protein-protein interactions underlie many important biological processes. Computational prediction methods can nicely complement experimental approaches for identifying protein-protein interactions. Recently, a unique category of sequence-based prediction methods has been put forward - unique in the sense that it does not require homologous protein sequences. This enables it to be universally applicable to all protein sequences unlike many of previous sequence-based prediction methods. If effective as claimed, these new sequence-based, universally applicable prediction methods would have far-reaching utilities in many areas of biology research. Results: Upon close survey, I realized that many of these new methods were ill-tested. In addition, newer methods were often published without performance comparison with previous ones. Thus, it is not clear how good they are and whether there are significant performance differences among them. In this study, I have implemented and thoroughly tested 4 different methods on large-scale, non-redundant data sets. It reveals several important points. First, significant performance differences are noted among different methods. Second, data sets typically used for training prediction methods appear significantly biased, limiting the general applicability of prediction methods trained with them. Third, there is still ample room for further developments. In addition, my analysis illustrates the importance of complementary performance measures coupled with right-sized data sets for meaningful benchmark tests. Conclusions: The current study reveals the potentials and limits of the new category of sequence-based protein-protein interaction prediction methods, which in turn provides a firm ground for future endeavours in this important area of contemporary bioinformatics.