Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0220723 (PCA)
 4,687 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Nowadays in modern medicine, computer modeling has already become one of key methods toward the discovery of new pharmaceuticals. And virtual screening is a necessary process for this discovery. In the procedure of virtual screening, shape matching is the first step to select ligands for binding protein. In the era of HTS (high throughput screening), a fast algorithm with good result is in demand. Many methods have been discovered to fulfill the requirement. Our method, called "Circular Cone", by finding principal axis, gives another way toward this problem. We use modified PCA (principal component analysis) to get the principal axis, around which the rotation is like whirling a cone. By using this method, the speed of giving score to a pocket and a ligand is very fast, while the accuracy is ordinary. So, the good speed and the general accuracy of our method present a good choice for HTS.
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PMID:Circular Cone: a novel approach for protein ligand shape matching using modified PCA. 2245 4

Fourier Transform InfraRed (FTIR) spectroscopy is a very powerful technique for the characterization of the chemical composition of biomass and its modifications occurring during thermochemical and chemical pretreatments. However, method development is necessary to generate reproducible signals that can be used in combination with multivariate techniques (such as principal component analysis, PCA) to extract meaningful information on biomass composition and bond cleavage. Particle size is a great source of spectra variability in FTIR of biomass. The FTIR signal for an array of particle sizes (2-0.075 mm) was evaluated for hardwood and switchgrass, revealing that 0.5 mm renders higher intensity and spectral reproducibility for both the FTIR sampling techniques investigated (ATR and HTS-XT). Furthermore, the suitability of different signal processing approaches to decrease particle size variability of spectral signals was tested (signal normalization, derivation, and their combination). Normalization showed the highest contribution to enhance ATR spectral reproducibility of both biomass, as statistically shown by the 5-fold decrease of the ratio of signal variance with magnitude of spectral features (VM ratio) with respect to the unprocessed signal. Spectral signal analysis in combination with multivariate statistics (PCA) was used to extract information about the chemical differences between hardwood and switchgrass. The agreement of the biomass composition findings from FTIR-PCA and literature wet chemistry results (acid hydrolysis) contributed to corroborating that FTIR combined with PCA is a clean, quick, efficient, and versatile technique with potential to analyze and characterize biomass composition.
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PMID:Transformations to reduce the effect of particle size in mid-infrared spectra of biomass. 3026 34