High dimensional surrogacy: computational aspects of an upscaled analysis.

Identification of genomic biomarkers is an important area of research in the context of drug discovery experiments. These experiments typically consist of several high dimensional datasets that contain information about a set of drugs (compounds) under development. This type of data structure introduces the challenge of multi-source data integration. High-Performance Computing (HPC) has become an important tool for everyday research tasks. In the context of drug discovery, high dimensional multi-source data needs to be analyzed to identify the biological pathways related to the new set of drugs under development. In order to process all information contained in the datasets, HPC techniques are required. Even though R packages for parallel computing are available, they are not optimized for a specific setting and data structure. In this article, we propose a new framework, for data analysis, to use R in a computer cluster. The proposed data analysis workflow is applied to a multi-source high dimensional drug discovery dataset and compared with a few existing R packages for parallel computing.

HPLC Fingerprint and Quantitative Analysis of 6 Components of Fructus Trichosanthis and Its Steamed Products / 中国药学杂志

OBJECTIVE: To study the chemical fingerprint features and the quantitative analysis of 6 components of Fructus Trichosanthis and its steamed products. METHODS: The chemical fingerprints were established by HPLC with 10 batches of Fructus Trichosanthis and their steamed products, and the contents of 5-hydroxymethyl furfural, vanillic acid, rutin, isoquercitrin, quercetin and luteolin in Fructus Trichosanthis and their steamed products were quantitatively analyzed. The similarity of Fructus Trichosanthis and its steamed products was calculated by the correlation coefficient method and the included angle cosine method, and the contents of 6 components were tested by means of calibration curve. RESULTS: The 10 batch of Fructus Trichosanthis similarity was from 0.82 to 0.86, and the 10 batch of Fructus Trichosanthis steamed products similarity was from 0.97 to 0.98, there was significant difference between the two (P < 0.01). Compared with Fructus Trichosanthis, the contents of 5-hydroxymethyl furfural, vanillic acid, quercetin and luteolin content in steamed products showed significant changes (P < 0.05 or P < 0.01). CONCLUSION: Before and after Fructus Trichosanthis steamed, the change of fingerprint feature and changes of the component content provide experimental basis for further studies of Fructus Trichosanthis and its steamed products.

Application of fisher component analysis to study chemical fingerprint feature similarities of fructus trichosanthis and its processed products / 国际药学研究杂志

Objective: To explore whether the basic principle of Fisher component analysis(FCA) can be used in the category analysis of Fructus Trichosanthis fruit and its processed products. Methods: Their fingerprints were established by using HPLC-PDAD, and the standard fingerprints of them were obtained by digitizing with quercetin as the internal reference peak. Then, their chemical fingerprint information was extracted by FCA and classified by quality model, and the classification results were compared with those classified by principal component analysis and standard atlas analysis. Results: Fructus Trichosanthis and its processed products can be accurately divided into two categories by FCA. Conclusion: FCA can extract the implied chemical information in fingerprints, and analyze them accurately.

Application of Fisher component analysis to study chemical fingerprint feature similarities of Fructus Trichosanthis and its processed products / 国际药学研究杂志

Objective To explore whether the basic principle of Fisher component analysis(FCA)can be used in the catego?ry analysis of Fructus Trichosanthis fruit and its processed products. Methods Their fingerprints were established by using HPLC-PDAD,and the standard fingerprints of them were obtained by digitizing with quercetin as the internal reference peak. Then,their chemical fingerprint information was extracted by FCA and classified by quality model,and the classification results were compared with those classified by principal component analysis and standard atlas analysis. Results Fructus Trichosanthis and its processed products can be accurately divided into two categories by FCA. Conclusion FCA can extract the implied chemical information in fin?gerprints,and analyze them accurately.