The available databases that catalogue information on traditional Chinese medicines are reviewed in terms of their content and utility for in-silico research on Chinese herbal medicines, as too are the various protein database resources, and the software available for use in such studies. The software available for bioinformatics and 'omics studies of Chinese herbal medicines are summarised, and a critical evaluation given of the various in-silico methods applied in screening Chinese herbal medicines, including classification trees, neural networks, support vector machines, docking and inverse docking algorithms. Recommendations are made regarding any future in-silico studies of Chinese herbal medicines.

In-silico studies in Chinese herbal medicines' research: evaluation of in-silico methodologies and phytochemical data sources, and a review of research to date / D. J. Barlow, A. Buriani, T. Ehrman, E. Bosisio, I. Eberini, P.J. Hylands. - In: JOURNAL OF ETHNOPHARMACOLOGY. - ISSN 0378-8741. - 140:3(2012 Apr 10), pp. 526-534.

In-silico studies in Chinese herbal medicines' research: evaluation of in-silico methodologies and phytochemical data sources, and a review of research to date

E. Bosisio;I. Eberini
Penultimo
;
2012

Abstract

The available databases that catalogue information on traditional Chinese medicines are reviewed in terms of their content and utility for in-silico research on Chinese herbal medicines, as too are the various protein database resources, and the software available for use in such studies. The software available for bioinformatics and 'omics studies of Chinese herbal medicines are summarised, and a critical evaluation given of the various in-silico methods applied in screening Chinese herbal medicines, including classification trees, neural networks, support vector machines, docking and inverse docking algorithms. Recommendations are made regarding any future in-silico studies of Chinese herbal medicines.
Settore BIO/15 - Biologia Farmaceutica
Good Practice in Traditional Chinese Medicine Research in the Post-genomic Era
Article (author)
File in questo prodotto:
File Dimensione Formato  
1-s2.0-S0378874112000542-main.pdf

accesso aperto

Tipologia: Publisher's version/PDF
Dimensione 365.52 kB
Formato Adobe PDF
365.52 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/178689
Citazioni
  • ???jsp.display-item.citation.pmc??? 13
  • Scopus 50
  • ???jsp.display-item.citation.isi??? 37
social impact