Literature DB >> 23106776

Efficacy prediction of jamu formulations by PLS modeling.

Farit M Afendi1, Latifah K Darusman, Aki Hirai Morita, Md Altaf-Ul-Amin, Hiroki Takahashi, Kensuke Nakamura, Ken Tanaka, Shigehiko Kanaya.   

Abstract

Indonesian herbal medicines made from mixtures of several plants are called "Jamu." The efficacy of a particular Jamu is determined by its ingredients i.e. the composition of the plants. Thus, we modeled the ingredients of Jamu formulas using Partial Least Squares Discriminant Analysis (PLS-DA) in order to predict their efficacy. The plants used in each Jamu medicine served as the predictors, whereas the efficacy of each Jamu provided the responses. Utilizing response predictions obtained from PLS-DA, we predicted the efficacies of Jamu formulations using two methods: maximum response prediction and maximum probability. In predictions of Jamu efficacy, the maximum response prediction method produced a smaller error than that the maximum probability method. Furthermore, utilizing the PLS-DA coefficient matrix, we determined the efficacy for which a plant is most useful, based on its largest coefficients.

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Year:  2013        PMID: 23106776     DOI: 10.2174/1573409911309010005

Source DB:  PubMed          Journal:  Curr Comput Aided Drug Des        ISSN: 1573-4099            Impact factor:   1.606


  2 in total

1.  Bipartite graph search optimization for type II diabetes mellitus Jamu formulation using branch and bound algorithm.

Authors:  Wisnu Ananta Kusuma; Zulfahmi Ibnu Habibi; Muhammad Fahmi Amir; Aulia Fadli; Husnul Khotimah; Vektor Dewanto; Rudi Heryanto
Journal:  Front Pharmacol       Date:  2022-08-11       Impact factor: 5.988

2.  Supervised clustering based on DPClusO: prediction of plant-disease relations using Jamu formulas of KNApSAcK database.

Authors:  Sony Hartono Wijaya; Husnawati Husnawati; Farit Mochamad Afendi; Irmanida Batubara; Latifah K Darusman; Md Altaf-Ul-Amin; Tetsuo Sato; Naoaki Ono; Tadao Sugiura; Shigehiko Kanaya
Journal:  Biomed Res Int       Date:  2014-04-07       Impact factor: 3.411

  2 in total

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