Exploring Bioinformatics Opportunities for Identification and Study of Medicinal Plants: A Comprehensive Review DOI Open Access

gopal gupta,

Shan Khatoon,

Rajnish singh

et al.

Published: May 13, 2024

Medicinal plants have been a cornerstone of traditional medicine systems for centuries, offering vast array bioactive compounds with therapeutic potential. However, the identification, characterization, and elucidation pharmacological properties these often challenging due to their complex chemical composition diverse biological activities. Bioinformatics, its interdisciplinary approach combining biology, computer science, information technology, presents powerful toolkit systematic study medicinal plants. This review provides an overview bioinformatics methodologies resources that can facilitate phytochemical analysis, investigation, conservation It highlights integration omics technologies, computational algorithms, database resources, molecular modeling techniques in advancing our understanding plants' potential applications drug discovery development.

Language: Английский

Rapid and non-destructive identification of Panax ginseng origins using hyperspectral imaging, visible light imaging, and X-ray imaging combined with multi-source data fusion strategies DOI

Jiacong Ping,

Zehua Ying,

Nan Hao

et al.

Food Research International, Journal Year: 2024, Volume and Issue: 192, P. 114758 - 114758

Published: July 14, 2024

Language: Английский

Citations

15

MTJNet: Multi-task joint learning network for advancing medicinal plant and leaf classification DOI
Shubham Sharma, Manu Vardhan

Knowledge-Based Systems, Journal Year: 2024, Volume and Issue: 299, P. 112147 - 112147

Published: June 17, 2024

Language: Английский

Citations

11

Rapid determination of residual pefloxacin in mutton based on hyperspectral imaging and data fusion DOI
Hui Li, Fujia Dong,

Yu Lv

et al.

Journal of Food Composition and Analysis, Journal Year: 2024, Volume and Issue: 132, P. 106285 - 106285

Published: May 2, 2024

Language: Английский

Citations

9

Application of ATR-FTIR and FT-NIR spectroscopy coupled with chemometrics for species identification and quality prediction of boletes DOI Creative Commons

Chuanmao Zheng,

Jieqing Li, Honggao Liu

et al.

Food Chemistry X, Journal Year: 2024, Volume and Issue: 23, P. 101661 - 101661

Published: July 15, 2024

Language: Английский

Citations

9

Effect of drying temperature on composition of edible mushrooms: Characterization and assessment via HS-GC-MS and IR spectral based volatile profiling and chemometrics DOI Creative Commons

Chuanmao Zheng,

Jieqing Li, Honggao Liu

et al.

Current Research in Food Science, Journal Year: 2024, Volume and Issue: 9, P. 100819 - 100819

Published: Jan. 1, 2024

Edible wild mushrooms are one of the popular ingredients due to their high quality and unique flavor nutrients. To gain insight into effect drying temperature on its composition, 86 Boletus bainiugan were divided 5 groups dried at different temperatures. Headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) was used for identification volatile organic compounds (VOCs) bainiugan. The 21 differential VOCs that distinguish temperatures identified. 65 °C retained more VOCs. There differences in types content temperatures, proteins, polysaccharides, crude fibers, fats. Fourier transform near-infrared (FT-NIR) spectroscopy, infrared (FTIR) two-dimensional correlation spectroscopy (2DCOS) images successfully characterized chemical composition Partial least squares discriminant analysis (PLS-DA) verified variability with coefficient determination (R2) = 0.95 predictive performance (Q2) 0.75 92.31% accuracy. Next, provides a fast efficient assessment nutrients (proteins, fats).

Language: Английский

Citations

6

Multi-spectra combined with Bayesian optimized machine learning algorithms for rapid and non-destructive detection of adulterated functional food Panax notoginseng powder DOI

Huanhuan Guan,

Zhi‐Tong Zhang,

Lei Bai

et al.

Journal of Food Composition and Analysis, Journal Year: 2024, Volume and Issue: 133, P. 106412 - 106412

Published: June 7, 2024

Language: Английский

Citations

5

New vision for TCM quality control: Elemental fingerprints and key ingredient combination strategy for identification and evaluation of TCMs DOI Creative Commons
Yaolei Li, Jing Fan,

Hongyu Jin

et al.

European Journal of Medicinal Chemistry, Journal Year: 2024, Volume and Issue: 281, P. 117006 - 117006

Published: Oct. 30, 2024

Language: Английский

Citations

4

Differentiation of Citri Reticulatae Pericarpium varieties via HPLC fingerprinting of polysaccharides combined with machine learning DOI
Meng Zhong,

Meng-ning Li,

Wei Zou

et al.

Food Chemistry, Journal Year: 2025, Volume and Issue: unknown, P. 143053 - 143053

Published: Jan. 1, 2025

Language: Английский

Citations

0

Research Approaches for the Discovery of Trypanocidal Molecular Prototypes from Plants DOI Creative Commons
Aboagye Kwarteng Dofuor

Natural Product Communications, Journal Year: 2025, Volume and Issue: 20(1)

Published: Jan. 1, 2025

In the absence of vaccines, chemotherapy remains a viable alternative for control African trypanosomiasis. To facilitate eradication trypanosomiasis, there is need to pay attention chemotherapeutic potential secondary metabolites obtained from natural sources. Despite increasing level paid towards pharmacological and medicinal properties trypanocidal molecular prototypes plants, integrative synthesis research methods relevant this progress lacking. Furthermore, applications machine learning in discovery plant-derived antitrypanosomal have not been well explored. The aim study thus provide critical appraisal plant context made, as highlight standard emerging investigative tools applicable drug process. It explores phytochemical, antitrypanosomals light traditional approaches. vitro, silico, vivo strategies investigations that may be employed are highlighted. Finally, promising particular benefit future also discussed. These insights ultimately optimization, target identification clinical development process against

Language: Английский

Citations

0

FT-NIR Spectra of Different Dimensions Combined with Machine Learning and Image Recognition for Origin Identification: An Example of Panax notoginseng DOI Creative Commons

Zhi‐Tian Zuo,

Yuanzhong Wang, Zeng-Yu Yao

et al.

ACS Omega, Journal Year: 2025, Volume and Issue: 10(7), P. 7242 - 7255

Published: Feb. 11, 2025

Panax notoginseng (P. notoginseng) is a traditional medicinal plant with high and economic values. The authenticity of P. often determines its quality, the quality geographical indication (GI)-producing areas usually superior to that other producing areas, which are exploited by unscrupulous traders affect market order. aim this study was characterize identify geographic origin using Fourier transform near-infrared (FT-NIR) spectroscopy, rapid detection combined multivariate analysis. use principal component analysis correlation spectral enabled initial differential characterization identification from different production areas. Then, random forest (RF) support vector machine (SVM) models were established, results show showed second-order derivative preprocessing successive projection algorithm feature extraction achieved 100% classification correctness model training time shortest. Further constructing image recognition model, synchronous two-dimensional spectroscopy (2DCOS) residual convolutional neural network accurate (accuracy 100%) did not require complex artificial process, maximize avoidance errors caused human factors. externally validated set method has strong generalization ability potential for application in

Language: Английский

Citations

0