UNaProd: A Universal Natural Product Database for <i>Materia Medica</i> of Iranian Traditional Medicine

Naghizadeh, Ayeh; Hamzeheian, Donya; Akbari, Shaghayegh; Mohammadi, Fahimeh; Otoufat, Tohid; Asgari, Saeme; Zarei, Azadeh; Noroozi, Samane; Nasiri, Najmeh; Salamat, Mahdi; Karbalaei, Reza; Mirzaie, Mehdi; Rezaeizadeh, Hossein; Karimi, Mehrdad; Jafari, Mohieddin

doi:10.1155/2020/3690781

Cited by 13 publications

(11 citation statements)

References 39 publications

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“…The query of database contents by one or more keywords is possible. Classes are linked to their instances in UNaProd database to create a knowledge-base of materia medica of Persian medicine [ 15 ].…”

Section: Utility and Discussionmentioning

confidence: 99%

“…They are described by their identity, Mizaj, actions and medicinal uses, dosage, adverse effects, substitutes, and corrigents. In a recent project, descriptions of the medicinal substances in Makhzan al-Advieh along with their scientific names and common names have been gathered in a database called UnaProd (Universal Natural Product Database) available at http://unaprod.com [ 15 ].…”

Section: Construction and Contentmentioning

confidence: 99%

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IrGO: Iranian traditional medicine General Ontology and knowledge base

et al. 2021

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Background Iranian traditional medicine, also known as Persian Medicine, is a holistic school of medicine with a long prolific history. It describes numerous concepts and the relationships between them. However, no unified language system has been proposed for the concepts of this medicine up to the present time. Considering the extensive terminology in the numerous textbooks written by the scholars over centuries, comprehending the totality of concepts is obviously a very challenging task. To resolve this issue, overcome the obstacles, and code the concepts in a reusable manner, constructing an ontology of the concepts of Iranian traditional medicine seems a necessity. Construction and content Makhzan al-Advieh, an encyclopedia of materia medica compiled by Mohammad Hossein Aghili Khorasani, was selected as the resource to create an ontology of the concepts used to describe medicinal substances. The steps followed to accomplish this task included (1) compiling the list of classes via examination of textbooks, and text mining the resource followed by manual review to ensure comprehensiveness of extracted terms; (2) arranging the classes in a taxonomy; (3) determining object and data properties; (4) specifying annotation properties including ID, labels (English and Persian), alternative terms, and definitions (English and Persian); (5) ontology evaluation. The ontology was created using Protégé with adherence to the principles of ontology development provided by the Open Biological and Biomedical Ontology (OBO) foundry. Utility and discussion The ontology was finalized with inclusion of 3521 classes, 15 properties, and 20,903 axioms in the Iranian traditional medicine General Ontology (IrGO) database, freely available at http://ir-go.net/. An indented list and an interactive graph view using WebVOWL were used to visualize the ontology. All classes were linked to their instances in UNaProd database to create a knowledge base of ITM materia medica. Conclusion We constructed an ontology-based knowledge base of ITM concepts in the domain of materia medica to help offer a shared and common understanding of this concept, enable reuse of the knowledge, and make the assumptions explicit. This ontology will aid Persian medicine practitioners in clinical decision-making to select drugs. Extending IrGO will bridge the gap between traditional and conventional schools of medicine, helping guide future research in the process of drug discovery.

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Section: Utility and Discussionmentioning

confidence: 99%

Section: Construction and Contentmentioning

confidence: 99%

IrGO: Iranian traditional medicine General Ontology and knowledge base

et al. 2021

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“…This work showed the potential to integrate traditional and modern medicine at both phenotypic and molecular levels toward phenotype-based drug discovery. Another example was the UNaProd database which contains information concerning 3,411 natural products used in Iranian traditional medicine (ITM) ( Naghizadeh et al., 2020 ).…”

Section: Using Clustering To Improve Patient Stratificationsmentioning

confidence: 99%

Unsupervised Learning and Multipartite Network Models: A Promising Approach for Understanding Traditional Medicine

et al. 2020

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The ultimate goal of precision medicine is to determine right treatment for right patients based on precise diagnosis. To achieve this goal, correct stratification of patients using molecular features and clinical phenotypes is crucial. During the long history of medical science, our understanding on disease classification has been improved greatly by chemistry and molecular biology. Nowadays, we gain access to large scale patientderived data by high-throughput technologies, generating a greater need for data science including unsupervised learning and network modeling. Unsupervised learning methods such as clustering could be a better solution to stratify patients when there is a lack of predefined classifiers. In network modularity analysis, clustering methods can be also applied to elucidate the complex structure of biological and disease networks at the systems level. In this review, we went over the main points of clustering analysis and network modeling, particularly in the context of Traditional Chinese medicine (TCM). We showed that this approach can provide novel insights on the rationale of classification for TCM herbs. In a case study, using a modularity analysis of multipartite networks, we illustrated that the TCM classifications are associated with the chemical properties of the herb ingredients. We concluded that multipartite network modeling may become a suitable data integration tool for understanding the mechanisms of actions of traditional medicine.

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“…One of the best and most comprehensive resources of ITM, this semistructured encyclopedia includes 1741 principal herbal, animal, and mineral preliminary monographs. Drugs are described by their identity, Mizaj, actions and medicinal uses, dosage, adverse effects, substitutes, and refinements [15] Ontology creation Protégé 5.5.0, which supports the latest Web Ontology Language (OWL) specification and is the most extensively used editor for development and management of ontologies [16] was used to construct the ontology of Mizaj. The principles of ontology development provided by the OBO Foundry (http://obofoundry.github.io/principles/fp-000-summary.html) were used.…”

Section: Resourcementioning

confidence: 99%

“…The query of database contents by one or more keywords is also provided for users. Both Mizaj types and degrees are linked to their instances in UNaProd to create a knowledge-base of Mizaj [15].…”

Section: Web Interfacementioning

confidence: 99%

Revisiting Temperaments with a Fine-Tuned Categorization Using Iranian Traditional Medicine General Ontology

Naghizadeh¹,

Hamzeheian²,

Akbari³

et al. 2019

Preprint

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Background: Iranian traditional medicine is a holistic school of medicine with a long prolific history. It describes numerous concepts and the relationships between them. However, no unified terminology has been proposed for the concepts of this medicine up to the present time. Considering the extensive use of concepts in the numerous textbooks written by the scholars over centuries, comprehending the totality of the terminology is obviously a very challenging task. To resolve this issue and overcome the obstacles, and code the concepts in a reusable manner, constructing an ontology of the concepts of Iranian traditional medicine seems a necessity.Methods: Makhzan al-Advieh, an encyclopedia of materia medica compiled by Mohammad Hossein Aghili Khorasani, was selected as the resource to create an ontology of Mizaj. The steps followed to accomplish this task included (1) compiling the list of classes for Mizaj; (2) arranging the classes in taxonomy; (3) determining object properties and their cardinalities; (4) specifying annotation properties including codes, labels, synonyms, and definitions for each concept; (5) reviewing the fields pertaining to Mizaj of all monographs in Makhzan al-Advieh. The ontology was created using Protégé with adherence to the principles of ontology development provided by the Open Biological and Biomedical Ontology (OBO) foundry. Results: Mizaj ontology was constructed with a final inclusion of 105 classes, three object properties, and 1078 axioms in the Iranian Traditional Medicine General Ontology database, IrGO, freely available at http://jafarilab.com/irgo/. An indented tree view and an interactive graph view using WebVOWL were used to visualize the ontology. All classes were linked to their instances in the UNaProd database to create a knowledge-base of Mizaj. Conclusion: We constructed an ontology-based knowledge base of ITM concepts of Mizaj in the domain of materia medica to help offer a shared and common understanding of this concept, enable reuse of the knowledge, and make the assumptions explicit. Extending IrGO will bridge the gap between traditional and conventional schools of medicine and help guide future research on new treatment options.

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UNaProd: A Universal Natural Product Database for Materia Medica of Iranian Traditional Medicine

Cited by 13 publications

References 39 publications

IrGO: Iranian traditional medicine General Ontology and knowledge base

IrGO: Iranian traditional medicine General Ontology and knowledge base

Unsupervised Learning and Multipartite Network Models: A Promising Approach for Understanding Traditional Medicine

Revisiting Temperaments with a Fine-Tuned Categorization Using Iranian Traditional Medicine General Ontology

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