دورية أكاديمية

Graph methods for the investigation of metabolic networks in parasitology

التفاصيل البيبلوغرافية
العنوان: Graph methods for the investigation of metabolic networks in parasitology
المؤلفون: Cottret, Ludovic, Jourdan, Fabien
المساهمون: Xénobiotiques, Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)
المصدر: ISSN: 0031-1820.
بيانات النشر: HAL CCSD
Cambridge University Press
سنة النشر: 2010
المجموعة: Université Toulouse III - Paul Sabatier: HAL-UPS
مصطلحات موضوعية: METABOLISM, METABOLIC NETWORK, GRAPH MODELLING, PARASITOLOGIE, [SDV]Life Sciences [q-bio]
الوصف: International audience ; Recently, a way was opened with the development of many mathematical methods to model and analyze genome-scale metabolic networks. Among them, methods based on graph models enable to us quickly perform large-scale analyses on large metabolic networks. However, it could be difficult for parasitologists to select the graph model and methods adapted to their biological questions. In this review, after briefly addressing the problem of the metabolic network reconstruction, we propose an overview of the graph-based approaches used in whole metabolic network analyses. Applications highlight the usefulness of this kind of approach in the field of parasitology, especially by suggesting metabolic targets for new drugs. Their development still represents a major challenge to fight against the numerous diseases caused by parasites.
نوع الوثيقة: article in journal/newspaper
اللغة: English
العلاقة: hal-02661590; https://hal.inrae.fr/hal-02661590Test; PRODINRA: 44428; WOS: 000280418400009
DOI: 10.1017/S0031182010000363
الإتاحة: https://doi.org/10.1017/S0031182010000363Test
https://hal.inrae.fr/hal-02661590Test
رقم الانضمام: edsbas.7FC4D71
قاعدة البيانات: BASE