The Experts below are selected from a list of 43953 Experts worldwide ranked by ideXlab platform

Peng Tao - One of the best experts on this subject based on the ideXlab platform.

Zhou Jia-ju - One of the best experts on this subject based on the ideXlab platform.

Kazuhiro Saitou - One of the best experts on this subject based on the ideXlab platform.

  • CASE - Image-based automated Chemical Database annotation with ensemble of machine-vision classifiers
    2010 IEEE International Conference on Automation Science and Engineering, 2010
    Co-Authors: Jungkap Park, Kazuhiro Saitou, Gus R. Rosania
    Abstract:

    This paper presents an image-based annotation strategy for automated annotation of Chemical Databases. The proposed strategy is based on the use of a machine vision-based classifier for extracting a 2D Chemical structure diagram in research articles and converting them into standard Chemical file formats, a virtual “Chemical Expert” system for screening the converted structures based on the level of estimated conversion accuracy, and a fragment-based measure for calculation intermolecular similarity. In particular, in order to overcome limited accuracies of individual machine-vision classifier, inspired by ensemble methods in machine learning, it is attempted to use of the ensemble of machine-vision classifiers. For annotation, calculated Chemical similarity between the converted structures and entries in a virtual small molecule Database is used to establish the links. Annotation test to link 121 journal articles to entries in PubChem Database demonstrates that ensemble approach increases the coverage of annotation, while keeping the annotation quality (e.g., recall and precision rates) comparable to using a single machine-vision classifier.

  • Tunable machine vision-based strategy for automated annotation of Chemical Databases.
    Journal of chemical information and modeling, 2009
    Co-Authors: Jungkap Park, Gus R. Rosania, Kazuhiro Saitou
    Abstract:

    We present a tunable, machine vision-based strategy for automated annotation of virtual small molecule Databases. The proposed strategy is based on the use of a machine vision-based tool for extracting structure diagrams in research articles and converting them into connection tables, a virtual “Chemical Expert” system for screening the converted structures based on the adjustable levels of estimated conversion accuracy, and a fragment-based measure for calculating intermolecular similarity. For annotation, calculated Chemical similarity between the converted structures and entries in a virtual small molecule Database is used to establish the links. The overall annotation performances can be tuned by adjusting the cutoff threshold of the estimated conversion accuracy. We perform an annotation test which attempts to link 121 journal articles registered in PubMed to entries in PubChem which is the largest, publicly accessible Chemical Database. Two cases of tests are performed, and their results are compare...

  • Automated extraction of Chemical structure information from digital raster images
    Chemistry Central Journal, 2009
    Co-Authors: Jungkap Park, Gus R. Rosania, Kerby A Shedden, Mandee Nguyen, Kazuhiro Saitou
    Abstract:

    Background To search for Chemical structures in research articles, diagrams or text representing molecules need to be translated to a standard Chemical file format compatible with cheminformatic search engines. Nevertheless, Chemical information contained in research articles is often referenced as analog diagrams of Chemical structures embedded in digital raster images. To automate analog-to-digital conversion of Chemical structure diagrams in scientific research articles, several software systems have been developed. But their algorithmic performance and utility in cheminformatic research have not been investigated. Results This paper aims to provide critical reviews for these systems and also report our recent development of ChemReader – a fully automated tool for extracting Chemical structure diagrams in research articles and converting them into standard, searchable Chemical file formats. Basic algorithms for recognizing lines and letters representing bonds and atoms in Chemical structure diagrams can be independently run in sequence from a graphical user interface-and the algorithm parameters can be readily changed-to facilitate additional development specifically tailored to a Chemical Database annotation scheme. Compared with existing software programs such as OSRA, Kekule, and CLiDE, our results indicate that ChemReader outperforms other software systems on several sets of sample images from diverse sources in terms of the rate of correct outputs and the accuracy on extracting molecular substructure patterns. Conclusion The availability of ChemReader as a cheminformatic tool for extracting Chemical structure information from digital raster images allows research and development groups to enrich their Chemical structure Databases by annotating the entries with published research articles. Based on its stable performance and high accuracy, ChemReader may be sufficiently accurate for annotating the Chemical Database with links to scientific research articles.

Corinne Sanchez - One of the best experts on this subject based on the ideXlab platform.

  • Non-metallurgical iron ore trade in the Roman Mediterranean: an initial synthesis of provenance and use in the case of imperial Colonia Narbo Martius (Narbonne, Aude, France)
    Archaeological and Anthropological Sciences, 2020
    Co-Authors: Gaspard Pagès, Stéphanie Leroy, Corinne Sanchez
    Abstract:

    Since prehistoric times, iron ore has been traded to be used for various purposes as in medicines, pigments, and cosmetics. This non-metallurgical iron ore trade, involving the transportation of ore from the mined deposits via trade hubs to consumption areas, must be viewed as part of a long-distance trading network, such as that for the trading of iron bars. This paper proposes an initial synthesis of (i) the circulation of iron ore fragments in the western Mediterranean and (ii) their multiple non-metallurgical uses in antiquity, as recorded in Naturalis Historia by Pliny the Elder. The basis of our discussion is a heterogeneous, concatenated Chemical Database, set up to assess the sourcing of iron ore fragments discovered in the Roman harbor of Colonia Narbo Martius (Narbonne, Aude, France). Lastly, we advance that in antiquity, iron ore was traded from Elba and possibly from southern Tuscany to Gaul, via the harbor of Colonia Narbo Martius , probably for use in medicine and as a coloring base. However, further development of this topic is required, since this trade is part of a larger, more complex network of distribution.

José L. Medina-franco - One of the best experts on this subject based on the ideXlab platform.

  • The Acid/Base Profile of a Large Food Chemical Database.
    Molecular informatics, 2019
    Co-Authors: Marisa G. Santibáñez-morán, Mariel P. Rico-hidalgo, David T. Manallack, José L. Medina-franco
    Abstract:

    Molecular acid/base properties have a significant influence on membrane permeation, metabolism, absorption, and affinity for biological targets. In particular, ionizable groups are critical in the strength of target-molecule interactions, pharmacokinetics, and toxicity. In this study, we estimated the acid/base properties of the food Chemicals from FooDB, a public compound collection with more than 22,000 compounds. It was found that the food Chemicals have 40.9 % of neutral compounds, which is twice as many as that found in approved drugs. The most common functional groups among the acid groups in the food Chemicals were phenols (16.1 %), phosphates (17.3 %), and carboxylates (17.3 %) while the single-base-containing compounds were of less interest as they accounted for just 5.5 %. To the best of our knowledge, this is the first systematic acid/base profiling of food Chemicals and it is part of a continued effort to profile food Chemicals for their broad interest in several areas such as nutrition and the food industry in general.

  • Analysis of a large food Chemical Database: Chemical space, diversity, and complexity
    F1000Research, 2018
    Co-Authors: J. Jesús Naveja, Mariel P. Rico-hidalgo, José L. Medina-franco
    Abstract:

    Background: Food Chemicals are a cornerstone in the food industry. However, its Chemical diversity has been explored on a limited basis, for instance, previous analysis of food-related Databases were done up to 2,200 molecules. The goal of this work was to quantify the Chemical diversity of Chemical compounds stored in FooDB, a Database with nearly 24,000 food Chemicals. Methods: The visual representation of the Chemical space of FooDB was done with ChemMaps, a novel approach based on the concept of Chemical satellites. The large food Chemical Database was profiled based on physicoChemical properties, molecular complexity and scaffold content. The global diversity of FoodDB was characterized using Consensus Diversity Plots. Results: It was found that compounds in FooDB are very diverse in terms of properties and structure, with a large structural complexity. It was also found that one third of the food Chemicals are acyclic molecules and ring-containing molecules are mostly monocyclic, with several scaffolds common to natural products in other Databases. Conclusions: To the best of our knowledge, this is the first analysis of the Chemical diversity and complexity of FooDB. This study represents a step further to the emerging field of “Food Informatics”. Future study should compare directly the Chemical structures of the molecules in FooDB with other compound Databases, for instance, drug-like Databases and natural products collections.

  • Analysis of a large food Chemical Database: Chemical space, diversity, and complexity
    F1000Research, 2018
    Co-Authors: J. Jesús Naveja, Mariel P. Rico-hidalgo, José L. Medina-franco
    Abstract:

    Background: Food Chemicals are a cornerstone in the food industry. However, its Chemical diversity has been explored on a limited basis, for instance, previous analysis of food-related Databases were done up to 2,200 molecules. The goal of this work was to quantify the Chemical diversity of Chemical compounds stored in FooDB, a Database with nearly 24,000 food Chemicals. Methods: The visual representation of the Chemical space of FooDB was done with ChemMaps, a novel approach based on the concept of Chemical satellites. The large food Chemical Database was profiled based on physicoChemical properties, molecular complexity and scaffold content. The global diversity of FooDB was characterized using Consensus Diversity Plots. Results: It was found that compounds in FooDB are very diverse in terms of properties and structure, with a large structural complexity. It was also found that one third of the food Chemicals are acyclic molecules and ring-containing molecules are mostly monocyclic, with several scaffolds common to natural products in other Databases. Conclusions: To the best of our knowledge, this is the first analysis of the Chemical diversity and complexity of FooDB. This study represents a step further to the emerging field of “Food Informatics”. Future study should compare directly the Chemical structures of the molecules in FooDB with other compound Databases, for instance, drug-like Databases and natural products collections. An additional future direction of this work is to use the list of 3,228 polyphenolic compounds identified in this work to enhance the on-going polyphenol-protein interactome studies.

  • Analysis of a large food Chemical Database: Chemical space, diversity, and complexity [version 1; referees: 2 approved, 1 approved with reservations]
    F1000 Research Ltd, 2018
    Co-Authors: J. Jesús Naveja, Mariel P. Rico-hidalgo, José L. Medina-franco
    Abstract:

    Background: Food Chemicals are a cornerstone in the food industry. However, its Chemical diversity has been explored on a limited basis, for instance, previous analysis of food-related Databases were done up to 2,200 molecules. The goal of this work was to quantify the Chemical diversity of Chemical compounds stored in FooDB, a Database with nearly 24,000 food Chemicals. Methods: The visual representation of the Chemical space of FooDB was done with ChemMaps, a novel approach based on the concept of Chemical satellites. The large food Chemical Database was profiled based on physicoChemical properties, molecular complexity and scaffold content. The global diversity of FoodDB was characterized using Consensus Diversity Plots. Results: It was found that compounds in FooDB are very diverse in terms of properties and structure, with a large structural complexity. It was also found that one third of the food Chemicals are acyclic molecules and ring-containing molecules are mostly monocyclic, with several scaffolds common to natural products in other Databases. Conclusions: To the best of our knowledge, this is the first analysis of the Chemical diversity and complexity of FooDB. This study represents a step further to the emerging field of “Food Informatics”. Future study should compare directly the Chemical structures of the molecules in FooDB with other compound Databases, for instance, drug-like Databases and natural products collections

  • Analysis of a large food Chemical Database: Chemical space, diversity, and complexity [version 2; referees: 2 approved, 1 approved with reservations]
    F1000 Research Ltd, 2018
    Co-Authors: J. Jesús Naveja, Mariel P. Rico-hidalgo, José L. Medina-franco
    Abstract:

    Background: Food Chemicals are a cornerstone in the food industry. However, its Chemical diversity has been explored on a limited basis, for instance, previous analysis of food-related Databases were done up to 2,200 molecules. The goal of this work was to quantify the Chemical diversity of Chemical compounds stored in FooDB, a Database with nearly 24,000 food Chemicals. Methods: The visual representation of the Chemical space of FooDB was done with ChemMaps, a novel approach based on the concept of Chemical satellites. The large food Chemical Database was profiled based on physicoChemical properties, molecular complexity and scaffold content. The global diversity of FooDB was characterized using Consensus Diversity Plots. Results: It was found that compounds in FooDB are very diverse in terms of properties and structure, with a large structural complexity. It was also found that one third of the food Chemicals are acyclic molecules and ring-containing molecules are mostly monocyclic, with several scaffolds common to natural products in other Databases. Conclusions: To the best of our knowledge, this is the first analysis of the Chemical diversity and complexity of FooDB. This study represents a step further to the emerging field of “Food Informatics”. Future study should compare directly the Chemical structures of the molecules in FooDB with other compound Databases, for instance, drug-like Databases and natural products collections. An additional future direction of this work is to use the list of 3,228 polyphenolic compounds identified in this work to enhance the on-going polyphenol-protein interactome studies