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  1. Article: "On demand" redox buffering by H

    Shukla, Prashant / Khodade, Vinayak S / SharathChandra, Mallojjala / Chauhan, Preeti / Mishra, Saurabh / Siddaramappa, Shivakumara / Pradeep, Bulagonda Eswarappa / Singh, Amit / Chakrapani, Harinath

    Chemical science

    2017  Volume 8, Issue 7, Page(s) 4967–4972

    Abstract: Understanding the mechanisms of antimicrobial resistance (AMR) will help launch a counter-offensive against human pathogens that threaten our ability to effectively treat common infections. Herein, we report bis(4-nitrobenzyl)sulfanes, which are ... ...

    Abstract Understanding the mechanisms of antimicrobial resistance (AMR) will help launch a counter-offensive against human pathogens that threaten our ability to effectively treat common infections. Herein, we report bis(4-nitrobenzyl)sulfanes, which are activated by a bacterial enzyme to produce hydrogen sulfide (H
    Language English
    Publishing date 2017-04-27
    Publishing country England
    Document type Journal Article
    ZDB-ID 2559110-1
    ISSN 2041-6539 ; 2041-6520
    ISSN (online) 2041-6539
    ISSN 2041-6520
    DOI 10.1039/c7sc00873b
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: Cytoview: Development of a cell modelling framework

    Khodade, Prashant / Malhotra, Samta / Kumar, Nirmal / Iyengar, M. Sriram / Balakrishnan, N / Chandra, Nagasuma

    Journal of biosciences. 2007 Aug., v. 32, no. Supplement 1

    2007  

    Abstract: The biological cell, a natural self-contained unit of prime biological importance, is an enormously complex machine that can be understood at many levels. A higher-level perspective of the entire cell requires integration of various features into ... ...

    Abstract The biological cell, a natural self-contained unit of prime biological importance, is an enormously complex machine that can be understood at many levels. A higher-level perspective of the entire cell requires integration of various features into coherent, biologically meaningful descriptions. There are some efforts to model cells based on their genome, proteome or metabolome descriptions. However, there are no established methods as yet to describe cell morphologies, capture similarities and differences between different cells or between healthy and disease states. Here we report a framework to model various aspects of a cell and integrate knowledge encoded at different levels of abstraction, with cell morphologies at one end to atomic structures at the other. The different issues that have been addressed are ontologies, feature description and model building. The framework describes dotted representations and tree data structures to integrate diverse pieces of data and parametric models enabling size, shape and location descriptions. The framework serves as a first step in integrating different levels of data available for a biological cell and has the potential to lead to development of computational models in our pursuit to model cell structure and function, from which several applications can flow out.
    Keywords cell structures ; genome ; metabolome ; models ; proteome ; trees
    Language English
    Dates of publication 2007-08
    Size p. 965-977.
    Publishing place Springer-Verlag
    Document type Article
    ZDB-ID 756157-x
    ISSN 0973-7138 ; 0250-5991
    ISSN (online) 0973-7138
    ISSN 0250-5991
    DOI 10.1007/s12038-007-0096-y
    Database NAL-Catalogue (AGRICOLA)

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    In stock of ZB MED Bonn / Germany

    Z 5290: Show issues

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  3. Article: Cytoview: development of a cell modelling framework.

    Khodade, Prashant / Malhotra, Samta / Kumar, Nirmal / Iyengar, M Sriram / Balakrishnan, N / Chandra, Nagasuma

    Journal of biosciences

    2007  Volume 32, Issue 5, Page(s) 965–977

    Abstract: The biological cell, a natural self-contained unit of prime biological importance, is an enormously complex machine that can be understood at many levels. A higher-level perspective of the entire cell requires integration of various features into ... ...

    Abstract The biological cell, a natural self-contained unit of prime biological importance, is an enormously complex machine that can be understood at many levels. A higher-level perspective of the entire cell requires integration of various features into coherent, biologically meaningful descriptions. There are some efforts to model cells based on their genome, proteome or metabolome descriptions. However, there are no established methods as yet to describe cell morphologies, capture similarities and differences between different cells or between healthy and disease states. Here we report a framework to model various aspects of a cell and integrate knowledge encoded at different levels of abstraction, with cell morphologies at one end to atomic structures at the other. The different issues that have been addressed are ontologies, feature description and model building. The framework describes dotted representations and tree data structures to integrate diverse pieces of data and parametric models enabling size, shape and location descriptions. The framework serves as a first step in integrating different levels of data available for a biological cell and has the potential to lead to development of computational models in our pursuit to model cell structure and function, from which several applications can flow out.
    MeSH term(s) Algorithms ; Animals ; Computer Simulation ; Eukaryotic Cells/chemistry ; Eukaryotic Cells/cytology ; Eukaryotic Cells/physiology ; Humans ; Models, Biological ; Systems Biology/methods ; Systems Biology/trends
    Language English
    Publishing date 2007-10-03
    Publishing country India
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Review
    ZDB-ID 756157-x
    ISSN 0250-5991
    ISSN 0250-5991
    DOI 10.1007/s12038-007-0096-y
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

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