Melbourne, Victoria, Australia
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About

I am a senior academic leader, with a strong desire to create inclusive, cohesive, and…

Activity

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Experience & Education

  • RMIT University

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Publications

  • C'mon girls, let’s program a better tech industry

    The Conversation

    Media piece on women in IT.

    See publication

  • Standardized Mutual Information for Clustering Comparisons: A Step Further in Adjustment for Chance

    Proceedings of the 31st International Conference on Machine Learning (ICML 2014), JMLR, pages 1143-1151, June 21-26, Beijing, China, 2014.

    Other authors
    See publication

  • Enhancing diagnostics for invasive Aspergillosis using machine learning

    Proceedings of the Abstracts of the Scientific Stream at Big Data 2014 Melbourne, Australia, April 3-4, 2014.

    Other authors
    See publication

  • Diving deep into data to crack the gene code on disease

    The Conversation

    Article looking at the need to explore supplementary information associated with publications, to find information on genetic variation.

    See publication

  • Impact of Corpus Diversity and Complexity on NER Performance

    Proceedings of the Australasian Language Technology Association Workshop 2013

    Other authors
    See publication

  • A Posteriori Ontology Engineering for Data-Driven Science

    Chapman and Hall/CRC Press

    In: Data-Intensive Science, Eds. T. Critchlow and K. Kleese van Dam

    Other authors
    See publication

  • Text Mining Improves Prediction of Protein Functional Sites

    PLoS One

    We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are…

    We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites) in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions.

    Other authors
    • Judith D Cohn
    • Ravikumar Komandur
    • Michael Wall
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  • Knowledge Integration in Open Worlds: Utilizing the Mathematics of Hierarchical Structure

    Proc. IEEE Int. Conf. Semantic Computing (ICSC 07), IEEE Computer Society, pp. 105-112

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  • Deconstruction, Reconstruction, and Ontogenesis for Large, Monolithic, Legacy Ontologies in Semantic Web Service Applications

    Los Alamos Technical Report 06-5859

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  • Distributed Representations of Bio-Ontologies for Semantic Web Services

    Joint BioLINK and 9th Bio-Ontologies Meeting (JBB 06), ISMB 06

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Patents

  • System and method for knowledge based matching of users in a network

    Issued US US7933856

    A knowledge-based system and methods to matchmaking and social network extension are disclosed. The system is configured to allow users to specify knowledge profiles, which are collections of concepts that indicate a certain topic or area of interest. The system utilizes the knowledge model as the semantic space within which to compare similarities in user interests. The knowledge model is hierarchical so that indications of interest in specific concepts automatically imply interest in more…

    A knowledge-based system and methods to matchmaking and social network extension are disclosed. The system is configured to allow users to specify knowledge profiles, which are collections of concepts that indicate a certain topic or area of interest. The system utilizes the knowledge model as the semantic space within which to compare similarities in user interests. The knowledge model is hierarchical so that indications of interest in specific concepts automatically imply interest in more general concept. Similarity measures between profiles may then be calculated based on suitable distance formulas within this space.

Languages

  • Spanish

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  • Dutch

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  • French

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Organizations

  • Australasian Language Technology Association (ALTA)

    Secretary

    - Present

    http://www.alta.asn.au

  • Australasian Language Technology Association (ALTA)

    President

    -

    http://www.alta.asn.au/

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