title: Propositionalisation of Profile Hidden Markov Models for Biological Sequence Analysis

authors: Mutter, Stefan

subjects: computer science

abstract: Hidden Markov Models are a widely used generative model for analysing sequence data. A variant, Profile Hidden Markov Models are a special case used in Bioinformatics to represent, for example, protein families. In this paper we introduce a simple propositionalisation method for Profile Hidden Markov Models. The method allows the use of PHMMs discriminatively in a classification task. Previously, kernel approaches have been proposed to generate a discriminative description for an HMM, but require the explicit definition of a similarity measure for HMMs. Propositionalisation does not need such a measure and allows the use of any propositional learner including kernel-based approaches. We show empirically that using propositionalisation leads to higher accuracies in comparison with PHMMs on benchmark datasets.

text: Propositionalisation of Profile Hidden Markov Models for Biological Sequence Analysis Hidden Markov Models are a widely used generative model for analysing sequence data. A variant, Profile Hidden Markov Models are a special case used in Bioinformatics to represent, for example, protein families. In this paper we introduce a simple propositionalisation method for Profile Hidden Markov Models. The method allows the use of PHMMs discriminatively in a classification task. Previously, kernel approaches have been proposed to generate a discriminative description for an HMM, but require the explicit definition of a similarity measure for HMMs. Propositionalisation does not need such a measure and allows the use of any propositional learner including kernel-based approaches. We show empirically that using propositionalisation leads to higher accuracies in comparison with PHMMs on benchmark datasets.

year: 2008

title: Weka: A machine learning workbench for data mining

authors: Frank, Eibe

subjects: computer science

abstract: The Weka workbench is an organized collection of state-of-the-art machine learning algorithms and data preprocessing tools. The basic way of interacting with these methods is by invoking them from the command line. However, convenient interactive graphical user interfaces are provided for data exploration, for setting up large-scale experiments on distributed computing platforms, and for designing configurations for streamed data processing. These interfaces constitute an advanced environment for experimental data mining. The system is written in Java and distributed under the terms of the GNU General Public License.

text: Weka: A machine learning workbench for data mining The Weka workbench is an organized collection of state-of-the-art machine learning algorithms and data preprocessing tools. The basic way of interacting with these methods is by invoking them from the command line. However, convenient interactive graphical user interfaces are provided for data exploration, for setting up large-scale experiments on distributed computing platforms, and for designing configurations for streamed data processing. These interfaces constitute an advanced environment for experimental data mining. The system is written in Java and distributed under the terms of the GNU General Public License.

year: 2005

title: Coastal communities, leisure and wellbeing: Advancing a trans-disciplinary agenda for understanding ocean-human relationships in Aotearoa New Zealand

authors: Wheaton, Belinda

subjects: Science & Technology

abstract: Commentators are advocating for research to better understand relationships between healthy coastal ecosystems and human wellbeing. Doing so requires inter- and transdisciplinary approaches across humanities, arts, social sciences, and science and technology disciplines. These approaches include culturally diverse knowledge systems, such as indigenous ones, that locate sustainable use of and relationships to marine ecosystems. This paper contributes to this agenda through a case-study of relationships between coastal ecosystems and human wellbeing in Aotearoa New Zealand. This article highlights interconnected cultural and wellbeing benefits of, and socio-ecological relationships between, these coastal ecosystems drawing on a case study of one ocean-based, ‘immersive’ leisure activity, surfing. Further, it examines how these relationships impact human physical, emotional and spiritual wellbeing, and the wellbeing of communities and ecosystems. The research illustrates that surfing creates strong bonds between practitioners and coastal places, linking the health of marine environments and people. We demonstrate the value of a transdisciplinary place-based approach that integrates research across the humanities and social sciences and engages with Indigenous knowledge (Mātauranga Māori). This argument for multicultural co-learning shows the value of Western and Māori vantage points for how we understand coastal blue spaces. Indigenous perspectives, we conclude, deepen appreciation, as well as equity considerations, of how we understand place, wellbeing, and long-term sustainable relationships with marine ecosystems.

text: Coastal communities, leisure and wellbeing: Advancing a trans-disciplinary agenda for understanding ocean-human relationships in Aotearoa New Zealand Commentators are advocating for research to better understand relationships between healthy coastal ecosystems and human wellbeing. Doing so requires inter- and transdisciplinary approaches across humanities, arts, social sciences, and science and technology disciplines. These approaches include culturally diverse knowledge systems, such as indigenous ones, that locate sustainable use of and relationships to marine ecosystems. This paper contributes to this agenda through a case-study of relationships between coastal ecosystems and human wellbeing in Aotearoa New Zealand. This article highlights interconnected cultural and wellbeing benefits of, and socio-ecological relationships between, these coastal ecosystems drawing on a case study of one ocean-based, ‘immersive’ leisure activity, surfing. Further, it examines how these relationships impact human physical, emotional and spiritual wellbeing, and the wellbeing of communities and ecosystems. The research illustrates that surfing creates strong bonds between practitioners and coastal places, linking the health of marine environments and people. We demonstrate the value of a transdisciplinary place-based approach that integrates research across the humanities and social sciences and engages with Indigenous knowledge (Mātauranga Māori). This argument for multicultural co-learning shows the value of Western and Māori vantage points for how we understand coastal blue spaces. Indigenous perspectives, we conclude, deepen appreciation, as well as equity considerations, of how we understand place, wellbeing, and long-term sustainable relationships with marine ecosystems.

year: 2021