title: A survey of neural network-based cancer prediction models from microarray data

authors: Daoud, Maisa

subjects: computer science

abstract: Neural networks are powerful tools used widely for building cancer prediction models from microarray data. We review the most recently proposed models to highlight the roles of neural networks in predicting cancer from gene expression data. We identified articles published between 2013–2018 in scientific databases using keywords such as cancer classification, cancer analysis, cancer prediction, cancer clustering and microarray data. Analyzing the studies reveals that neural network methods have been either used for filtering (data engineering) the gene expressions in a prior step to prediction; predicting the existence of cancer, cancer type or the survivability risk; or for clustering unlabeled samples. This paper also discusses some practical issues that can be considered when building a neural network-based cancer prediction model. Results indicate that the functionality of the neural network determines its general architecture. However, the decision on the number of hidden layers, neurons, hypermeters and learning algorithm is made using trail-and-error techniques.

text: A survey of neural network-based cancer prediction models from microarray data Neural networks are powerful tools used widely for building cancer prediction models from microarray data. We review the most recently proposed models to highlight the roles of neural networks in predicting cancer from gene expression data. We identified articles published between 2013–2018 in scientific databases using keywords such as cancer classification, cancer analysis, cancer prediction, cancer clustering and microarray data. Analyzing the studies reveals that neural network methods have been either used for filtering (data engineering) the gene expressions in a prior step to prediction; predicting the existence of cancer, cancer type or the survivability risk; or for clustering unlabeled samples. This paper also discusses some practical issues that can be considered when building a neural network-based cancer prediction model. Results indicate that the functionality of the neural network determines its general architecture. However, the decision on the number of hidden layers, neurons, hypermeters and learning algorithm is made using trail-and-error techniques.

year: 2019

title: Shifting realities: Immigrant teacher transitions into early childhood settings in Aotearoa New Zealand

authors: Arndt, Sonja Kathrina

abstract: Imagine you are an immigrant early childhood teacher… this article tells your story of transition and diversity. It interweaves tensions and complex realities and explores issues and concerns for immigrant teachers in the cultural places and relational spaces of early childhood settings.  Based on teacher narratives and a post-structural discourse analysis, it suggests that immigrant teachers’ realities are not always ‘rich’ or celebratory, but are often complex entanglements of struggle and contradictions.  The article urges fresh considerations of early childhood relationships to allow for fluid, shifting identities and cultures – yours, ours, and the centre’s.

text: Shifting realities: Immigrant teacher transitions into early childhood settings in Aotearoa New Zealand Imagine you are an immigrant early childhood teacher… this article tells your story of transition and diversity. It interweaves tensions and complex realities and explores issues and concerns for immigrant teachers in the cultural places and relational spaces of early childhood settings.  Based on teacher narratives and a post-structural discourse analysis, it suggests that immigrant teachers’ realities are not always ‘rich’ or celebratory, but are often complex entanglements of struggle and contradictions.  The article urges fresh considerations of early childhood relationships to allow for fluid, shifting identities and cultures – yours, ours, and the centre’s.

year: 2014

title: E Kui Rāwinia

authors: Maxwell, Te Kahautu

abstract: E Kui Rāwinia; this composition is a lament to a Te Whakatōhea chieftainess who married the paramount Ngāti Porou rangatira Tokorua (Toko) Te Kani. This composition recites the genealogical ties between the East Coast iwi to Te Whakatōhea. The composition paints a spiritual journey for Rāwinia to return to her birth place Ōpōtiki. The journey names geographical features of importance to map her journey home. This composition gained first place for composition. Performed by Ōpōtiki Mai Tawhiti at the Te Matatini World Championship Kapa Haka competition.

text: E Kui Rāwinia E Kui Rāwinia; this composition is a lament to a Te Whakatōhea chieftainess who married the paramount Ngāti Porou rangatira Tokorua (Toko) Te Kani. This composition recites the genealogical ties between the East Coast iwi to Te Whakatōhea. The composition paints a spiritual journey for Rāwinia to return to her birth place Ōpōtiki. The journey names geographical features of importance to map her journey home. This composition gained first place for composition. Performed by Ōpōtiki Mai Tawhiti at the Te Matatini World Championship Kapa Haka competition.

year: 2015