1 resultado para Audio-visual Speech Recognition, Visual Feature Extraction, Free-parts, Monolithic, ROI
em DigitalCommons@The Texas Medical Center
Filtro por publicador
- KUPS-Datenbank - Universität zu Köln - Kölner UniversitätsPublikationsServer (1)
- Acceda, el repositorio institucional de la Universidad de Las Palmas de Gran Canaria. España (1)
- AMS Tesi di Dottorato - Alm@DL - Università di Bologna (8)
- AMS Tesi di Laurea - Alm@DL - Università di Bologna (11)
- Applied Math and Science Education Repository - Washington - USA (8)
- ArchiMeD - Elektronische Publikationen der Universität Mainz - Alemanha (2)
- Archive of European Integration (5)
- Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco (2)
- Argos - Repositorio Institucional de la Secretaría de Investigación y Postgrado de la Facultad de Humanidades y Ciencias Sociales de la Universidad Nacional de Misiones (1)
- Aston University Research Archive (36)
- Biblioteca de Teses e Dissertações da USP (3)
- Biblioteca Digital | Sistema Integrado de Documentación | UNCuyo - UNCUYO. UNIVERSIDAD NACIONAL DE CUYO. (3)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (5)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (13)
- Biblioteca Virtual del Sistema Sanitario Público de Andalucía (BV-SSPA), Junta de Andalucía. Consejería de Salud y Bienestar Social, Spain (2)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (20)
- Brock University, Canada (6)
- Bucknell University Digital Commons - Pensilvania - USA (1)
- Bulgarian Digital Mathematics Library at IMI-BAS (9)
- CentAUR: Central Archive University of Reading - UK (35)
- CiencIPCA - Instituto Politécnico do Cávado e do Ave, Portugal (1)
- Cochin University of Science & Technology (CUSAT), India (30)
- Coffee Science - Universidade Federal de Lavras (2)
- Comissão Econômica para a América Latina e o Caribe (CEPAL) (4)
- Consorci de Serveis Universitaris de Catalunya (CSUC), Spain (54)
- CORA - Cork Open Research Archive - University College Cork - Ireland (1)
- Dalarna University College Electronic Archive (13)
- Digital Commons - Michigan Tech (3)
- Digital Commons @ DU | University of Denver Research (1)
- Digital Commons at Florida International University (22)
- Digital Peer Publishing (3)
- DigitalCommons@The Texas Medical Center (1)
- DigitalCommons@University of Nebraska - Lincoln (2)
- Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland (26)
- DRUM (Digital Repository at the University of Maryland) (4)
- Duke University (4)
- Glasgow Theses Service (2)
- Illinois Digital Environment for Access to Learning and Scholarship Repository (1)
- Instituto Politécnico de Leiria (1)
- Instituto Politécnico do Porto, Portugal (19)
- Instituto Superior de Psicologia Aplicada - Lisboa (1)
- Martin Luther Universitat Halle Wittenberg, Germany (4)
- Massachusetts Institute of Technology (17)
- Memoria Académica - FaHCE, UNLP - Argentina (6)
- Memorial University Research Repository (1)
- Ministerio de Cultura, Spain (17)
- National Center for Biotechnology Information - NCBI (19)
- Open University Netherlands (1)
- Portal de Revistas Científicas Complutenses - Espanha (2)
- Publishing Network for Geoscientific & Environmental Data (4)
- QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast (8)
- RDBU - Repositório Digital da Biblioteca da Unisinos (3)
- ReCiL - Repositório Científico Lusófona - Grupo Lusófona, Portugal (2)
- Repositório Aberto da Universidade Aberta de Portugal (1)
- Repositorio Académico de la Universidad Nacional de Costa Rica (2)
- Repositório Científico da Universidade de Évora - Portugal (2)
- Repositório Científico do Instituto Politécnico de Lisboa - Portugal (25)
- Repositório da Produção Científica e Intelectual da Unicamp (1)
- Repositório da Universidade Federal do Espírito Santo (UFES), Brazil (1)
- Repositorio de la Universidad de Cuenca (1)
- Repositório digital da Fundação Getúlio Vargas - FGV (2)
- Repositório Digital da UNIVERSIDADE DA MADEIRA - Portugal (1)
- Repositório Institucional da Universidade de Aveiro - Portugal (1)
- Repositório Institucional da Universidade de Brasília (1)
- Repositório Institucional da Universidade Federal do Rio Grande - FURG (1)
- Repositório Institucional da Universidade Federal do Rio Grande do Norte (1)
- Repositório Institucional da Universidade Tecnológica Federal do Paraná (RIUT) (3)
- Repositorio Institucional de la Universidad de Málaga (1)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (91)
- Repositorio Institucional Universidad EAFIT - Medelin - Colombia (1)
- Royal College of Art Research Repository - Uninet Kingdom (1)
- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (10)
- School of Medicine, Washington University, United States (20)
- Scielo Saúde Pública - SP (4)
- Scielo Uruguai (2)
- Sistema UNA-SUS (1)
- Universidad de Alicante (15)
- Universidad del Rosario, Colombia (4)
- Universidad Politécnica de Madrid (41)
- Universidade Complutense de Madrid (1)
- Universidade do Minho (5)
- Universidade dos Açores - Portugal (1)
- Universidade Federal de Uberlândia (4)
- Universidade Federal do Pará (6)
- Universidade Federal do Rio Grande do Norte (UFRN) (12)
- Universidade Metodista de São Paulo (3)
- Universitat de Girona, Spain (15)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (5)
- Université de Lausanne, Switzerland (31)
- Université de Montréal (6)
- Université de Montréal, Canada (23)
- University of Canberra Research Repository - Australia (4)
- University of Michigan (36)
- University of Queensland eSpace - Australia (29)
- University of Southampton, United Kingdom (1)
- University of Washington (4)
- WestminsterResearch - UK (2)
Resumo:
Improvements in the analysis of microarray images are critical for accurately quantifying gene expression levels. The acquisition of accurate spot intensities directly influences the results and interpretation of statistical analyses. This dissertation discusses the implementation of a novel approach to the analysis of cDNA microarray images. We use a stellar photometric model, the Moffat function, to quantify microarray spots from nylon microarray images. The inherent flexibility of the Moffat shape model makes it ideal for quantifying microarray spots. We apply our novel approach to a Wilms' tumor microarray study and compare our results with a fixed-circle segmentation approach for spot quantification. Our results suggest that different spot feature extraction methods can have an impact on the ability of statistical methods to identify differentially expressed genes. We also used the Moffat function to simulate a series of microarray images under various experimental conditions. These simulations were used to validate the performance of various statistical methods for identifying differentially expressed genes. Our simulation results indicate that tests taking into account the dependency between mean spot intensity and variance estimation, such as the smoothened t-test, can better identify differentially expressed genes, especially when the number of replicates and mean fold change are low. The analysis of the simulations also showed that overall, a rank sum test (Mann-Whitney) performed well at identifying differentially expressed genes. Previous work has suggested the strengths of nonparametric approaches for identifying differentially expressed genes. We also show that multivariate approaches, such as hierarchical and k-means cluster analysis along with principal components analysis, are only effective at classifying samples when replicate numbers and mean fold change are high. Finally, we show how our stellar shape model approach can be extended to the analysis of 2D-gel images by adapting the Moffat function to take into account the elliptical nature of spots in such images. Our results indicate that stellar shape models offer a previously unexplored approach for the quantification of 2D-gel spots. ^