Bioimage informatics: a new area of engineering biology
In recent years, the deluge of complicated molecular and cellular microscopic images creates compelling challenges for the image computing community. There has been an increasing focus on developing novel image processing, data mining, database and visualization techniques to extract, compare, searc...
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| Vydáno v: | Bioinformatics Ročník 24; číslo 17; s. 1827 - 1836 |
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| Hlavní autor: | |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Oxford
Oxford University Press
01.09.2008
Oxford Publishing Limited (England) |
| Témata: | |
| ISSN: | 1367-4803, 1367-4811, 1460-2059, 1367-4811 |
| On-line přístup: | Získat plný text |
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| Abstract | In recent years, the deluge of complicated molecular and cellular microscopic images creates compelling challenges for the image computing community. There has been an increasing focus on developing novel image processing, data mining, database and visualization techniques to extract, compare, search and manage the biological knowledge in these data-intensive problems. This emerging new area of bioinformatics can be called ‘bioimage informatics’. This article reviews the advances of this field from several aspects, including applications, key techniques, available tools and resources. Application examples such as high-throughput/high-content phenotyping and atlas building for model organisms demonstrate the importance of bioimage informatics. The essential techniques to the success of these applications, such as bioimage feature identification, segmentation and tracking, registration, annotation, mining, image data management and visualization, are further summarized, along with a brief overview of the available bioimage databases, analysis tools and other resources. Contact: pengh@janelia.hhmi.org Supplementary information: Supplementary data are available at Bioinformatics online. |
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| AbstractList | In recent years, the deluge of complicated molecular and cellular microscopic images creates compelling challenges for the image computing community. There has been an increasing focus on developing novel image processing, data mining, database and visualization techniques to extract, compare, search and manage the biological knowledge in these data-intensive problems. This emerging new area of bioinformatics can be called 'bioimage informatics'. This article reviews the advances of this field from several aspects, including applications, key techniques, available tools and resources. Application examples such as high-throughput/high-content phenotyping and atlas building for model organisms demonstrate the importance of bioimage informatics. The essential techniques to the success of these applications, such as bioimage feature identification, segmentation and tracking, registration, annotation, mining, image data management and visualization, are further summarized, along with a brief overview of the available bioimage databases, analysis tools and other resources. In recent years, the deluge of complicated molecular and cellular microscopic images creates compelling challenges for the image computing community. There has been an increasing focus on developing novel image processing, data mining, database and visualization techniques to extract, compare, search and manage the biological knowledge in these data-intensive problems. This emerging new area of bioinformatics can be called ‘bioimage informatics’. This article reviews the advances of this field from several aspects, including applications, key techniques, available tools and resources. Application examples such as high-throughput/high-content phenotyping and atlas building for model organisms demonstrate the importance of bioimage informatics. The essential techniques to the success of these applications, such as bioimage feature identification, segmentation and tracking, registration, annotation, mining, image data management and visualization, are further summarized, along with a brief overview of the available bioimage databases, analysis tools and other resources. Contact: pengh@janelia.hhmi.org Supplementary information: Supplementary data are available at Bioinformatics online. In recent years, the deluge of complicated molecular and cellular microscopic images creates compelling challenges for the image computing community. There has been an increasing focus on developing novel image processing, data mining, database and visualization techniques to extract, compare, search and manage the biological knowledge in these data-intensive problems. This emerging new area of bioinformatics can be called 'bioimage informatics'. This article reviews the advances of this field from several aspects, including applications, key techniques, available tools and resources. Application examples such as high-throughput/high-content phenotyping and atlas building for model organisms demonstrate the importance of bioimage informatics. The essential techniques to the success of these applications, such as bioimage feature identification, segmentation and tracking, registration, annotation, mining, image data management and visualization, are further summarized, along with a brief overview of the available bioimage databases, analysis tools and other resources. Contact: pengh@janelia.hhmi.org Supplementary information: Supplementary data are available at Bioinformatics online. [PUBLICATION ABSTRACT] In recent years, the deluge of complicated molecular and cellular microscopic images creates compelling challenges for the image computing community. There has been an increasing focus on developing novel image processing, data mining, database and visualization techniques to extract, compare, search and manage the biological knowledge in these data-intensive problems. This emerging new area of bioinformatics can be called 'bioimage informatics'. This article reviews the advances of this field from several aspects, including applications, key techniques, available tools and resources. Application examples such as high-throughput/high-content phenotyping and atlas building for model organisms demonstrate the importance of bioimage informatics. The essential techniques to the success of these applications, such as bioimage feature identification, segmentation and tracking, registration, annotation, mining, image data management and visualization, are further summarized, along with a brief overview of the available bioimage databases, analysis tools and other resources.In recent years, the deluge of complicated molecular and cellular microscopic images creates compelling challenges for the image computing community. There has been an increasing focus on developing novel image processing, data mining, database and visualization techniques to extract, compare, search and manage the biological knowledge in these data-intensive problems. This emerging new area of bioinformatics can be called 'bioimage informatics'. This article reviews the advances of this field from several aspects, including applications, key techniques, available tools and resources. Application examples such as high-throughput/high-content phenotyping and atlas building for model organisms demonstrate the importance of bioimage informatics. The essential techniques to the success of these applications, such as bioimage feature identification, segmentation and tracking, registration, annotation, mining, image data management and visualization, are further summarized, along with a brief overview of the available bioimage databases, analysis tools and other resources. In recent years, the deluge of complicated molecular and cellular microscopic images creates compelling challenges for the image computing community. There has been an increasing focus on developing novel image processing, data mining, database and visualization techniques to extract, compare, search and manage the biological knowledge in these data-intensive problems. This emerging new area of bioinformatics can be called ‘bioimage informatics’. This article reviews the advances of this field from several aspects, including applications, key techniques, available tools and resources. Application examples such as high-throughput/high-content phenotyping and atlas building for model organisms demonstrate the importance of bioimage informatics. The essential techniques to the success of these applications, such as bioimage feature identification, segmentation and tracking, registration, annotation, mining, image data management and visualization, are further summarized, along with a brief overview of the available bioimage databases, analysis tools and other resources. Contact: pengh@janelia.hhmi.org Supplementary information: Supplementary data are available at Bioinformatics online. In recent years, the deluge of complicated molecular and cellular microscopic images creates compelling challenges for the image computing community. There has been an increasing focus on developing novel image processing, data mining, database and visualization techniques to extract, compare, search and manage the biological knowledge in these data-intensive problems. This emerging new area of bioinformatics can be called 'bioimage informatics'. This article reviews the advances of this field from several aspects, including applications, key techniques, available tools and resources. Application examples such as high-throughput/high-content phenotyping and atlas building for model organisms demonstrate the importance of bioimage informatics. The essential techniques to the success of these applications, such as bioimage feature identification, segmentation and tracking, registration, annotation, mining, image data management and visualization, are further summarized, along with a brief overview of the available bioimage databases, analysis tools and other resources. Contact: pengh@janelia.hhmi.org Supplementary information: Supplementary data are available at Bioinformatics online. |
| Author | Peng, Hanchuan |
| AuthorAffiliation | Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA |
| AuthorAffiliation_xml | – name: Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA |
| Author_xml | – sequence: 1 givenname: Hanchuan surname: Peng fullname: Peng, Hanchuan |
| BackLink | http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=20598796$$DView record in Pascal Francis https://www.ncbi.nlm.nih.gov/pubmed/18603566$$D View this record in MEDLINE/PubMed |
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| ContentType | Journal Article |
| Copyright | 2008 The Author(s) 2008 2008 INIST-CNRS 2008 The Author(s) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
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| Issue | 17 |
| Keywords | Bioinformatics Biology |
| Language | English |
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| Notes | ark:/67375/HXZ-TR13QRXR-8 Associate Editor: Jonathan Wren ArticleID:btn346 istex:9295113E8CD41BB2B46489419F6991FC74898653 ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 ObjectType-Review-3 content type line 23 |
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| Snippet | In recent years, the deluge of complicated molecular and cellular microscopic images creates compelling challenges for the image computing community. There has... |
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| SubjectTerms | Bioinformatics Biological and medical sciences Biomedical Engineering - methods Biomedical Engineering - trends Computational Biology - methods Computational Biology - trends Computer Graphics Computer Simulation Data management Data mining Diagnostic Imaging - methods Fundamental and applied biological sciences. Psychology General aspects Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects) Models, Biological Review Paper User-Computer Interface |
| Title | Bioimage informatics: a new area of engineering biology |
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