Identifying spatially similar gene expression patterns in early stage fruit fly embryo images: binary feature versus invariant moment digital representations.
Identifying spatially similar gene expression patterns in early stage fruit fly embryo images: binary feature versus invariant moment digital representations.
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DOI：
10.1186/1471-2105-5-202
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发表时间：
2004-12-16
影响因子：
3
通讯作者：
Kumar S
中科院分区：
文献类型：
--
作者：
Gurunathan R;Van Emden B;Panchanathan S;Kumar S
现代发育生物学在很大程度上依赖于胚胎基因表达模式的分析。研究人员手动检查数百或数千种表达模式，以识别那些在空间上相似的模式，并最终推断潜在的基因相互作用。然而，在过去20年中，在高通量技术的推动下，基因表达模式数据的快速积累产生了开发有效的方法来直接比较图像而不是其文本描述来识别空间相似的表达模式的需要。在小(226张图像)和大(1819张图像)的数据集上，比较了基于二进制特征向量(BFV)和不变矩向量(IMV)的基因表达模式的数字表示在寻找具有生物学意义的模式方面的有效性。对于每个数据集，生成与查询图像相关的图像的有序列表，以识别重叠和相似的基因表达模式，其方式类似于发育生物学家可能做的事情。结果表明，当考虑到基因表达模式和涉及的基因的空间重叠时，BFV表示在寻找有生物学意义的匹配方面一致优于IMV表示。此外，我们探索了在数据集中进行基于图像内容的搜索的价值，其中也单独包括了多域表达模式的单个表达成分(或结构域)。我们发现，这种技术提高了基于IMV和BFV的搜索的性能。我们的结论是，与IMV表示相比，BFV表示始终产生更广泛和更好的生物学有用模式列表。随着搜索数据库变得更大，获得的高质量结果规模也越来越大，这鼓励了为空间基因表达模式建立自动图像查询和检索系统的努力。
Modern developmental biology relies heavily on the analysis of embryonic gene expression patterns. Investigators manually inspect hundreds or thousands of expression patterns to identify those that are spatially similar and to ultimately infer potential gene interactions. However, the rapid accumulation of gene expression pattern data over the last two decades, facilitated by high-throughput techniques, has produced a need for the development of efficient approaches for direct comparison of images, rather than their textual descriptions, to identify spatially similar expression patterns. The effectiveness of the Binary Feature Vector (BFV) and Invariant Moment Vector (IMV) based digital representations of the gene expression patterns in finding biologically meaningful patterns was compared for a small (226 images) and a large (1819 images) dataset. For each dataset, an ordered list of images, with respect to a query image, was generated to identify overlapping and similar gene expression patterns, in a manner comparable to what a developmental biologist might do. The results showed that the BFV representation consistently outperforms the IMV representation in finding biologically meaningful matches when spatial overlap of the gene expression pattern and the genes involved are considered. Furthermore, we explored the value of conducting image-content based searches in a dataset where individual expression components (or domains) of multi-domain expression patterns were also included separately. We found that this technique improves performance of both IMV and BFV based searches. We conclude that the BFV representation consistently produces a more extensive and better list of biologically useful patterns than the IMV representation. The high quality of results obtained scales well as the search database becomes larger, which encourages efforts to build automated image query and retrieval systems for spatial gene expression patterns.
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影响因子：
2.6
作者：
Colas, JF;Launay, JM;Maroteaux, L
通讯作者：
Maroteaux, L
影响因子：
11.4
作者：
Arnosti, DN;Gray, S;Levine, M
通讯作者：
Levine, M
DOI：
10.1109/tit.1962.1057692
发表时间：
1962-01-01
期刊：
IRE TRANSACTIONS ON INFORMATION THEORY
影响因子：
--
作者：
HU, M
通讯作者：
HU, M
影响因子：
64.8
作者：
Ashe, HL;Levine, M
通讯作者：
Levine, M
影响因子：
64.5
作者：
GAUL, U;JACKLE, H
通讯作者：
JACKLE, H