IEEE Transactions on Computational Biology and Bioinformatics (TCBB) will move to the OnlinePlus publication model starting with 2015 issues!
From the May/June 2014 Issue
Bio-Driven Cell Region Detection in Human Embryonic Stem Cell Assay
By Benjamin X. Guan, Bir Bhanu, Prue Talbot, and Sabrina Lin
This paper proposes a bio-driven algorithm that detects cell regions automatically in the human embryonic stem cell (hESC) images obtained using a phase contrast microscope. The algorithm uses both statistical intensity distributions of foreground/hESCs and background/substrate as well as cell property for cell region detection. The intensity distributions of foreground/hESCs and background/substrate are modeled as a mixture of two Gaussians. The cell property is translated into local spatial information. The algorithm is optimized by parameters of the modeled distributions and cell regions evolve with the local cell property. The paper validates the method with various videos acquired using different microscope objectives. In comparison with the state-of-the-art methods, the proposed method is able to detect the entire cell region instead of fragmented cell regions. It also yields high marks on measures such as Jacard similarity, Dice coefficient, sensitivity and specificity. Automated detection by the proposed method has the potential to enable fast quantifiable analysis of hESCs using large data sets which are needed to understand dynamic cell behaviors.
Editorials and Announcements
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- TCBB celebrates its 10th Anniversary. Editor-in-Chief Ying Xu says, "The emergence and maturation of increasingly more and powerful molecular measurement technologies such as next generation sequencing and chromosome conformation capture allow scientists to tackle biological problems at the depth and breadth that we have never seen before. At the same time the enormity and complexity of the data generated using these technologies raised tremendous challenges to computational scientists to develop more effective techniques to store, transmit, organize, process, analyze and mine the data, and to construct models to assist interpreting the data. Since its creation ten years ago, TCBB has been playing a major role in bridging the world of computing and the world of biology. I want to congratulate what the journal has done in providing biologists with the most powerful computational tools to help address their data and modeling needs. I fully expect that TCBB will continue to play increasingly significant roles in attracting more computational scientists to address the ever increasing needs for new and more powerful computational techniques and to introduce to new comers the important and challenging computational biology problems in a timely fashion."
- eBooks of issues of TCBB can now be downloaded from the Computer Society Digital Library
- Subscribe to TCBB in 2014. Click for more information. (PDF)
- EIC Editorial by M.-F. Sagot (March/April 2011)
- EIC Editorial by M.-F. Sagot (January/February 2011)
- Pattern Recognition in Bioinformatics (May/June 2014)
- Special Section on Bioinformatics Research and Applications (May/June 2014)
- Bioinformatics and Computational Systems Biology (July/August 2012)
- High Performance Computational Systems Biology (May/June 2012)
- Special Section on Bioinformatics Research and Applications (July/August 2011)
- Special Focus on Bioinformatics and Systems Biology (March/April 2011)
- Special Section on Bioinformatics Research and Applications (Oct-Dec 2010)
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TCBB is a joint publication of the IEEE Computer Society, Association for Computing Machinery, IEEE Computational Intelligence Society, and the IEEE Engineering in Medicine and Biology Society.
Published in cooperation with: IEEE Control Systems Society
Indexed in MEDLINE®/PubMed® & ISI
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) is a bimonthly journal that publishes archival research results related to the algorithmic, mathematical, statistical, and computational methods that are central in bioinformatics and computational biology.
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