Bioimage Informatics: a new thematic series

BMC Bioinformatics launches its latest article collection today, focusing on Bioimage Informatics.

Fig 1 Peng et al BMC Bioinformatics (2013) 14,293Edited by Ivo Sbalzarini, Pavel Tomancak and Hanchuan Peng, Section Editor for BMC Bioinformatics (Allen Institute for Brain Science, Seattle, USA), this thematic series focuses on the latest developments in the emerging field of computational analysis, management, visualization, and mining of biological images. In an accompanying commentary by Peng the major issues in computational neuroscience are highlighted along with suggestions on potential solutions based on bioimage informatics, especially automated image computing.

Several articles in this series propose novel segmentation methods for detecting cell nuclei (Azuma and Onami, and Buggenthin et al., Navlakha et al., and Song et al.), determining cell morphology (Du et al.), and identifying gene knock-down cell morphologies (Failmezger et al.), from microscopy and time-lapse images.

Pattern recognition is also the focus of two articles including the development of the BIOimage Classification and Annotation Tool (BIOCAT) for pattern recognition based biological image classification of 2D and 3D images by Zhou et al., and the fully automatic 3D facial image mapping method, presented by Guo et al., that enables the high-throughput capture and analysis of the wide spectrum of variation in human facial morphology. All these articles and more are available to read on the series homepage.

New articles will be added continuously to the article collection. Please join the discussions by using the ‘comment’ option below each individual article.

Posted on behalf of Tam Sneddon

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