Archives for posts with tag: cell adhesion

Our paper on extracellular matrix networks and stem cell growth makes the cover of this week’s issue of the Journal of Biological Chemistry. The stunning image by Despina Soteriou captures stem cells growing in a web of extracellular matrix.

Journal of Biological Chemistry cover, 2013, vol. 288 (no. 26) // Image by Despina Soteriou

Journal of Biological Chemistry cover, 2013, vol. 288 (no. 26)

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Research at the University of Manchester has identified networks of proteins that control the fate of our body’s stem cells, findings that could aid progress towards new disease therapies.

Extracellular matrix networks control stem cell fate // Image by Adam Byron

Stem cells have the amazing ability to develop into different types of cells of the body, such as blood cells, muscle cells or brain cells. Remarkably, stem cells can also regenerate, essentially renewing themselves an unlimited number of times.

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Proteomics Clinical Applications cover, 2012, vol. 6 (no. 7-8) // Image by Adam Byron // Reproduced with permission from Wiley-VCH Verlag GmbH & Co. KGaA

Proteomics Clinical Applications cover, 2012, vol. 6 (no. 7-8)

My image features on the cover of the current issue of the journal Proteomics Clinical Applications.

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My paper has been published in the current issue of the journal Proteomics. The paper also makes the cover of the issue, which is a special issue on the theme of Cancer Proteomics.

Proteomics cover, 2012, vol. 12 (no. 13) // Images by Adam Byron & Sue Craig // Reproduced with permission from Wiley-VCH Verlag GmbH & Co. KGaA

Proteomics cover, 2012, vol. 12 (no. 13)

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Interpreting proteomic data // Image by Adam Byron

Proteomic analyses, which often aim to catalogue – to ever-increasing depths – all the proteins present in a particular biological sample, generate vast sets of data. Of course, these datasets are only useful if they are interrogated to extract meaningful information, which is not a trivial task. Proteomic data are usually interpreted on the basis of current knowledge, which is important to gain understanding in the context of the experiment. Still, proteomic approaches such as mass spectrometry lend themselves to the discovery of new insights into proteins.

My letter in today’s issue of the Journal of Proteomics argues that the interpretation of proteomic data should be open to the possibility of identifying unexpected functions or subcellular locations of proteins.

Such approaches to the analysis of the ever-increasing volume of large-scale datasets will likely lead to many new discoveries.

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