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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Tab1 Kempler DataScienceJournal2017 16.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig4 Auer CytometryPartA2018 93-7.jpg|240px]]</div>
'''"[[Journal:Earth science data analytics: Definitions, techniques and skills|Earth science data analytics: Definitions, techniques and skills]]"'''
'''"[[Journal:ChromaWizard: An open-source image analysis software for multicolor fluorescence in situ hybridization analysis|ChromaWizard: An open-source image analysis software for multicolor fluorescence in situ hybridization analysis]]"'''


The continuous evolution of data management systems affords great opportunities for the enhancement of knowledge and advancement of science research. To capitalize on these opportunities, it is essential to understand and develop methods that enable data relationships to be examined and [[information]] to be manipulated. Earth science data analytics (ESDA) comprises the techniques and skills needed to holistically extract information and knowledge from all sources of available, often heterogeneous, data sets. This paper reports on the ground-breaking efforts of the Earth Science Information Partners' (ESIP) ESDA Cluster in defining ESDA and identifying ESDA methodologies. As a result of the void of earth science data analytics in the literature, the ESIP ESDA definition and goals serve as an initial framework for a common understanding of techniques and skills that are available, as well as those still needed to support ESDA. Through the acquisition of earth science research use cases and categorization of ESDA result oriented research goals, ESDA techniques/skills have been assembled. The resulting ESDA techniques/skills provide the community with a definition for ESDA that is useful in articulating data management and research needs, as well as a working list of techniques and skills relevant to the different types of ESDA. ('''[[Journal:Earth science data analytics: Definitions, techniques and skills|Full article...]]''')<br />
Multicolor image analysis finds its applications in a broad range of biological studies. Specifically, multiplex [[wikipedia:Fluorescence in situ hybridization|fluorescence ''in situ'' hybridization]] (M‐FISH) for chromosome painting facilitates the analysis of individual chromosomes in complex metaphase spreads and is widely used to detect both numerical and structural aberrations. While this is well established for human and mouse [[wikipedia:Karyotype|karyotypes]], for which species sophisticated software and analysis tools are available, other organisms and species are less well served. Commercially available software is proprietary and not easily adaptable to other karyotypes. Therefore, a publicly available open-source software that combines flexibility and customizable functionalities is needed. Here we present such a tool, called “ChromaWizard,” which is based on popular scientific image analysis libraries (OpenCV, scikit‐image, and NumPy). We demonstrate its functionality on the example of primary Chinese hamster (''Cricetulus griseus'') fibroblasts metaphase spreads and on Chinese hamster ovary cell lines, known for their large number of chromosomal rearrangements. ('''[[Journal:ChromaWizard: An open-source image analysis software for multicolor fluorescence in situ hybridization analysis|Full article...]]''')<br />
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''Recently featured'':  
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Revision as of 22:58, 24 February 2020

Fig4 Auer CytometryPartA2018 93-7.jpg

"ChromaWizard: An open-source image analysis software for multicolor fluorescence in situ hybridization analysis"

Multicolor image analysis finds its applications in a broad range of biological studies. Specifically, multiplex fluorescence in situ hybridization (M‐FISH) for chromosome painting facilitates the analysis of individual chromosomes in complex metaphase spreads and is widely used to detect both numerical and structural aberrations. While this is well established for human and mouse karyotypes, for which species sophisticated software and analysis tools are available, other organisms and species are less well served. Commercially available software is proprietary and not easily adaptable to other karyotypes. Therefore, a publicly available open-source software that combines flexibility and customizable functionalities is needed. Here we present such a tool, called “ChromaWizard,” which is based on popular scientific image analysis libraries (OpenCV, scikit‐image, and NumPy). We demonstrate its functionality on the example of primary Chinese hamster (Cricetulus griseus) fibroblasts metaphase spreads and on Chinese hamster ovary cell lines, known for their large number of chromosomal rearrangements. (Full article...)

Recently featured:

Haves and have nots must find a better way: The case for open scientific hardware
CytoConverter: A web-based tool to convert karyotypes to genomic coordinates
Implementing a novel quality improvement-based approach to data quality monitoring and enhancement in a multipurpose clinical registry