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The fifth challenge in the analysis of the urban social movements is therefore the problem of defining their political significance.
Thus data pretreatment, or normalisation, has been recognised as a major challenge in the analysis of microarray data.
A central challenge in the analysis of social networks is to identify the central individuals within a certain context solely based on their position in the global structure of the interactions [24, 25].
Another problem is the quality of older data, a common challenge in the analysis of retrospective databases.
The issue of heterozygosity continues to be a challenge in the analysis of genome sequences.
One main challenge in the analysis of protein interaction networks are false positive edges.
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Incorporating PRO instruments as study endpoint measures introduces challenges in the analysis of clinical trial data.
The meeting highlighted challenges in the analysis of expression data from archival tissues and strategies being developed to overcome them.
Finally, heterogeneity of data quality, and the presence of unknown confounders may pose challenges in the analysis of data and the attribution of cause.
One of the main challenges in the analysis of microarray data is to identify common underlying biological themes by integrating multiple similar experiments.
However, any change or failure in the spot identification may affect the peptide identification in the downstream proteomics as explained later in the challenges section (Challenges in the analysis of the 2-DE images).
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