Getting the Noise Out of Gene Arrays
By E. Marshall. Science, 2004
322 citations recorded by the source corpus.
Subfields: Molecular Biology
View Paper: https://www.semanticscholar.org/paper/3f9e057e6c233a198510022a93a32d925e805cb5
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Molecular Biology
- Arthur Gretton
- Alex Smola
- Bernhard Schölkopf
- Karsten M. Borgwardt
- Malte J. Rasch
- Roger Perkins
- Hans-Peter Kriegel
- Kathleen Marchal
Citations in the corpus
- Advantages and limitations of current network inference methods (2010, background): “The large number of possible solutions (the large search space ), together with the restricted number of independent data points and the low information content of the available dat”
- Integrating structured biological data by Kernel Maximum Mean Discrepancy (2006, methodology): “Recently, Marshall (2004) gave an extremely negative picture of cross-platform comparability — and hence the reliability and reproducibility — of microarray results, due to the various platforms and data analysis methods employed (Shi et al., 2005).”
- The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies (2008, background): “Criticism of and concerns about microarrays continue to appear in some of the most prestigious scientific journals [6-10], leading to a growing negative perception regarding microarray reproducibility, and hence reliability.”