By carefully choosing a smaller set of expression data, accurate functional prediction comparable with a state-of-the-art software tool becomes feasible.
However, the Arabidopsis co-regulatory networks can be used as reference for other species where a smaller set of expression experiments is available.
Most of the current work on automated facial expression analysis attempt to recognize a small set of prototypic expressions, such as joy and fear.
Furthermore, we selected for clustering the smallest set of genes with the greatest variance in expression (variance filter in TMEV program) that showed the most robust cluster result with the highest support from the bootstrap analysis.
To attain high disease diagnostic accuracy, many studies focus on identifying biomarkers from mass spectral profiles, which are generally a small set of protein expression peaks at selected m/z (mass/charge) ratios, through different machine learning approaches (e.g., peak selection), [ 7, 8].
With respect to recognition targets, most techniques attempt to recognize a small set of prototypic emotional expressions, that is, happiness, surprise, anger, sadness, fear, and disgust, as well as the neutral state.
Recent benchmarks and challenges have highlighted the good performance of methods which formalize the GRN inference problem as a regression and feature selection problem, namely, identifying a small set of TF whose expression levels are sufficient to predict the expression level of each TG of interest.
Analysis of four normal and 125 pancreatic tumor samples revealed a much smaller set of genes showing expression changes in tumors.
Unlike most traditional molecular biology tools, which only allow study of a single gene or a very small set of genes, gene expression microarrays provide a comprehensive overview of the entire transcriptional activity in a biological sample.
We found a small set of genes whose expression was altered by at least 1.5-fold in either the control versus galectin-1 siRNA ratio or in the scramble siRNA versus galectin-1 siRNA ratio (Table 1).
The formula we have derived links a small set of easily definable gene expression levels to the UHRDS Total Motor Score, and is thus a promising candidate biomarker set to monitor disease state, progression and putative therapeutic effect of interventions.
