Our approach involves five main components, each of which is described briefly below (Fig.1cand Supplementary Fig.1; see Methods): (I) Data processing; (II) construction of a SNP–SNP interaction network; (III)
Eukaryotic genetic interaction networks (GINs) are extensively described in theSaccharomyces cerevisiaeS288C model using deletion libraries, yet being limited to this one genetic background, not informative to individual drug response. Here we created deletion libraries in three additional genetic background...
Protein kinases and phosphatases regulate protein phosphorylation, a critical means of modulating protein function, stability and localization. The identification of functional networks for protein phosphatases has been slow due to their redundant nature
When implemented with a factor analysis algorithm, AIC and BIC model selection criteria (MSC) outperform the other four MSC on inferring genetic networks using data simulated from a linear dynamic model [3]. However, the suitable MSC and search space (power law or non-power law) for GASA app...
3). Similarly, no evidence of interaction was found between UIE and PGS (β = 0.1; 95% CI − 1.9 to 2.1; P = 0.93). Fig. 3 Sensitivity analysis: change in the FI score per 1 SD increase in either UIE (blue) or PGS for general cognitive function (orange) in the...
Therefore, such events are highly impacted by the different cell/tissue structures, the reproductive mode as well as the degree of interaction of the species involved [6,7,8,9]. Several multicellular eukaryotic species present several barriers to DNA exchange by HT such as: (i) cellular ...
Data S1. Hierarchical Interaction Score Network and HIS Yeast versus Human Conserved Network, Related to Figures 4 and 5 Table S1. Primary Screening Results, Related to Figure 1 Table S2. RT-qPCR Results, Related to Figure 1 Table S3. Secondary Screening Results, Related to Figure 1 Table ...
Comparing how mutations combine at different expression levels in the full model revealed that changes in expression not only alter the magnitude of genetic interactions but can also switch their direction of interaction (between positive and negative interactions, Fig.4a, b). Re-analysis of the exp...
This feature is especially useful in the inference of gene relationships, which can be due to physical interaction, overlapping gene function, or coordinated contributions to a larger cellular process. Here, we show that the use of dimensionality reduction by UMAP on bulk expression profiling data ...
Therefore, the two QTL clusters should be a result of interaction between hbd2 and hbd3. Although we could not elucidate gene interactions for other QTLs detected in only one of the reciprocal backgrounds, detection of many QTLs in only one genetic background suggests that a large part of ...