Sentence examples for between the query disease from inspiring English sources
(Recall that in the ab initio prediction, we completely remove all known associations between the query disease and other genes).
The strength of association between the query disease and a candidate gene was then assessed by a hypothesis testing procedure and quantified by the corresponding p-value.
If there is a similarity at the genetic level between the query disease and the reference disease, we expect more individuals with the query disease to be classified as belonging to the disease class than if there is no similarity.
A common characteristic of these methods is the requirement of a set of genes known as associated with a query disease before the inference of novel associations between the query disease and candidate genes.
We then fit this model using the lasso penalty strategy and calculate the coefficient of determination (R) of the fitted model as a score to measure the strength of association between the query disease (d) and the candidate gene (g).
We also removed all annotated associations between the query disease and genes in the regression model to pretend that the genetic basis of the query disease is completely unknown.
A naïve thinking of identifying disease-related protein complex is to quantify the strength of associations between proteins and the query disease and then sum over the scores of member proteins to obtain a score for a protein complex.
Once the maximum information flow f* has been calculated, we define for each candidate gene vertex u∈ S the total amount of net flow leaving u as | f u +|=Σ v ∈ V ″, f (u, v )>0 f* u, v) and we use the value of this positive flow as a score to indicate the strength of the association between u and the query disease d.
With the steady-state probability (denoted by q obtained, we further calculate a normalized score s i for the ith complex as (3) s i = q l + m + i ∑ i = 1 n q l + m + i and use this score to quantify the strength of association between the complex and the query disease.
The novelty of our method and the key to its success lie in the information flow model which is based on the premise that the relationship between a query disease and the candidate genes can be captured by the maximum information flow sent from the query disease to the genes.
