Genetic Algorithm for Assigning Weights to Gene Expressions using Functional Annotations

        Welcome to the page for assigning proper weights to expressions at each time point of gene expression data using functional annotations of genes.

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The steps for assigning proper weight in each time point (using Matlab and 16GB RAM) are as follows:

·        Download yeastallgoprocessvector.mat. When loaded in Matlab the file will create a variable "vector" which will provide annotation profiles for Saccharomyces cerevisiae genes using yeast GO-Slim process annotations in SGD.

·        Download the expression values yeastalllsadaptive.mat for All Yeast data set.

·        Download the Main Program (mainGA_AY.m) for assigning proper weight in expressions of each time point. Before running this program one has to keep all other downloadable files, mentioned above and below, in the same folder of the Main Program. The main program will return the optimum weight combination.

·        Download InitPop.m for Initial Population. Here we choose the population size as 20. One can chnage the population size at Main Program as it is inputed from keyboard.

·        Download Fitnessfcn.m for calculating PPV for top 10,000 gene pair. The optimal weight combination is the one where the PPV for top 10,000 is maximized.

·        Download RankSelection.m for linear normalization selection.

·        Download Crossover.m for one point crossover. Here we choose the crossover probabilty as 0.85. One can chnage the selection probabilty at Main Program as it is inputed from keyboard.

·        Download Mutation.m for inverse mutation. Here we choose the mutation probabilty as 0.1. One can chnage the mutation probabilty at Main Program as it is inputed from keyboard.