Manage a genome.  The genome, aka chromosome, is the solution to the 
  problem trying to be solved via genetic optimization.  It is referred to 
  as being composed of genes that are manipulated by the crossover and 
  mutation operators.  In our genetic optimization module this genome is 
  basically just a schrodinger.structure.Structure object.
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          | copy(self,
        genome) Copy the current genome to the provided genome.
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    | StructureGenome | 
        
          | clone(self) Clone the current genome.
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          | resetParentProperties(self) Reset the crossover and mutation parent structure properties.
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          | removeProperties(self) Remove some structure properties.
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          | optimizeGeometry(self) Optimize the geometry of this genome's structure using OPLS.
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          | evaluate(self,
        **args) Evaluate the score of this individual.
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    | Inherited from pyevolve.GenomeBase.GenomeBase:__repr__,getFitnessScore,getParam,getRawScore,initialize,mutate,resetStats,setParams |