IMP Reference Guide
2.21.0
The Integrative Modeling Platform
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Functions for weighting graphNode objects based on stoichiometry data. More...
Functions for weighting graphNode objects based on stoichiometry data.
Functions | |
def | calc_likelihood |
Function that adds a score for the compositional likelihood for all states represented as nodes in the graph. More... | |
def | composition_likelihood_function |
Function that calculates the likelihood of an individual node, used by calc_likelihood(). More... | |
def | get_state |
function to calculate how many times a protein appears in a list of proteins, which can be accessed from a graphNode object using node.get_subcomplex_components() More... | |
def IMP.spatiotemporal.composition_scoring.calc_likelihood | ( | exp_comp_map, | |
nodes | |||
) |
Function that adds a score for the compositional likelihood for all states represented as nodes in the graph.
The composition likelihood assumes a Gaussian distribution for copy number of each protein or subcomplex with means and standard deviatiations derived from experiment. Returns the nodes, with the new weights added.
exp_comp_map | dictionary, which describes protein stoicheometery. The key describes the protein, which should correspond to names within the expected_subcomplexes. Only copy numbers for proteins or subcomplexes included in this dictionary will be scored. For each of these proteins, a csv file should be provided with protein copy number data. The csv file should have 3 columns, 1) "Time", which matches up to the possible times in the graph, 2) "mean", the average protein copy number at that time point from experiment, and 3) "std", the standard deviation of that protein copy number from experiment. |
nodes | list of graphNode objects, which have been already been initiated with static scores |
Definition at line 64 of file composition_scoring.py.
def IMP.spatiotemporal.composition_scoring.composition_likelihood_function | ( | mean, | |
std, | |||
prots, | |||
node | |||
) |
Function that calculates the likelihood of an individual node, used by calc_likelihood().
mean | dictionary of dictionaries where the first key is the protein, the second key is the time, and the expected mean copy number from experiment is returned. |
std | dictionary of dictionaries where the first key is the protein, the second key is the time, and the expected standard deviation of protein copy number from experiment is returned. |
prots | list of proteins or subcomplexes which will be scored according to this likelihood function |
node | the graphNode object for which the likelihood will be calculated. |
Definition at line 34 of file composition_scoring.py.
def IMP.spatiotemporal.composition_scoring.get_state | ( | subcomplex_components, | |
prot | |||
) |
function to calculate how many times a protein appears in a list of proteins, which can be accessed from a graphNode object using node.get_subcomplex_components()
subcomplex_components | subcomplexes or components in a given node, which can be accessed by graphNode.get_subcomplex_components() |
prot | string, protein or subcomplex we are interested in finding |
Definition at line 15 of file composition_scoring.py.