silvio.extensions.utils package

Submodules

silvio.extensions.utils.laboratory module

silvio.extensions.utils.laboratory.ErrorRate(Invest, ResTotal=5000, relKM=0.005, Vmax=0.9)

Calculate the experimental error rate based on the investment to equipment. Based on inverse Michaelis-Menten equation mit max error 0.9 and min error 0.1.

silvio.extensions.utils.misc module

Methods that are not yet assigned to another place. They usually include methods before the restructuring. TODO: Almost all of the methods inside this file can me integrated into module functions.

silvio.extensions.utils.misc.Growth_Maxrate(growth_rate_const, Biomass)

TODO: Documentation is out of sync. The function calculates the maximum slope during growth.

Arguments:

Host: class, contains maximum biomass concentration as carrying capacity growth_rate_const: float, maximum growth rate constant

Output:

growth_rate_max: float, maximum growth rate

silvio.extensions.utils.misc.Help_GrowthConstant(OptTemp, CultTemp, var=5)

Function that generates the growth rate constant. The growth rate constant depends on the optimal growth temperature and the cultivation temperature. It is sampled from a Gaussian distribution with the mean at the optimal temperature and variance 1. Arguments:

Opt_Temp: float, optimum growth temperature, mean of the Gaussian distribution Cult_Temp: float, cultivation temperature for which the growth constant is evaluated var: float, variance for the width of the Gaussian covering the optimal growth temperature

Output:

growth_rate_const: float, constant for use in logistic growth equation

silvio.extensions.utils.misc.Help_PromoterStrength(PromSequence, RefPromoter: str, Scaler=1, Similarity_Thresh=0.4, Regressor_File=None, AddParams_File=None) → float

TODO: Some arguments are missing. Expression of the recombinant protein.

Arguments:

Host: class, contains optimal growth temperature, production phase Sequence: string, Sequence for which to determine promoter strength Scaler: int, multiplied to the regression result for higher values Predict_File: string, address of regression file

Output:

Expression: float, expression rate

silvio.extensions.utils.misc.Sequence_ReferenceDistance(SeqObj, RefSeq)

Returns the genetic sequence distance to a reference sequence. Input:

SeqDF: list, the sequence in conventional letter format

Output:

SequenceDistance: float, genetic distances as determined from the sum of difference in bases divided by total base number, i.e. max difference is 1, identical sequence =0

silvio.extensions.utils.misc.check_primer_integrity_and_recombination(Promoter: Bio.Seq.Seq, Primer: Bio.Seq.Seq, Tm: int, RefPromoter: Bio.Seq.Seq, OptPrimerLen: int) → silvio.outcome.Outcome

Experiment to clone selected promoter. Return whether the experiment was successful.

silvio.extensions.utils.shotgun_sequencing module

silvio.extensions.utils.transform module

Methods used in the Transform step of a ETL pipeline.

silvio.extensions.utils.transform.list_integer(SeqList)

define input values

silvio.extensions.utils.transform.list_onehot(IntegerList)

silvio.extensions.utils.visual module

Utilities used for interaction with the student.

silvio.extensions.utils.visual.Help_Progressbar(n, loading_time, add)

function for display of a loading bar, n: width of loading bar