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Simulator005 investigates the the accumulation of harmful and beneficial DNA-changes in non-recombining populations. These asexual systems can experience a phenomenon called "Muller's ratchet" and might help to understand the evolution of human mitochondrial DNA.

Simulator005 investigates Muller's ratchet in a single asexual population to determine rates of mutation accumulation for many different potentially realistic situations.

The constant onslaught of slightly harmful DNA changes may be a significant cause of extinction of species on the long term. This simulator helps to uncover the true extent of the problem in asexual genomes. The results have implications for all non-recombining genomes such as mitochondrial DNA in humans or other organisms. They further deepen our understanding of the importance of sex (= regular recombination of genetic material) for the long term survival of organisms. Thus, in a broader sense, the results computed by this simulator help understand more about the origins and evolution of life on our wonderful planet earth.

You can read more about the principle of Muller's ratchet and about the various properties of organisms that might affect the speed of Muller's ratchet.

To get started, follow these quick instructions for computing.

If you are interested in the published results from this simulator, please find them under


Simulator005 is defined by these parameters

If you want to know the values of the parameters listed below for a currently running simulation, just open the eParametersList.txt file in your simulators folder. It is updated regularly.

Besides these values, a result as written to the results-file contains your personalization data (if you did not stay anonymous) and a long list of all clicks actually observed during the simulation (if the Ratchet had clicked). 

All lines below follow the format
Abbreviation ParameterID Explanation

Simulator005 accepts the following input-parameters

K 1 Carrying capacity of the population
Ri 2 Initial reproductive capacity
Ub 3 Genomic mutation rate for background mutations 
Sb 4 Selection coefficient for background mutations
dmeb 5 Distribution of mutational effects (background)
Ur 6 Genomic mutation rate for the Ratchet observed 
Sr 7 Selection coefficient for the Ratchet observed 
dmer 8 Distribution of mutational effects (Ratchet) 
Cend 9 Clicks to observe before worldhistory can stop 
Tend 10 Last generation in standard worldhistory 
rfcID 11 ID of RunFileCollection this simulation belongs to
rndseed 12 First seed used to initialize global RND generator 

Simulator005 computes the following output parameters

Computing Statistics
err 14 Errors since start of this worldhistory 
intm 15 Result is intermediate (=1) or complete (=0)
timev 16 Total seconds needed for last evolve&observe-loop
timpr 17 Total amount of work (GigaIndividuals) predicted
timwh 18 Total seconds computing time for this single-run
GIo 19 Workunits in this run (in gigaindividuals)
minds 20 Performance during current single run in MINDS 

Unique events in simulated world history
Teq 21 Time from perfect start to exp(-U) fitness 
Tclfd1 22 Time from perfect start to 1.FitnessDownClick 
Tclfi1 23 Time from perfect start to 1.FitnessIncrClick
Tclb1 24 Time from perfect start to 1.background click 
Tclr1 25 Time from perfect start to 1. Ratchet click 
mmpr 26 Date where meltdown is predicted to start 
Tmm 27 Date where meltdown started 
Tex 28 Extinction time (single run) 
wtim 29 Current world time in current simulation 

Timeseries summaries: background information
aclfd 30 Absolute click time for fitness decreases 
eclfd 31 Effective click time for fitness decreases 
clsfd 32 Click size of fitness decreases 
aclfi 33 Absolute click time for fitness increases 
eclfi 34 Effective click time for fitness increases 
clsfi 35 Click size of fitness increases 
atcb 36 Click time (absolute) of background mutations
etcb 37 Click time (effective) of background mutations 
tcbpr 38 Predicted click time of background mutations 
clsb 39 Click size of background mutations 

Timeseries summaries: Muller's ratchet observations
atcr 40 Click time (absolute) of Ratchet mutations
etcr 41 Click time (effective) of Ratchet mutations 
tcrpr 42 Predicted click time of Ratchet mutations
clsr 43 Click size of Ratchet mutations 

Multiple clicks 
cl1 44 Absolute time for clicks that fix 1 mutation 
cl2 45 Absolute time for clicks that fix 2 mutations 
cl3 46 Absolute time for clicks that fix 3 mutations 
cl4 47 Absolute time for clicks that fix 4 mutations 
cl5 48 Absolute time for clicks that fix 5 mutations 

Duration of phases of a click 
T1a 49 Duration of phase 1a for Ratchet (n1 to 1.6*no) 
T1b 50 Duration of phase 1b for Ratchet (1.6*no to no)
T2 51 Duration of phase 2 for Ratchet (no to 0) 

Sizes of various population subgroups 
Nt 52 Average total population size over worldhistory
Nod 53 Individuals with highest fitness (best class)
Noi 54 Individuals with lowest fitness (worst class) 
irNo 55 Analytic best class size for Ratchet 
Nor 56 Individuals with least Ratchet mutations 
ibNo 57 Analytic best class size, background mutations 
Nob 58 Individuals with least background mutations

Snapshot of features of the last generation
Df 59 Distribution of overall genetic fitness in population
Dr 60 Number of Ratchet mutations per genome
Db 61 Number of background mutations per genome


Timeseries and snapshot parameters 

Many output parameters belong to the time series (30-37, 39-41, 43- 54,56,58) or snapshot type (59-61). They are currently treated as normally distributed data and the following values are recorded during simulation (or inferred from recorded values upon request): 

  • Mean (m) of the inferred Normal distribution, upon request.
  • Standard deviation (sd), upon request.
  • Coefficient of variation (CV = sd/m), upon request. 
  • Sample size (n), recorded. 
  • Absolute minimum (min) of all values, recorded. 
  • Absolute maximum (max) of all values, recorded. 
  • Current value (curr = last value observed), recorded. 
  • Sum of all values (sum), recorded. 
  • Sum of squared values (ssq), recorded. 

Please note that all these numbers are stored as 64 bit (double) IEEE floats, the same elementary data type used for all other parameter values as well. This limits numerical accuracy to at most 15 decimal positions, but allows for exponents of >±300 and high computational speed on modern CPUs. An in-depth discussion of numerical limits can be found elsewhere (Goldberg 1991; Kahan 1997). 



Goldberg, D. (1991) 'What every computer scientist should know about floating-point arithmetic',

Kahan, W. (1997) 'Lecture Notes on the status of IEEE standard 754 for binary floating-point arithmetic',




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