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Nemo specifications


Unique identifier OMICS_17388
Name Nemo
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages C++
License GNU General Public License version 2.0
Computer skills Advanced
Version 2.3.46
Stability Beta
Maintained Yes




No version available


  • person_outline Frederic Guillaume

Publication for Nemo

Nemo citations


What, if anything, are hybrids: enduring truths and challenges associated with population structure and gene flow

Evol Appl
PMCID: 4947152
PMID: 27468308
DOI: 10.1111/eva.12380

[…] We used individual‐based, genetically explicit simulations to generate pseudo‐data under different demographic and evolutionary histories. Simulations were conducted using the program nemo version 2.3.44 (Guillaume and Rougemont ). Generations were discrete, and each generation consisted of the following ordered events: breeding, dispersal, viability selection (some histories), and […]


Comparative evaluation of potential indicators and temporal sampling protocols for monitoring genetic erosion

Evol Appl
PMCID: 4231590
PMID: 25553062
DOI: 10.1111/eva.12197
call_split See protocol

[…] ealism, which enables more thorough assessment of how a method can be expected to perform in real-world conditions (Landguth et al. ; Hoban et al. ; Hoban ). We therefore used the simulation software Nemo (Guillaume and Rougemont ) to perform generation-by-generation, individual-based simulations of populations that experience realistic demographic decreases. We then sampled from the simulated dat […]


High variance in reproductive success generates a false signature of a genetic bottleneck in populations of constant size: a simulation study

BMC Bioinformatics
PMCID: 3852946
PMID: 24131797
DOI: 10.1186/1471-2105-14-309

[…] s using computer simulations [,]. Summary statistics from observed data can be compared to a distribution of expected values from simulated data created with forward simulations, in simuPOP, spip [], Nemo [], cdpop [] or other software []. The distribution of reproductive success and other aspects of the species’ reproductive system can be taken into account in the simulations, allowing the invest […]


Understanding admixture patterns in supplemented populations: a case study combining molecular analyses and temporally explicit simulations in Atlantic salmon

Evol Appl
PMCID: 3689348
PMID: 23798972
DOI: 10.1111/j.1752-4571.2012.00280.x

[…] In simulated data, the Structure program identified three genetic clusters (k) corresponding to AUL, GAV, and BMS samples ( & ). The variability of admixture estimates among Nemo and Structure runs was relatively low for a same scenario (average standard deviations of 0.03 and 0.01, respectively). 90% credible intervals were relatively narrow and of the same magnitude as […]


Long distance gene flow and adaptation of forest trees to rapid climate change

Ecol Lett
PMCID: 3490371
PMID: 22372546
DOI: 10.1111/j.1461-0248.2012.01746.x
call_split See protocol

[…] rts should be dedicated to foster development of integrated computer simulation platforms with this aim. Individual-based, population and quantitative genetics simulation packages already exist (e.g. Nemo, ; e.g. Metapop, ) that could be extended to include the ecological and spatially explicit layers needed.A key aspect of the modelling approach advocated here is the overlay of predictions from d […]


Simulation of Genes and Genomes Forward in Time

Curr Genomics
PMCID: 2851118
PMID: 20808525
DOI: 10.2174/138920210790218007

[…] combination, and migration, however, is somewhat limited by the genome size it can manage. FREGENE [] simulates complex demographic and evolutionary models similarly to GenomePop []. KernelPop [] and NEMO [] implement individual-based, spatially explicit models. KernelPop uses the R environment []. Mendel's Accountant [] performs forward-time population simulations and can be supported on parallel […]

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Nemo institution(s)
Department of Ecology and Evolution, University of Lausanne, Biofore, Lausanne, Switzerland; Department of Zoology, University of British Columbia, Vancouver, BC, Canada; Vital-IT, Swiss Institute of Bioinformatics, Quartier Sorge-Genopode, Lausanne, Switzerland
Nemo funding source(s)
This work has been supported by SNSF grants 31-059442, 31-1000348 and 31-108194.

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