GSR: Simulator - NanoSimFormer

AttributeValue
TitleNanoSimFormer
Short DescriptionTransformer-based nanopore raw signal simulator.
Long DescriptionNanoSimFormer is an end-to-end deep learning simulator for nanopore sequencing signal data that uses a Transformer architecture and basecaller-guided training to generate raw signals suitable for downstream basecalling, variant calling, and assembly benchmarking.
Keywordsnanopore sequencing; raw signal simulation; Transformer; deep learning; basecaller guidance; Python
Version2026-02-18
Homepagehttps://github.com/BioinfoSZU/NanoSimFormer
Citations
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Author verificationThe basic description provided was derived from a website or publications by the GSR team and has not yet been verified by the simulation author. To modify this entry or add more information, propose changes to this simulator.
Attribute CategoryAttribute
Target
Type of Simulated DataSequencing Reads,
VariationsSingle Nucleotide Variation,
Simulation Method
Input
Data Type
File format
Output
Data TypeGenotype or Sequence,
Sequencing Reads
File Format
Sample Type
Phenotype
Trait Type
Determinants
Evolutionary Features
Demographic
Population Size Changes
Gene Flow
Spatiality
Life Cycle
Mating System
Fecundity
Natural Selection
Determinant
Models
Recombination
Mutation Models
Events Allowed
Other
InterfaceCommand-line, Script-based,
Development
Tested PlatformsLinux and Unix,
LanguagePython,
License
GSR Certification

Number of Primary Citations: 0

Number of Non-Primary Citations: 0

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