AFLPinSilico

AFLPinSilico simulates Amplified Fragment Length Polymorphism (AFLP) experiments to generate virtual fingerprints and link AFLP fragments to source cDNA or genomic sequences for high-throughput identification and analysis.

Key Features:

• Simulation of AFLP experiments: Performs in silico AFLP simulation on both cDNA and genomic sequences to produce predicted fragment patterns.
• High-throughput fragment identification: Enables simultaneous analysis and identification of numerous AFLP fragments across large sequence sets.
• Experimental design optimization: Allows prediction of expected AFLP outcomes to inform and refine laboratory experiment design.
• Virtual fingerprint generation: Produces virtual AFLP fingerprints from computationally generated fragments for downstream comparison and analysis.

Scientific Applications:

• Genetic mapping: Assists in identification of polymorphic markers across genomes to support detailed genetic mapping efforts.
• Population genetics: Facilitates analysis of genetic diversity within and between populations using simulated AFLP data.
• Biodiversity and phylogenetics: Enables comparison of AFLP fingerprints for studies of species differentiation and phylogenetic relationships.

Methodology:

Computational algorithms simulate the AFLP process by processing input DNA sequences (cDNA or genomic) to generate fragments and assemble virtual fingerprints for analysis and comparison.