1 - 5 of 5 results


Identifies the most diverse randomer that is free of recognition sites for any set of restriction enzymes. CutFree converts the problem of blocking restriction sites into a mixed-integer linear program (MILP) that returns a site-free randomer of maximum diversity. It can be applied to block a randomer of any length from containing arbitrary sequences. This tool ensures large numbers of barcode sequences and is compatible with restriction enzyme assembly methods like Golden Gate cloning.


Generates unbiased random sequences with pre-specified amino acid and GC content, which has been developed into a python package. NullSeq method allows users to obtain maximally unbiased random sequences that are subject to GC usage and primary amino acid sequence constraints. Furthermore, this approach can easily be expanded to create unbiased random sequences that incorporate more complicated constraints such as individual nucleotide usage or even di-nucleotide frequencies. The ability to generate correctly specified null models will allow researchers to accurately identify sequence motifs which will lead to a better understanding of biological processes as well as more effective engineering of biological systems.