GitHub - Sarikaya-Lab-GEMSEC/Iterative-Alignment: This program is designed to randomly perturb a given Amino Acid Similarity matrix and maximize the similarity (calculated via the Needleman-Wunsch algorithm) between sequences having high and low affinity to a single-layer material or a protein.

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This program is designed to randomly perturb a given Amino Acid Similarity matrix and maximize the similarity (calculated via the Needleman-Wunsch algorithm) between sequences having high and low affinity to a single-layer material or a protein.

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IterativeAlignment.py		IterativeAlignment.py
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How to use IterativeAlignment.py


1) Each matrix you want to work with in a single run must be in the same folder as a ".csv" file. In the given format (see example matrix)


2) Each peptide dataset must be divided into high binders and low binders (or non-binders) and labeled as "high.csv" and "low.csv" respectively.
        a. Similar to the matrices each database that is needed to run in a single run, must be in a folder with each subfolder containing 
           both the high and low files.
3) It is recommended to create a seperate folder for each result to save to, but not necessary.


4) The iterations, cutoff, Dataset Selection, and Gap Penalty all must be positive integers. The perturb percentage must be 0 < x < 1.