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Probabilistic_Graphical_Models_Project

For EN.625.692.81.SP24

Using Conditional Random Fields to predict beta-helix protein folding. Based on "Protein Fold Recognition Using Segmentation Conditional Random Fields (SCRFs)" by Liu et al, 2006.

Candidate Methods:

sklearn-crfsuite source: https://github.com/TeamHG-Memex/sklearn-crfsuite/blob/master/docs/CoNLL2002.ipynb

with tutorial: https://sklearn-crfsuite.readthedocs.io/en/latest/tutorial.html

linear chain CRF source: https://github.com/mtreviso/linear-chain-crf

with tutorial: https://towardsdatascience.com/implementing-a-linear-chain-conditional-random-field-crf-in-pytorch-16b0b9c4b4ea

biRNN-CRF source: https://github.com/alrojo/biRNN-CRF/blob/master/cb513.ipynb

with paper: https://dl.acm.org/doi/pdf/10.1145/3107411.3107489

with data: https://github.com/LucaAngioloni/ProteinSecondaryStructure-CNN/blob/master/dataset.py

https://zenodo.org/records/7764556#.ZByi1ezMJvI

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