v2.0.2

• Fixed installation issues.

v2.0.1

Updated DeepCoil2 neural network weights.

v2.0

• Retrained with the updated dataset based on SamCC-Turbo labels.
• Faster inference time by applying SeqVec embeddings instead of psiblast profiles.
• Heptad register prediction (a and d core positions).
• No maximum sequence length limit.
• Convenient interface for using DeepCoil within python scripts.
• Automated peak detection for improved output readability.
• Simplified installation with pip.

v1.1

Added custom output filtering options -min_residue_score and -min_segment_length.

v1.0

Initial release - corresponds to the version presented in the original paper DOI:10.1093/bioinformatics/bty1062