Codon-bias

Latest version: v0.3.5

Safety actively analyzes 723650 Python packages for vulnerabilities to keep your Python projects secure.

Scan your dependencies

Page 2 of 2

0.2.0

- new:
- added scores.NormalizedTranslationalEfficiency
- added scores.CodonPairBias
- added stats.BaseCounter for nucleotide and k-mer statistics across reading frames
- added `k_mer` parameter to:
- stats.CodonCounter
- scores.CodonAdaptationIndex
- scores.EffectiveNumberOfCodons
- pairwise.CodonUsageFrequency
- added abstract class scores.WeightScore that computes a weight vector for each input sequence, with the following children:
- scores.CodonPairBias
- scores.EffectiveNumberOfCodons
- scores.RelativeSynonymousCodonUsage
- scores.RelativeCodonBiasScore
- improved:
- various improvements to scores.EffectiveNumberOfCodons
- background correction
- improved estimation
- added count() method to counter classes
- added `pseudocount` parameter to models

**Full Changelog**: https://github.com/alondmnt/codon-bias/compare/0.1.0...0.2.0

0.1.0

First release.

- stats.CodonCounter
- scores.FrequencyOfOptimalCodons (FOP)
- scores.RelativeSynonymousCodonUsage (RSCU)
- scores.CodonAdaptationIndex (CAI)
- scores.EffectiveNumberOfCodons (ENC)
- scores.TrnaAdaptationIndex (tAI)
- scores.RelativeCodonBiasScore (RCBS + DCBS)
- pairwise.CodonUsageFrequency (CUFS)

Page 2 of 2

© 2025 Safety CLI Cybersecurity Inc. All Rights Reserved.