Published April 6, 2020 | Version 1.0.0

MCMC data for A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment and novelty detection

  • 1. Cambridge Centre for Proteomics
  • 2. MRC Biostatistics Unit
  • 3. de Duve Institute, UCLouvain,

Description

These are unprocessed Markov-chain Monte-Carlo datasets accompanying the manuscript "A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment and novelty detection"

Files

Files (18.9 GB)

Name Size
md5:b5035e67f9b6af24955a3d7dcff06ded
871.7 MB Download
md5:5bf98c040ced554c6c418c19f8affb3d
890.0 MB Download
md5:67a4e8fc97372391f534f3f42ff55dd2
2.9 GB Download
md5:583bb2be950ed0ae004f413b7fefdba3
394.4 MB Download
md5:039ec02ff0caba909d2b0510f25ef7dc
828.6 MB Download
md5:383851869f28ee4b45d68c72bb8aab37
2.2 GB Download
md5:b5b5bc2242847581e31a80ad423b8c70
1.5 GB Download
md5:3b165173985cfe8043bbe5440486f035
2.1 GB Download
md5:98c1ad03f3dc4007b45062fd7ae7d196
1.5 GB Download
md5:124e032001f34cd8843adb0ffc624745
1.6 GB Download
md5:a7e88812f5419d74da7532a925e3dee8
4.1 GB Download