Tmp-ssurface: a deep learning-based predictor for surface accessibility of transmembrane

HIGHLIGHTS

  • who: Protein Residues and colleagues from the School of Information Science and Technology, Northeast Normal University, Changchun, China have published the research work: TMP-SSurface: A Deep Learning-Based Predictor for Surface Accessibility of Transmembrane, in the Journal: (JOURNAL)
  • what: In this work, the ASA of each residue was calculated by DSSP, Accessible surface area (ASA) refers to the surface accessibility of a residue when it exposes to the water or lipid. The authors proposed a sequence-based rASA predictor for the full sequence of all type of TMPs, called TMP-SSurface.
  • how . . .

     

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