ACME specifications

Information


Unique identifier OMICS_32968
Name ACME
Alternative name Attention-based Convolutional neural networks for MHC Epitope binding prediction
Software type Application/Script
Interface Command line interface
Restrictions to use None
Input data Some peptide and MHC sequences, both encoded based on the standard BLOSUM50 scoring matrix, with each residue encoded by the corresponding row of this matrix.
Output data The average prediction score over all the networks in the ensemble.
Operating system Unix/Linux
Programming languages Python
Computer skills Advanced
Stability Stable
Maintained Yes

Download


download.png

Versioning


No version available

Maintainers


  • person_outline Jianyang Zeng
  • person_outline Weiren Huang

Publication for Attention-based Convolutional neural networks for MHC Epitope binding prediction

ACME institution(s)
School of Life Sciences, Tsinghua University, Beijing, China; Department of Urology, Shenzhen Second People’s Hospital, The First Affiliated Hospital of Shenzhen University, International Cancer Center, Shenzhen University School of Medicine, Shenzhen, China; School of Medicine, Tsinghua University, Beijing, China; Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing, China; Turing AI Institute of Nanjing, Nanjing, China; Department of Computer Science and Technology, Tsinghua University, Beijing, China; Bioinfomatics Division, Beijing National Research Center for Information Science and Technology, Beijing, China; MOE Key Laboratory of Bioinformatics, Tsinghua University, Beijing, China

ACME reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review ACME