diSTruct v1.0: Generating Biomolecular Structures from Distance Constraints.

diSTruct v1.0: Generating Biomolecular Structures from Distance Constraints.

Taubert, Oskar;Reinartz, Ines;Meyerhenke, Henning;Schug, Alexander;
Bioinformatics 2019
233
taubert2019distructbioinformatics

Abstract

The distance geometry problem is often encountered in molecular biology and the life sciences at large, as a host of experimental methods produce ambiguous and noisy distance data. In this note, we present diSTruct; an adaptation of the generic MaxEnt-Stress graph drawing algorithm to the domain of biological macromolecules. diSTruct is fast, provides reliable structural models even from incomplete or noisy distance data and integrates access to graph analysis tools.diSTruct is written in C ++, Cython and Python 3. It is available from https://github.com/KIT-MBS/distruct.git or in the Python package index under the MIT license.Supplementary data is available at Bioinformatics online.

Access

Citation

ID: 3572
Ref Key: taubert2019distructbioinformatics
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
3572
Unique Identifier:
btz578
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet