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A new Python library to analyse skeleton images confirms malaria parasite remodelling of the red blood cell membrane skeleton.
Nunez-Iglesias, Juan; Blanch, Adam J; Looker, Oliver; Dixon, Matthew W; Tilley, Leann.
Afiliación
  • Nunez-Iglesias J; Melbourne Bioinformatics, The University of Melbourne, Melbourne, Australia.
  • Blanch AJ; Department of Biochemistry and Molecular Biology, Bio21 Institute, University of Melbourne, Melbourne, Australia.
  • Looker O; Department of Biochemistry and Molecular Biology, Bio21 Institute, University of Melbourne, Melbourne, Australia.
  • Dixon MW; Department of Biochemistry and Molecular Biology, Bio21 Institute, University of Melbourne, Melbourne, Australia.
  • Tilley L; Department of Biochemistry and Molecular Biology, Bio21 Institute, University of Melbourne, Melbourne, Australia.
PeerJ ; 6: e4312, 2018.
Article en En | MEDLINE | ID: mdl-29472997
ABSTRACT
We present Skan (Skeleton analysis), a Python library for the analysis of the skeleton structures of objects. It was inspired by the "analyse skeletons" plugin for the Fiji image analysis software, but its extensive Application Programming Interface (API) allows users to examine and manipulate any intermediate data structures produced during the analysis. Further, its use of common Python data structures such as SciPy sparse matrices and pandas data frames opens the results to analysis within the extensive ecosystem of scientific libraries available in Python. We demonstrate the validity of Skan's measurements by comparing its output to the established Analyze Skeletons Fiji plugin, and, with a new scanning electron microscopy (SEM)-based method, we confirm that the malaria parasite Plasmodium falciparum remodels the host red blood cell cytoskeleton, increasing the average distance between spectrin-actin junctions.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: PeerJ Año: 2018 Tipo del documento: Article País de afiliación: Australia

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: PeerJ Año: 2018 Tipo del documento: Article País de afiliación: Australia