Treffer: Visualizing Protein Big Data Using Python and Jupyter Notebooks

Title:
Visualizing Protein Big Data Using Python and Jupyter Notebooks
Language:
English
Authors:
Weiss, Charles J. (ORCID 0000-0002-1092-2776)
Source:
Biochemistry and Molecular Biology Education. Sep-Oct 2022 50(5):431-436.
Availability:
Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed:
Y
Page Count:
6
Publication Date:
2022
Document Type:
Fachzeitschrift Journal Articles<br />Reports - Descriptive
Descriptors:
Visual Aids, Programming Languages, Data Analysis, Science Instruction, Teaching Methods, Biochemistry, Workshops, Conferences (Gatherings), Computer Software, Molecular Structure, Trend Analysis
DOI:
10.1002/bmb.21621
ISSN:
1470-8175
1539-3429
Entry Date:
2022
Accession Number:
EJ1349383
Database:
ERIC

Weitere Informationen

This article reports a workshop from the 2021 IUBMB/ASBMB Teaching Science with Big Data conference held virtually in June 2021 where participants learned to explore and visualize large quantities of protein PBD data using Jupyter notebooks and the Python programming language. This activity instructs participants using Jupyter notebooks, Python functions, loading data with Python, and visualize data using the matplotlib and seaborn Python plotting libraries. It also allows participants to explore large quantities of data to discover trends such amino acid abundance, dihedral angles patterns, and secondary protein structure trends. All files used in this activity, including data files, Jupyter notebooks, and completed Jupyter notebooks, are freely available at https://github.com/weisscharlesj/BiopythonRamachandran under the CC BY-NC-SA 4.0 Creative Commons license.

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