Investigating Evolutionary Relationships through Cluster Analysis: A Teaching Science with Big Data Workshop Session

Autor/in	Novak, Walter R. P.
Titel	Investigating Evolutionary Relationships through Cluster Analysis: A Teaching Science with Big Data Workshop Session
Quelle	In: Biochemistry and Molecular Biology Education, 50 (2022) 5, S.440-445 (6 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Novak, Walter R. P.)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1470-8175
DOI	10.1002/bmb.21645
Schlagwörter	Biochemistry; Data; Workshops; Undergraduate Students; Teaching Methods; Programming Languages; Science Instruction + Suchen Sie Ihr Suchwort? Biochemie; Daten; Lernwerkstatt; Schulung; Teaching method; Lehrmethode; Unterrichtsmethode; Teaching of science; Science education; Natural sciences Lessons; Naturwissenschaftlicher Unterricht
Abstract	Biochemistry is a data-heavy discipline, yet teaching students to work with large datasets is absent from many undergraduate Biochemistry programs. Ensuring that future generations of students are confident in tackling problems using big data first requires that educators become comfortable teaching big data skills. The activity described herein introduces educators to working with big data and a framework for generating sequence similarity networks using JupyterLab and Python. This article reports a session from the virtual international 2021 IUBMB/ASBMB workshop, "Teaching Science with Big Data." (As Provided).
Anmerkungen	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
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01