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Three web tools to aid genetics instruction developed by students in a unique undergraduate bioinformatics projects course
Author(s) -
Rutherford Robert,
Garcia Nic,
Charczenko Richard,
Levy Samuel,
Bjelajac Jeremy
Publication year - 2018
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.2018.32.1_supplement.663.42
Subject(s) - computer science , software , population , outreach , set (abstract data type) , class (philosophy) , artificial intelligence , programming language , demography , sociology , political science , law
At Seattle University, some of our undergraduate Cellular and Molecular biology (CMOL) majors enroll in 10 week bioinformatics course. In addition to learning to use a range of bioinformatics tools written by the research community, students learn to use Python programming language. Some of these students take a second course, where they work in teams to develop novel biological software to support the teaching and learning of threshold genetics concepts. Here we describe this method of teaching bioinformatics and programming to CMOL majors and also features three student projects that have extended beyond this class to become independent and ongoing research endeavors. These web ready, graphical software projects include: 1) EVO.py, a new pedagogical tool that simulates genetic drift and natural selection in snowshoe hare populations. Users control a multitude of variables, including climate, allele frequency, and population size, and run the simulation, observing how procedurally generated snowshoe hare populations evolve over time in response to those inputs. 2) Lactose Operon (LacOp), a new program that simulates the regulation and biochemistry of the E.coli Lac operon. LacOp allows students configure this pathway with a wide range of mutations and/or substrate concentrations and then observe the full set of molecular outputs through time in a graphical format. 3) An enhanced FaSE (FauxSequenceEvolver) tool, which subjects user supplied molecular sequence(s) to faux evolution, automating the generation of novel but biologically credible derivative sequences. These derivative sequences have been used, for example, as ‘unknown sequences' suitable to develop and test a classroom of students' abilities to use bioinformatics tools for characterization and annotation. Student software development on this project included integrating FaSE with BioPython to allow NCBI interactivity, to capture and import known characterization data, and to automate scanning for domains. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .