ComputationalThinkingCourseComputingDNAdegeneracy
- 1. Computational Thinking Course:Computing DNA degeneracy Project plan at a glance... Core subject(s) Science Subject area(s) A level Biology, DNA structure and Genomics. Suggested age 16 to 18 years old Prior knowledge Understanding of genetic transcription and translation. N.b No prior understanding of Python programming required. Time Curriculum: 90 minutes Extracurricular: 4 x 90 minutes. Standards Core Subject: GCE Biology (UK) Computer Science: UK Project Overview The project will be titled: "Degenerate DNA code: The search for genetic resilience." The purpose of the project is for students to discover which nucleotide sequences are the most resilient to the effects of mutations. The students will apply the computational thinking skills (CTS) of decomposition, pattern recognition, abstraction and algorithm design in order to further define the problem, create Python based solutions and formulate a conclusion. Learning outcomes Students will be expected to be able to: ● Communicate the ideas of the triplet code, degeneracy and genetic mutations. ○ State the central dogma of biology. ○ Describe how the triplet code has 64 possibilities, but encodes for only 20 amino acids. ○ Explain the significance of different mutations. ● Create, edit and test Python code that can solve the project question. ○ Create functions and variables. ○ Use loops and conditional logic. ○ Create and search data structures such as arrays.
- 2. Project lesson plan Lesson content Potential structure/ suggested activities 1: Decomposition Intro to DNA mutations. Introduction to the idea of DNA degeneracy and the project aims/objectives by the teacher (presentation). Students (self) organise into groups and each student researches a particular mutation. CTS decomposition. Students are tasked with breaking down the problem into subproblems. CTS decomposition. Potential project decomposition given and groups create an analysis and suggest improvements. 2: Pattern recognition DNA degeneracy Basic combinatorics worksheet/’practical’ activity using different coloured counters and students, linking to the idea of codon degeneracy. Students are given a variety of nucleotide sequences and using dice and or a spreadsheet application create some nucleotide sequences that ‘appear’ resilient to random mutations. Students are guided to identify potential patterns in the different nucleotide sequences. CTS Pattern recognition. Discussion surrounding which nucleotide sequences are the most resistant to random mutations. 3: Abstraction DNA degeneracy and interspecies genetic conservation. Students asked to input their most resistant nucleotide sequences into a random mutation Python program. Students mind map generalisations. Students use a template Python program that manipulates text strings in order to test generalisations. Peer assess solutions and suggest improvements. 4: Algorithmic design Genomic databases and BLAST Students are given different snippets of pseudo code and are asked to arrange them into a logical sequence (card sort type activity). Students create pseudo code for their Python programs. Students start writing their program. CTS algorithm design. Students present preliminary findings and teacher comments on code design (via an online feedback system). 5: Algorithmic design Self directed problem solving and coding. Poster presentation of findings.
- 3. Assessment Students will complete and be questioned about a scientific poster presentation. This presentation will be assessed against the learning outcomes and verbal feedback will be provided. Students will also complete a project feedback google form (https://docs.google.com/forms/d/1wukHu1ZmZ7nLD9v12hYj2yEUnSOfhmTbdbMIpjHw_Aw/ viewform?usp=send_form). Additional Resource Links ● Python (https://www.python.org/) ● Python programming introductory course, Udacity (https://www.udacity.com/course/programmingfoundationswithpythonud036) ● Codon degeneracy, Wikipedia (https://en.wikipedia.org/wiki/Codon_degeneracy) ● Evolution as a sequence of mistakes (http://rosalind.info/problems/hamm/) ● Local sequence alignment, BLAST (http://blast.ncbi.nlm.nih.gov/Blast.cgi)