Lecture Notes 1.2 Computational Thinking Biology.pdf

Module 01: Computational Thinking Problem Solving Techniques (Biology) © 2021 Nanyang Technological University, Singapore. All Rights Reserved. 1 Computational Thinking Competencies (4 main) Computational: Involving the calculation of answers, amounts, results( e.g., calculations, order) Thinking: T...

Module 01: Computational Thinking Problem Solving Techniques (Biology) © 2021 Nanyang Technological University, Singapore. All Rights Reserved. 1 Computational Thinking Competencies (4 main) Computational: Involving the calculation of answers, amounts, results( e.g., calculations, order) Thinking: The activity of using your mind to consider something (e.g., reasoning, questioning) Competencies: Important skills that are needed to do a job (e.g., managerial competencies) Abstraction © 2021 Nanyang Technological University, Singapore. All Rights Reserved. Algorithms Decomposition Pattern Recognition 2 Abstraction: Biology Abstraction: Identifying and utilizing the structure of concepts / main ideas Simplifies things Identifies what is important without worrying too much about the detail Allows us to manage the complexity of the context or content The abstraction process – deciding what details we need to highlight and what details we can ignore – underlies computational thinking. - Jeannette Wing © 2021 Nanyang Technological University, Singapore. All Rights Reserved. 3 Bioinformatics Combines different fields of study, including computer sciences, molecular biology, biotechnology, statistics and engineering Large amount of data: Genomics, Proteomics Pseudocode: An informal description of the steps involved in executing a computer program, often written in something similar to plain [in designed language] © 2021 Nanyang Technological University, Singapore. All Rights Reserved. 4 Human Genomes (Abstraction) Structure of cell: Incredibly crowded Incomprehensible for humans Question: How to simplify the representation of cells? How to make it readable? Answer: By abstraction: labelling, lettering, shaping, colouring, etc. © 2021 Nanyang Technological University, Singapore. All Rights Reserved. 5 Human Genomes (Abstraction) Formulating in pseudo level can enable us to understand concepts more clearly. Abstraction simplifies complex life phenomenon to something readable and understandable. © 2021 Nanyang Technological University, Singapore. All Rights Reserved. 6 Algorithms in Biology Algorithm is about following, identifying, using, and creating an ordered set of instructions ordering things ascending order (e.g., from 1 to 5, or from A B C to X Y Z) descending order (e.g., from 5 to 1, or from Z Y X to C B A) Allows us to order the complexity of the context or content © 2021 Nanyang Technological University, Singapore. All Rights Reserved. 7 Algorithms Biology (overview) © 2021 Nanyang Technological University, Singapore. All Rights Reserved. 8 Algorithms Biology (overview) © 2021 Nanyang Technological University, Singapore. All Rights Reserved. 9 Decomposition is about: Decomposition in Biology Breaking down data, processes or problems into smaller and more manageable components to solve a problem Each subproblem can then be examined or solved individually, as they are simpler to work with Natural way to solve problems Also known as divide-and-conquer © 2021 Nanyang Technological University, Singapore. All Rights Reserved. 10 Decomposition (divide and conquer) © 2021 Nanyang Technological University, Singapore. All Rights Reserved. 11 Decomposition Solve complex problems If a complex problem is not decomposed, it is much harder to solve at once. Subproblems are usually easy to tackle Each subproblem can be solved by different parties of analysis Decomposition forces you to analyze your problem from different aspects © 2021 Nanyang Technological University, Singapore. All Rights Reserved. 12 Pattern Recognition is about observing patterns, trends and regularities in data A pattern is a discernible regularity The elements of a pattern repeat in a predictable manner In computational thinking, a pattern is the spotted similarities and common differences between problems It involves finding the similarities or patterns among small, decomposed problems, which can help us solve complex problems more efficiently © 2021 Nanyang Technological University, Singapore. All Rights Reserved. 13 Pattern Recognition in Biology © 2021 Nanyang Technological University, Singapore. All Rights Reserved. 14 Pattern Recognition Patterns make problems simpler and easy to solve Problems are easier to solve when they share patterns, we can use the same problem-solving solution wherever the pattern exists The more patterns we can find, the easier and quicker our problem solving will be © 2021 Nanyang Technological University, Singapore. All Rights Reserved. 15