Homework
Weekly homework submissions:
Week 1 HW: Principles and Practices
First, describe a biological engineering application or tool you want to develop and why. Engineered bacteriophage as a delivery vector or indicator. Factors such as selective host range, ability to integrate, infection of drug-resistant bacteria, reproducibility, and more would make them a versatile tool. Next, describe one or more governance/policy goals related to ensuring that this application or tool contributes to an “ethical” future, like ensuring non-malfeasance (preventing harm). Break big goals down into two or more specific sub-goals. (slightly edited from example framework)
Week 2 HW: DNA Read, Write, and Edit
Part 1: Benchling & In-silico Gel Art My node (W&M) is using one of our phages’(Kampy) DNA for the Gel Art DNA - https://phagesdb.org/phages/Kampy/ Our lab’s restriction enzymes: AfIII Age1 AluI ApaI BamHI-HF BbsI BsaI-HF BglI BstXI DpnI Eco0109I Eco47III EcoICRI EcoRI-HF EcoRV HindIII I-SceI KpnI NotI-HF PspAI PstI-HF SpaI-HF XbaI XhoI Part 2: Gel Art - Restriction Digests and Gel Electrophoresis Our design
Python Script for Opentrons Artwork Designs Using the GUI at opentrons-art.rcdonovan.com Using custom design tools (trying out stippling, different dot sizes) Python Files What the different dot design looks like after programming so far (still need to scale a bit)
Week 4 HW: Protein Design Part I
Part A. Conceptual Questions How many molecules of amino acids do you take with a piece of 500 grams of meat? (on average an amino acid is ~100 Daltons) Meat is about 25% protein so 500 grams of meat is about 125 grams of protein. 100 Daltons is equivalent to 100 grams/mol so it is about 1.25 moles amino acids. Multiplying this by avogadro’s number, 6.022x1023, we get about 7.5275x1024 molecules of amino acids for a 500 gram piece of meat.
Week 7 HW: Genetic Circuts Part II: Neuromorphic Circuts
Assignment Part 1: Intracellular Artificial Neural Networks (IANNs) What advantages do IANNs have over traditional genetic circuits, whose input/output behaviors are Boolean functions? IANNs allow for the detection of more gradient cellular signals and multiple signals being taken into account at once, which results in more nuanced outputs (not based on a single on/off like in traditional circuits).