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Dive into the intricate world of genetics and scientific models with a focus on various outcomes and underlying assumptions. Discover how models can be refuted and the complexities of linear, nonlinear, and regulated relationships in genetic studies.
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Welcome to Genetics WC Aug. 28, 2003 Class Web Site
Some model forms • Descriptive “stories” – many kinds of outcomes not based on observable “causes” • Branched – multiple results • Cascades – branched and re-branched like avalanche, undeterminable reasons • Multiple meanings based on context • Future affects present, present affects past
Scientific Models • Based on observation at some level • Can be refuted (some observation can be in contradiction to model’s prediction) • Acknowledges that there are limits to what we practically be observed • Identifies the underlying assumptions that are necessary to build a model without knowing everything that is relevant.
Complexity of Scientific Models • Switch (A then B, not A then not B) • Linear (A changes proportionally with B) • Regulated (A then B as C determines) =lacoperon • Nonlinear (A changes non-proportionally with B – many kinds of complexity) =growth, development • Time lags with above relationships =sexual maturity, trans-generational, seasonal, etc. • Combinations of above relationships (complex) =love,culture, snowflakes, 3 billiard ball collision, etc.