Title

Object-Oriented Implementation of a Novel Mathematical Framework to Determine the Effects of Developmental Interactions on Evolutionary Responses

Presenter Information

Elizabeth Brooks

Document Type

Oral Presentation

Location

SURC 137B

Start Date

21-5-2015

End Date

21-5-2015

Keywords

Object-Oriented Programming, Quantitative Genetics, Evolutionary Developmental Biology

Abstract

Quantitative genetics is the study of complex biological traits, or traits controlled by more than one gene. Traditional quantitative genetic models use the (co)variances of traits to predict evolution in response to selection. However, traits often result from nonlinear interactions between developmental factors. Because of this, traditional models may not accurately predict evolutionary dynamics. With an updated mathematical framework, we have developed a program that will determine the extent to which the developmental architecture of traits affects the evolutionary response of a given species. To date, we have developed an object-oriented program in Java as well as C++ that is highly adaptable, easily permitting future extensions to the code base. The program’s infrastructure allows for increasingly complex levels of developmental interaction through the incorporation of a class hierarchy that refines and increases the flexibility of the code. This programming structure will readily interface with a web-based tool that accepts user supplied functions for particular biological systems that can then be seamlessly integrated into the source code. The completed program will allow users to test hypotheses about how the developmental interactions among multiple traits affect their (co)variances and subsequent evolutionary trajectories.

Faculty Mentor(s)

Filip Jagodzinski, Alison Scoville

Department/Program

Computer Science

Additional Mentoring Department

Computer Science

Additional Mentoring Department

Biology

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May 21st, 11:40 AM May 21st, 12:00 PM

Object-Oriented Implementation of a Novel Mathematical Framework to Determine the Effects of Developmental Interactions on Evolutionary Responses

SURC 137B

Quantitative genetics is the study of complex biological traits, or traits controlled by more than one gene. Traditional quantitative genetic models use the (co)variances of traits to predict evolution in response to selection. However, traits often result from nonlinear interactions between developmental factors. Because of this, traditional models may not accurately predict evolutionary dynamics. With an updated mathematical framework, we have developed a program that will determine the extent to which the developmental architecture of traits affects the evolutionary response of a given species. To date, we have developed an object-oriented program in Java as well as C++ that is highly adaptable, easily permitting future extensions to the code base. The program’s infrastructure allows for increasingly complex levels of developmental interaction through the incorporation of a class hierarchy that refines and increases the flexibility of the code. This programming structure will readily interface with a web-based tool that accepts user supplied functions for particular biological systems that can then be seamlessly integrated into the source code. The completed program will allow users to test hypotheses about how the developmental interactions among multiple traits affect their (co)variances and subsequent evolutionary trajectories.