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Cabaret: A Suite of Characterized Discrete Models for Benchmarking Systems Biology Tools

Ding, Handa (2020) Cabaret: A Suite of Characterized Discrete Models for Benchmarking Systems Biology Tools. Master's Thesis, University of Pittsburgh. (Unpublished)

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Abstract

Computational modeling tools have a great potential to increase our understanding of complex biological systems. With the significant increase in publicly available biomedical data, systems biology methods have advanced, resulting in numerous frameworks that are accessible for the whole community. However, with many different methods proposed to solve computational biology problems, there is a tremendous need for standards to measure capabilities of the tools. Accordingly, assessing and deciding which tools to use to address specific questions and problems is often a considerable challenge. One solution to address this challenge is to follow the practice of other fields, such as computer engineering, and create benchmarks. In biology, a suite of models that are evaluated using typical measures would allow researchers to compare the performance among different tools in an unbiased fashion. Thus, we propose CABARET, a Characterized Assembly of Benchmarks for Automation, Reproducibility and Evaluation of Tools in biology.
Our benchmark suite (CABARET) will provide a set of models and analysis methods for biological modelers to comprehensively evaluate their tools. In this thesis, we selected seven discrete cell signaling and gene regulation network models of immune system and cancer cells. These models are then simulated both deterministically and stochastically to explore their steady states and transient responses. Using the same simulation approach and analysis methods on all models allows for standardized measures and reporting of the features of the models and results in a well characterized set of benchmark models. For this characterization, feedback loop, fan-in and fan-out cone analyses, as well as the analysis of paths between inputs and outputs, and additional features of scenarios specific for modeled systems have been documented. We believe these models can serve as standardized, calibrated, benchmarks to evaluate future tools developed by the biology community.


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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Ding, Handad.handa@pitt.eduhad52
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairMiskov-Zivanov, Natasanmzivanov@pitt.edunmzivanov
Committee MemberYang, Junjuy9@pitt.edujuy9
Committee MemberDickerson, Samueldickerson@pitt.edudickerson
Committee MemberTelmer, Cherylctelmer@cmu.edu
Date: 28 January 2020
Date Type: Publication
Defense Date: 14 November 2019
Approval Date: 28 January 2020
Submission Date: 21 November 2019
Access Restriction: 2 year -- Restrict access to University of Pittsburgh for a period of 2 years.
Number of Pages: 66
Institution: University of Pittsburgh
Schools and Programs: Swanson School of Engineering > Electrical and Computer Engineering
Degree: MS - Master of Science
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: Biological Systems, Boolean Model, Cancer Systems, Benchmarking Characteristics, Logic, Feedback Loops, Python, Automation, Tools
Date Deposited: 28 Jan 2020 17:32
Last Modified: 28 Jan 2020 17:32
URI: http://d-scholarship.pitt.edu/id/eprint/37873

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