Towards an intelligent system for biosynthesis: fragment annotation of the building plasmid

Wang, Mu-Chun

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https://hdl.handle.net/2142/124448 Copy

Description

Title

Towards an intelligent system for biosynthesis: fragment annotation of the building plasmid

Author(s)

Wang, Mu-Chun

Issue Date

2024-05-02

Director of Research (if dissertation) or Advisor (if thesis)

Zhai, Chengxiang

Department of Study

Computer Science

Discipline

Computer Science

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• Plasmid
• Fragment Annotation

Abstract

In this project, we study a new task in computational biology, which is Fragment An- notation of the Building Plasmid. Plasmid, a small circulated DNA, is used extensively in basic and applied biology. Plasmids play a significant role in numerous computational biology experiments, emphasizing the necessity to construct them. During the making process of the plasmid, instead of synthesizing the whole plasmid, we can attempt to use the assembly method to create them. However, to apply the assembly method, we have to reuse the existing fragment to lower the cost. To this end, we formulate a new task, Fragment Annotation, which is to find the reuse 100% match fragment of the given plasmid to lower the cost when assembly the plasmid. To achieve that, We designed a greedy-based method in three different kinds of versions, which are vanilla, iteratively, and one-shot iteratively. We further examine the performance of the plasmid dataset from the PlasmidMaker paper. We evaluate the method through 2 different kinds of metrics, accuracy and cost reduction. In the cost analysis, we find a 70% drop in the cost when applying the one-shot iteratively method, which shows the effectiveness of our method. The new algorithm has been incorporated into a state-of-the-art system, called PlasmidMaker, enabling the system to reduce its cost in supporting many biosynthesis tasks.

Graduation Semester

2024-05

Type of Resource

Thesis

Copyright and License Information

Copyright 2024 Mu-Chun Wang

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