Elicitation of Protein-Protein Interactions from Biomedical Literature Using Association Rule Discovery

PDF Version Also Available for Download.

Description

Extracting information from a stack of data is a tedious task and the scenario is no different in proteomics. Volumes of research papers are published about study of various proteins in several species, their interactions with other proteins and identification of protein(s) as possible biomarker in causing diseases. It is a challenging task for biologists to keep track of these developments manually by reading through the literatures. Several tools have been developed by computer linguists to assist identification, extraction and hypotheses generation of proteins and protein-protein interactions from biomedical publications and protein databases. However, they are confronted with the challenges ... continued below

Physical Description

vii, 82 p. : ill.

Creation Information

Samuel, Jarvie John August 2010.

Context

This thesis is part of the collection entitled: UNT Theses and Dissertations and was provided by UNT Libraries to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 328 times , with 6 in the last month . More information about this thesis can be viewed below.

Who

People and organizations associated with either the creation of this thesis or its content.

Chair

Committee Members

Publisher

Rights Holder

For guidance see Citations, Rights, Re-Use.

  • Samuel, Jarvie John

Provided By

UNT Libraries

With locations on the Denton campus of the University of North Texas and one in Dallas, UNT Libraries serves the school and the community by providing access to physical and online collections; The Portal to Texas History and UNT Digital Libraries; academic research, and much, much more.

Contact Us

What

Descriptive information to help identify this thesis. Follow the links below to find similar items on the Digital Library.

Description

Extracting information from a stack of data is a tedious task and the scenario is no different in proteomics. Volumes of research papers are published about study of various proteins in several species, their interactions with other proteins and identification of protein(s) as possible biomarker in causing diseases. It is a challenging task for biologists to keep track of these developments manually by reading through the literatures. Several tools have been developed by computer linguists to assist identification, extraction and hypotheses generation of proteins and protein-protein interactions from biomedical publications and protein databases. However, they are confronted with the challenges of term variation, term ambiguity, access only to abstracts and inconsistencies in time-consuming manual curation of protein and protein-protein interaction repositories. This work attempts to attenuate the challenges by extracting protein-protein interactions in humans and elicit possible interactions using associative rule mining on full text, abstracts and captions from figures available from publicly available biomedical literature databases. Two such databases are used in our study: Directory of Open Access Journals (DOAJ) and PubMed Central (PMC). A corpus is built using articles based on search terms. A dataset of more than 38,000 protein-protein interactions from the Human Protein Reference Database (HPRD) is cross-referenced to validate discovered interactive pairs. A set of an optimal size of possible binary protein-protein interactions is generated to be made available for clinician or biological validation. A significant change in the number of new associations was found by altering the thresholds for support and confidence metrics. This study narrows down the limitations for biologists in keeping pace with discovery of protein-protein interactions via manually reading the literature and their needs to validate each and every possible interaction.

Physical Description

vii, 82 p. : ill.

Language

Identifier

Unique identifying numbers for this thesis in the Digital Library or other systems.

Collections

This thesis is part of the following collection of related materials.

UNT Theses and Dissertations

Theses and dissertations represent a wealth of scholarly and artistic content created by masters and doctoral students in the degree-seeking process. Some ETDs in this collection are restricted to use by the UNT community.

What responsibilities do I have when using this thesis?

When

Dates and time periods associated with this thesis.

Creation Date

  • August 2010

Added to The UNT Digital Library

  • Jan. 6, 2011, 6:55 a.m.

Description Last Updated

  • Jan. 21, 2014, 2 p.m.

Usage Statistics

When was this thesis last used?

Yesterday: 0
Past 30 days: 6
Total Uses: 328

Interact With This Thesis

Here are some suggestions for what to do next.

Start Reading

PDF Version Also Available for Download.

Citations, Rights, Re-Use

Samuel, Jarvie John. Elicitation of Protein-Protein Interactions from Biomedical Literature Using Association Rule Discovery, thesis, August 2010; Denton, Texas. (digital.library.unt.edu/ark:/67531/metadc30508/: accessed December 13, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; .