IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Mining BioLiterature: Toward Automatic Annotation of Genes and Proteins

Mining BioLiterature: Toward Automatic Annotation of Genes and Proteins
View Sample PDF
Author(s): Francisco M. Couto (Universidade de Lisboa, Portugal)
Copyright: 2009
Pages: 11
Source title: Medical Informatics: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Joseph Tan (McMaster University, Canada)
DOI: 10.4018/978-1-60566-050-9.ch158

Purchase

View Mining BioLiterature: Toward Automatic Annotation of Genes and Proteins on the publisher's website for pricing and purchasing information.

Abstract

This chapter introduces the use of Text Mining in scientific literature for biological research, with a special focus on automatic gene and protein annotation. This field became recently a major topic in Bioinformatics, motivated by the opportunity brought by tapping the BioLiterature with automatic text processing software. The chapter describes the main approaches adopted and analyzes systems that have been developed for automatically annotating genes or proteins. To illustrate how text-mining tools fit in biological databases curation processes, the chapter presents a tool that assists protein annotation. Besides the promising advances of Text Mining of BioLiterature, many problems need to be addressed. This chapter presents the main open problems in using text-mining tools for automatic annotation of genes and proteins, and discusses how a more efficient integration of existing domain knowledge can improve the performance of these tools.

Related Content

Saloua Mabsor-Zgandaoui, Khawla Rachmoune, Ilham Aftais, Fatima Ezzahra Elamrani, Imade Amradi, Adil El Housseini, Youssef Ait Hamdan, Youness Zgandaoui, Abdelghani Iddar, Mohammed El Mzibri, Adnane Moutaouakkil, Aboubaker El Hessni, Abdelhalim Mesfioui. © 2026. 30 pages.
Yusuf Olatunji Waidi. © 2026. 20 pages.
Ajinkya Nene, Sorour Sadeghzade, Wenjie Yang, Prakash Somani. © 2026. 12 pages.
Seyyed Mohammad Amin Mousavi-Sagharchi, Mahdieh Ranjbar-Jamalabadi, Sama Yavari, Elina Afrazeh, Naresh Poondla, Mohsen Sheykhhasan. © 2026. 32 pages.
Wenqiang Xie, Yuan Su, Ruiqi Zhang, Sijia Li, Jia Ni, Longquan Shao. © 2026. 18 pages.
Zhengao Wang, Huiyu Zhao, Yao Han, Wuyi Zhou, Chengyun Ning. © 2026. 30 pages.
Navya Aggarwal, Shinjini Sen, Tanmay J. Urs, Shreya Gupta, Banashree Bondhopadhyay. © 2026. 36 pages.
Body Bottom