The world has widely changed in terms of communicating, acquiring, and storing information. Hundreds of millions of people are involved in information retrieval tasks on a daily basis, in particular while using a Web search engine or searching their e-mail, making such field the dominant form of information access, overtaking traditional database-style searching. How to handle this huge amount of information has now become a challenging issue. In this paper, after recalling the main topics concerning information retrieval, we present a survey on the main works on literature retrieval and mining in bioinformatics. While claiming that information retrieval approaches are useful in bioinformatics tasks, we discuss some challenges aimed at showing the effectiveness of these approaches applied therein. 1. Introduction Nowadays, most of the scientific publications are electronically available on the Web, making the problem of retrieving and mining documents and data a challenging task. To this end, automated document management systems have gained a main role in the field of intelligent information access [1]. Thus, research and development in the area of bioinformatics literature retrieval and mining is aimed at providing intelligent and personalized services to biologists and bioinformaticians while searching for useful information in scientific publications. In particular, the main goal of bioinformatics text analysis is to provide access to unstructured knowledge by improving searches, providing automatically generated summaries, linking publications with structured resources, visualizing contents for better understanding, and guiding researchers to formulate novel hypotheses and to discover knowledge. In the literature, several methods, systems, and tools to retrieve and mine bioinformatics publications have been proposed and adopted, some of them being currently available on the Web. In this paper, we provide a survey of existing end-user-oriented literature retrieval and/or mining solutions for bioinformatics, together with a short discussion on open challenges. The rest of the paper is organized as follows: Section 2 illustrates the main topics addressed in this paper, that is, information retrieval, text mining, and literature retrieval and mining. In Section 3, the state of the art on literature retrieval and mining in bioinformatics is presented. Section 4 discusses some relevant open problems and challenges. Section 5 ends the paper. 2. Background Supporting users in handling the huge and widespread amount of Web information is becoming a primary
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