Information Retrieval in Bioinformatics: State of the Art and Challenges

Information Retrieval (IR) is a process for information processing with the aim of concerned among dealing with documents containing free text in order to acquire them rapidly using keywords process in a user’s search string. Designing effective tools to collect and utilize electronic resources has become a key challenge as the large amount of internet resource grows. The semantic-web era based on domain ontologies has provided some benefits. Life sciences, health care, and biomedicine are gradually becoming data intensives fields of study. We countenance not only increased amount and variety of well difficult, multi-dimensional, and frequently weakly structured and noisy data in bioinformatics and computational biology, although a growing requirement for integrative investigation and modeling. Following a review of the major topics in information retrieval, we give an overview of the major works in literature- study retrieval and mining in bioinformatics. While stating that IR methodologies are valuable in bioinformatics jobs, we outline certain problems that must be overcome in order to demonstrate their efficacy. Information retrieval using biomedical data mining for text, images, and visual content is addressed in Biomedical Data Mining for Information Retrieval. There are many possibilities and challenges in biomedical and health informatics, which lies at the intersection of information science, computer science, and health care. Biomedical and health data is abundant, easily accessible, and can be analyzed in a wide range of ways. By analyzing biomedical and healthcare data, such as patient records, electronic health records (EHRs), and lifestyle data, healthcare informatics will be able to provide high-quality, efficient health care, better treatment, and better quality of life.