Librarians and Bioinformatics Communities Working Together to Advance Research and Instruction

Librarians and Bioinformatics Communities Working Together to Advance Research and Instruction

Marci D. Brandenburg, Rolando Garcia-Milian
DOI: 10.4018/978-1-6684-2515-2.ch013
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Given the importance of bioinformatics in the health sciences and the increasing role information professionals are playing in informatics and data management, it is logical to develop collaborations between libraries and bioinformatics communities. Given these trends, academic libraries are providing new data services in support of research and teaching. Librarians at University of Michigan and Yale University have found different ways to engage with their respective bioinformatics communities and build successful partnerships around instruction, data analysis, software licensing, project management, seminar programming, and tool documentation. This chapter discusses the librarians' involvement, the advantages to the library and the bioinformatics communities, and the challenges faced.
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Academic libraries are always looking for new opportunities to enhance their services and role on campus. This often means applying information-related skills to new areas, topics, and services. This is evidenced by increasing library involvement in systematic reviews, visualization, and data-related activities. A recent trend is that from humanities to STEM, disciplines are becoming more data intensive. Therefore, to maintain their relevance on campus, academic libraries are providing new data services in support of research and teaching. These include data management, digital humanities, bioinformatics support, and GIS, among others. The pervasiveness of data in biomedicine is even more pronounced as high-throughput technologies generate huge amounts of data (e.g., genomics, proteomics, metabolomics) that is essential for understanding, diagnosing, prognosis, and treatment of diseases. Consequently, the production and organization of data and information in the form of journal articles, databases, and knowledge bases has also increased exponentially not only in volume but also in diversity. To understand the relevance of the data generated by these methods, the researcher needs to effectively aggregate diverse types of data to identify functions, phenotypes, expression, evolutionary conservation, disease association, protein structure, etc. (Hutchins, 2014). This is only possible by mining and integrating the enormous amount of biomedical data, information and knowledge contained in the text of the scientific literature, and datasets from molecular databases. In response to this, the field of bioinformatics has been developing at an accelerated pace and is playing a key role in biomedical research.

Bioinformatics is a highly interdisciplinary field that combines the use of computer science, statistics, and information technology for the management of biological data including, but not limited to, organization, mining, analysis (Luscombe et al., 2001), modeling (Hofmann-Apitius et al., 2015), and visualization (Staiano et al., 2005) of these data. The application of bioinformatics in medicine is not only making possible the understanding of mechanisms of disease but also the ability to tailor treatment and prognosis at the individual level in what is called Precision or Genomic Medicine. Medical libraries have been providing bioinformatics services in support of data-intensive biomedical research and teaching for many years. The Houston Academy of Medicine-Texas Medical Center Library created a biotechnology liaison librarian position to serve the information needs of the biotechnology clients, provide education and training, and to explore the use of databases to provide access to biotechnology results (Pratt, 1990). Also, in the 1990s, the Library of the University of California, San Francisco taught a class that introduced faculty and students to the use of the Internet for accessing human genome databases (Owen, 1995).

Key Terms in this Chapter

Core Facility: A for-fee unit that provides shared services, equipment, and expertise.

High-Throughput Technology: Refers to technologies that allow the simultaneous extraction, processing, and analysis of thousands of genes, proteins, metabolites, etc.

Omics: Refers to high-throughput technology or assays that measure all the same molecules simultaneously from a biological sample providing a holistic view of the biological system. For example, genomics profile DNA, transcriptomics measure transcripts, proteomics and metabolomics quantify proteins and metabolites, respectively.

Bioinformatics: A discipline concerned with the acquisition, storage, analysis, and dissemination of biological data. It is also represented as the interaction between several disciplines such as statistics, computer science, information technology, and biology.

Network Visualization: A type of visualization that shows relationships between things. A standard network may include circles (called nodes) that represent the objects and lines connecting the circles (called edges), which represent a relationship between them.

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