Ranajit Chakrabortya,b, C.R. Raoc, Pranab K. Send

a Center for Computational Genomics, Institute of Applied Genetics, University of North Texas Health Science Center, 3500 Camp Bowie Blvd., Fort Worth, Texas 76107, USA

b Department of Forensic and Investigative Genetics, University of North Texas Health Science Center, 3500 Camp Bowie Blvd., Fort Worth, Texas 76107, USA

c C.R. Rao AIMSCS, University of Hyderabad Campus, Hyderabad, India

d Departments of Biostatistics and Statistics and Operational Research, University of North Carolina, Chapel Hill, NC 27599-7420, USA

E-mail address: ranajit.chakraborty@unthsc.edu

E-mail address: crr1@psu.edu

E-mail address: pksen@bios.unc.edu

Abstract

With a working definition of bioinformatics provided, this chapter briefly outlines the premises with which integration of information from several disciplines are used in this newly introduced discipline. While not an entirely new subject, research areas of bioinformatics have wide diversity and they have important implications not only in basic science, particularly in molecular biology, systems biology, and genomics, but also in translational research with applications in medical, public health, and health policy practices. We note that bioinformatics and computational biology are not synonymous, but they adhere to a common broader interdisciplinary field. With illustrations of different research areas within this subject, some of which are addressed in the chapters of this volume, this introduction ends with a listing of some of the open areas of research in bioinformatics.

Keywords

• bioinformatics • computational biology • sequence analysis • genome annotation • computational evolutionary genomics • analysis of regulation • protein expression analysis • protein structure prediction • comparative genomics • databases • DNA forensics • microbial forensics

1 Introduction

The general lexicographic meaning of the word “Bioinformatics” (= Bio + Informatics) relates to the discipline dealing with information (informatics) with regard to biological data (bio). According to Wikipedia (http://en.wikipedia.org/wiki/Bioinformatics), arguably, this terminology was first coined in 1978 by a Dutch theoretical biologist and complex systems researcher, Paulien Hogeweg, when she was working together with Ben Hesper to study informatic processes in biotic systems (Hogeweg, 1978; Hogeweg and Hesper, 1978). During the 1980s, and up until the sequencing of the human genome which was completed in 2001 (Lander et al., 2001; Venter et al., 2001), the primary activities in this subject have been in the area of genomics involving large-scale DNA sequencing. Actually, even to this date, the sequencing of the entire human genome is heralded as the most prominent achievement of bioinformatics.

In July 17, 2000, the Biomedical Information Science and Technology Initiative Consortium (BISTIC) of the US National Institutes of Health (NIH), provided a working definition of bioinformatics as “research, development, or application of computational tools and approaches for expanding the use of biological, medical, behavioral or health data, including those to acquire, store, organize, archive, analyze, or visualize such data” (http://www.bisti.nih.gov/). BISTIC also drew a distinction between bioinformatics and computational biology by defining the latter as “the development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological, behavioral, and social systems” (http://www.bisti.nih.gov/). Imbedded in these definitions, the distinctions are obvious; namely, studies under bioinformatics would emphasize applications of principles of information sciences and related technologies that increase the power of comprehension and utility of diverse and complex forms of life sciences’ data, while mathematical and computational tools are intended to be the foci of attention in computational biology to address analytical and experimental issues of biological research in computational biology.

With the above working definition of bioinformatics, this chapter addresses three issues. First, we argue that while this is not an entirely new subject, under the umbrella of this terminology a revolutionary transformation has occurred through which biology, computer science, and information technology have merged to form a single integrated discipline that enhances the efficient collection, storage, retrieval, and synthetic interpretation of large-scale data and the visualization of summary results of such data analyses. Next, we provide a brief overview of bioinformatic activities as they relate to human health and heredity from the time of the establishment of relevant resources at the National Center for Biotechnology Information (NCBI) in the US and more generally at the global level. Lastly, we briefly outline some of the active areas of research in which more refined bioinformatic tools are needed. It is our belief that this discussion will illustrate the diversity of this field of research and practice and should help the readers to better understand the importance of the topics in the remaining chapters of this volume.

2 Sciences dealing with biological information and rationale of their integration

The premise of bioinformatics is integration of diverse sets of data and to synthesize knowledge from the interpretation of such data (with the aim of making the whole better than the sum of individuals—a common road map of today’s research). Thus, it may be easier to fully understand first the sources of biological information and what is needed for their integration. We first note that biological information had traditionally been obtained through the classical disciplines such as: botany (dealing with the biology of plants), zoology (biology of animals), physiology (biology and function of body organs), neurology (structure, biology, and function of neural systems), demography (study of composition and variation of populations over time and space), taxonomy (classification of biological objects), evolution (study of morphological and biological changes over time), and genetics (study of properties of inheritance of traits). Each of these disciplines contributed fundamental and important information that revolutionized our understanding of the origin, distribution (temporal as well as spatial), and evolution of organisms, traits, as well as their functions and/or deformities. Knowledge gained from these individual disciplines helped not only the basic sciences, but also helped medical, public health, and even economic policy decision experts. Thus, even though general organismal level knowledge had been the source of bioinformatic observations, their relevance to human health and heredity is often direct and immensely important.

The integration of knowledge gains is basically governed by some common themes of biological investigations. Table 1 illustrates some of these common themes, together with their respective interdisciplinary features that define many of the currently practiced bioinformatic activities.

Table 1 Common themes of biological investigations with their respective interdisciplinary features

Clearly this simplified view of common themes of biological investigations illustrates that for effective interpretation of biological data in a broader context knowledge and tools are required from disciplines beyond biology that includes (and is not exhaustive of) mathematics, computer science (both hardware and software), information theory and its practice, statistical principles and computations, quality control (QC) and quality assurance (QA), and multi-task administration (to attain efficiency of time and cost economy). Thus, bioinformatics, as an integrative science, offers: