BIO 413 — Bioinformatics: Lecture Note

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BIO la-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS

BIO la-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS Course code: BIO 413 Course title: Bioinformatics Course credit load: 2 Units Series 1: History of Bioinformatics • Part 1.1: Origins of Bioinformatics o Sub Part 1.1.1: Defining bioinformatics o Sub Part 1.1.2: Early foundations and the first biological databases o Sub Part 1.1.3: The role of Margaret Dayhoff and early sequence analysis • Part 1.2: The Emergence of Modern Bioinformatics o Sub Part 1.2.1: The genomics revolution and the Human Genome Project o Sub Part 1.2.2: Key algorithms and computational breakthroughs o Sub Part 1.2.3: The rise of public biological databases • Part 1.3: Bioinformatics in the Twenty-First Century o Sub Part 1.3.1: Next-generation sequencing and big data in biology o Sub Part 1.3.2: Bioinformatics in medicine, agriculture, and industry o Sub Part 1.3.3: Bioinformatics in Nigeria and Africa • Part 1.4: Scope and Subdisciplines of Bioinformatics o Sub Part 1.4.1: Core subdisciplines of bioinformatics o Sub Part 1.4.2: Bioinformatics and related disciplines o Sub Part 1.4.3: Career pathways in bioinformatics

BIO la-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS Introduction Bioinformatics has transformed biology from a largely descriptive science into a quantitative, data-intensive discipline capable of addressing questions about the molecular basis of life at a scale and speed unimaginable just decades ago. It sits at the intersection of biology, computer science, mathematics, and statistics, providing the computational and analytical tools needed to store, retrieve, analyse, and interpret the vast quantities of molecular biological data generated by modern genomic and proteomic technologies. This Series traces the historical development of bioinformatics from its earliest roots in the compilation of protein sequence data in the 1960s through the pivotal genomics revolution and the completion of the Human Genome Project, to the era of next-generation sequencing and big data biology in the twenty-first century. It also establishes the scope and subdisciplines of bioinformatics and situates the discipline in the Nigerian and African context, providing the conceptual foundation on which the technical content of the remaining Series of this course builds. Series Learning Outcomes Upon completing this Series, you should be able to: • SLO 1.1 define bioinformatics and describe its early origins, including the contributions of Margaret Dayhoff and the first biological databases, • SLO 1.2 describe the genomics revolution, the Human Genome Project, and the key computational breakthroughs that shaped modern bioinformatics, • SLO 1.3 describe the applications of bioinformatics in the twenty-first century, including in medicine, agriculture, and the Nigerian and African context, and • SLO 1.4 identify the core subdisciplines of bioinformatics and explain its relationship with related disciplines and career pathways.

BIO la-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS 1.1 Origins of Bioinformatics 1.1.1 Defining bioinformatics Bioinformatics is the interdisciplinary science that develops and applies computational methods, mathematical models, and statistical approaches to store, retrieve, analyse, and interpret biological data, particularly molecular biological data such as nucleotide and amino acid sequences, protein structures, and gene expression profiles; the term was coined by Paulien Hogeweg and Ben Hesper in 1970 to describe the study of information processes in biotic systems, though the practical application of computing to biological sequence data predates the coinage of the term by nearly a decade. The scope of bioinformatics extends from the management of large biological databases through the development of algorithms for sequence alignment and structure prediction, to the systems-level analysis of entire genomes, transcriptomes, and proteomes; it is distinct from computational biology (which is more broadly concerned with mathematical modelling of biological systems) and from biomedical informatics (which focuses primarily on clinical and health data), though these disciplines overlap substantially and the boundaries between them are not universally agreed. Fill in the blank: The term bioinformatics was coined by Paulien Hogeweg and Ben Hesper in ________ to describe the study of information processes in biotic systems. 1.1.2 Early foundations and the first biological databases The foundations of bioinformatics were laid in the early 1960s with the first systematic efforts to collect and organise biological macromolecule sequence data; the development of protein sequencing methods (principally by Frederick Sanger, who determined the first complete protein sequence, that of bovine insulin, in 1951 using his end-group analysis and partial hydrolysis methods) generated the data that needed organising, and the simultaneous development of electronic computers created the tools with which to organise it; the combination of biological data generation and computational storage capacity created the conditions from which bioinformatics as a discipline emerged.

BIO la-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS Early biological databases were entirely paper-based before their transfer to machine-readable formats: the Atlas of Protein Sequence and Structure (initiated by Margaret Dayhoff in 1965, later known as the Protein Information Resource, PIR) was the first systematically organised collection of protein sequence data, initially compiled and distributed as a book before being transferred to computer-readable magnetic tape; this early database established many of the principles of biological database design that persist to the present, including the importance of standardised formats, comprehensive annotation, and free availability of data to the scientific community. Fill in the blank: The Atlas of Protein Sequence and Structure, initiated by Margaret Dayhoff in ________ , was the first systematically organised collection of protein sequence data. 1.1.3 The role of Margaret Dayhoff and early sequence analysis Margaret Dayhoff (1925 to 1983) is widely regarded as the founder of bioinformatics, having pioneered the creation of protein sequence databases, developed computational methods for their analysis, and established many of the conceptual frameworks that still underpin the field; her most significant scientific contributions include the development of the first amino acid substitution matrices (the PAM matrices, Percent Accepted Mutations, constructed from aligned protein sequences and quantifying the relative rates at which one amino acid replaces another over evolutionary time) which became the foundation for all subsequent work in sequence alignment and database searching. Dayhoff also developed the single-letter amino acid code (which replaced the three-letter code for computational convenience), contributed to the first computational phylogenetic analyses, and promoted the principle that biological sequence data should be collected in a central repository and made freely available to the entire scientific community; her Atlas was accompanied by early computer programs for sequence comparison, making her work the direct ancestor of modern bioinformatics tools and databases including BLAST, GenBank, UniProt, and the NCBI suite of resources.

BIO la-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS Fill in the blank: Margaret Dayhoff developed the PAM (Percent Accepted ________ ) matrices, which quantify the rates at which amino acids replace each other over evolutionary time and underpin modern sequence alignment. Figure 1.1: Origins of bioinformatics Pilot questions 1.1 1. Define bioinformatics and state who coined the term and when. 2. Distinguish between bioinformatics and computational biology. 3. Name the first systematically organised protein sequence database and state who created it. 4. Explain what PAM matrices are and why they are important. 5. State two principles of biological database design established by Margaret Dayhoff.

BIO la-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS 1.2 The Emergence of Modern Bioinformatics 1.2.1 The genomics revolution and the Human Genome Project The development of automated DNA sequencing, based on Frederick Sanger dideoxy chain-termination method (1977) and later automated using fluorescent dye-labelled terminators and capillary electrophoresis, transformed the scale at which biological sequence data could be generated; the first complete genome sequences of living organisms (the bacteriophage phiX174 in 1977, the bacterium Haemophilus influenzae in 1995, and the yeast Saccharomyces cerevisiae in 1996) demonstrated the feasibility of whole-genome sequencing and established the computational infrastructure for managing and analysing complete genomes. The Human Genome Project (HGP), initiated in 1990 as an international collaborative effort involving research centres in the United States, United Kingdom, France, Germany, Japan, and China, with the goal of determining the complete sequence of all approximately 3.2 billion base pairs of the human genome, was completed in its draft form in 2001 (announced simultaneously in Nature and Science) and declared essentially complete in 2003; the HGP was transformative not only for its scientific output but for the bioinformatics infrastructure it created, including GenBank, the European Molecular Biology Laboratory nucleotide database (EMBL-Bank), and the DNA Data Bank of Japan (DDBJ), which together form the International Nucleotide Sequence Database Collaboration (INSDC). Fill in the blank: The Human Genome Project was initiated in ________ as an international collaborative effort to determine the complete sequence of the approximately 3.2 billion base pairs of the human genome. 1.2.2 Key algorithms and computational breakthroughs Several computational breakthroughs were essential for the development of modern bioinformatics: the Needleman-Wunsch algorithm (1970), the first dynamic programming algorithm for global pairwise sequence alignment, made systematic comparison of biological sequences possible; the Smith-Waterman algorithm (1981), a local alignment variant, identified regions of similarity within longer sequences; and the development of BLAST (Basic Local

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