Bioinformatics Overview and Importance

Bioinformatics

• Bioinformatics is the study of informatic processes in biotic systems
• Bioinformatics is considered computational molecular biology which uses computational techniques to study the structure, function, and regulation of genes and proteins
• Bioinformatics is a part of computational biology
• Computational biology is broader in scope and includes any subdiscipline that uses computer-aided analysis, modeling, and prediction.

Importance of Bioinformatics

• Bioinformatics experienced explosive growth starting in the mid-1990s due to the Human Genome Project and advances in DNA sequencing technology
• The Human Genome Project had mapped around 85% of the human genome by 2003
• The complete human genome was mapped in 2021
• Bioinformatics will be essential for scientific discoveries as more biodata is collected.

Goals of Bioinformatics

• The primary goal is to increase the understanding of biological processes and to be able to predict biological processes in health and disease
• Bioinformatics aims to:
  • Organize biodata to make it accessible and searchable
  • Develop software to analyze biodata
  • Analyze and interpret biodata in a biologically meaningful manner

Components of Bioinformatics

• Biological Data
• Biological Databases
• Analysis Tools

Biological Data

• Information derived from living organisms and their products that is processed by computers.
• Includes:
  • Nucleic Acid Sequences (DNA, RNA)
  • Protein sequences
  • Protein structures
  • Literature
• Sequencing determines the precise order of nucleotides in DNA
• Earlier methods of DNA sequencing were expensive and time-consuming
• Next-Generation Sequencing (NGS) allows for high-throughput sequencing of millions or billions of DNA molecules.

Biological Databases

• An organized collection of biological data stored and accessed electronically
• Most databases are public.

Analysis Tools

• Software programs that extract meaningful information from raw biological data.
• Major categories:
  • Homology and Similarity Tools: Identify similarities between novel sequences and database sequences with known structure and function.
  • Protein Function Analysis tools: Compare protein sequences to databases containing information on motifs, signatures, and protein domains to approximate the function of a query protein.
  • Structural Analysis tools: Compare structures with known structure databases.
  • Sequence Analysis tools: Carry out further analysis, including evolutionary analysis and identification of mutations.
  • Sequence Alignment: Arranges DNA, RNA, or protein sequences for comparison to identify regions of similarity.

Genome Annotation

• The process of identifying the locations of genes and coding regions in a genome and determining their function
• Requires automation due to the large size of most genomes
• In 1995, a team at The Institute for Genomic Research sequenced and analyzed the genome of the bacterium Haemophilus influenzae
• The GeneMark program identifies genes.

Analysis of Gene Expression

• Measures mRNA levels to determine the expression of genes
• Techniques include microarrays
• Bioinformatics develops statistical tools to separate signal from noise in microarray data.
• Microarray data studies can be used to determine genes implicated in disorders

Analysis of Regulation

• Gene regulation is the complex organization of events that lead to an increase or decrease in protein activity
• Bioinformatics explores various steps in gene regulation
• Promoter Analysis identifies and studies DNA sequences surrounding the coding region of a gene that influence transcription.

Analysis of Protein Expression

• Not all mRNA is translated into protein.
• Proteomics confirms the presence of proteins and provides a measure of their quantity.
• Techniques include protein microarrays and high throughput mass spectrometry (MS)
• Bioinformatics helps make sense of protein microarray and MS data.

Analysis of Mutations in Cancer

• Cancer alters the genomes of affected cells in unpredictable ways
• Massive sequencing efforts identify point mutations in genes.
• Bioinformatics creates automated systems and software to compare sequencing results to human genome sequences.
• Single-nucleotide polymorphisms (SNPs) are identified using new technology
• dbSNP, from NCBI, lists SNPs in humans.
• The OMIM database describes the association between polymorphisms and diseases.

Single Nucleotide Polymorphism (SNP)

• A variation at a single position in a DNA sequence in more than 1% of a population.
• If a SNP occurs within a gene, the gene has more than one allele.
• Roughly 90% of genetic variation between humans is the result of SNPs.
• Most variations don't alter cellular function, but some contribute to diseases.
• SNPs are identified and characterized by sequencing the same genomic region in several populations.

Types of SNPs

• SNPs in coding regions:
  • Synonymous substitutions: do not change the amino acid sequence.
  • Nonsynonymous substitutions: change the amino acid sequence.
    • Missense: a single base change results in a change in amino acid and protein malfunction.
    • Nonsense: a single base change results in a premature stop codon, resulting in a nonfunctional protein product.
• SNPs in non-coding regions: may affect transcription factor binding, mRNA structure, and disease susceptibility.

Prediction of Protein Structure

• Protein structure prediction is another important application of bioinformatics.
• Primary structure: amino acid sequence of the polypeptide chain
• Secondary structures: Alpha helices and Beta sheets.
• Tertiary structure: Three-dimensional structure of a single polypeptide chain.
• Quaternary structure: Aggregation of two or more polypeptide chains that operate as a single unit (multimer).

Comparative Genomics

• The study of interrelationships of genomes of different species
• Compares whole or large parts of genomes to study similarities and differences between organisms.
• Revealed high levels of similarity between closely related organisms and distantly related organisms.
• VISTA is a collection of databases and tools for comparative genomics analyses.

Computational Evolutionary Biology

• Evolution is the process of change in populations and species over generations.
• Evolutionary biology (Phylogenetics) studies evolution.
• Molecular evolution studies variations and evolution in cellular molecules.
• Bioinformatics helps trace the evolution of organisms by analyzing DNA sequence changes.

Explore the fundamentals of bioinformatics, its significance, and its goals in understanding biological processes. Learn how computational techniques are vital in molecular biology and how the Human Genome Project has accelerated developments in this field. This quiz is essential for anyone interested in the intersection of biology and technology.