Bioinformatics is an interdisciplinary field of science that develops methods and software tools for understanding biological data, especially when the data sets are large and complex. Bioinformatics uses biology, chemistry, physics, computer science, computer programming, information engineering, mathematics and statistics to analyze and interpret biological data. The subsequent process of analyzing and interpreting data is referred to as computational biology.
Genomics is an interdisciplinary field of biology focusing on the structure, function, evolution, mapping, and editing of genomes. A genome is an organism's complete set of DNA, including all of its genes as well as its hierarchical, three-dimensional structural configuration. In contrast to genetics, which refers to the study of individual genes and their roles in inheritance, genomics aims at the collective characterization and quantification of all of an organism's genes, their interrelations and influence on the organism. Genes may direct the production of proteins with the assistance of enzymes and messenger molecules. In turn, proteins make up body structures such as organs and tissues as well as control chemical reactions and carry signals between cells. Genomics also involves the sequencing and analysis of genomes through uses of high throughput DNA sequencing and bioinformatics to assemble and analyze the function and structure of entire genomes. Advances in genomics have triggered a revolution in discovery-based research and systems biology to facilitate understanding of even the most complex biological systems such as the brain.
In computational biology, gene prediction or gene finding refers to the process of identifying the regions of genomic DNA that encode genes. This includes protein-coding genes as well as RNA genes, but may also include prediction of other functional elements such as regulatory regions. Gene finding is one of the first and most important steps in understanding the genome of a species once it has been sequenced.
Metagenomics is the study of genetic material recovered directly from environmental or clinical samples by a method called sequencing. The broad field may also be referred to as environmental genomics, ecogenomics, community genomics or microbiomics.
The Integrated Microbial Genomes system is a genome browsing and annotation platform developed by the U.S. Department of Energy (DOE)-Joint Genome Institute. IMG contains all the draft and complete microbial genomes sequenced by the DOE-JGI integrated with other publicly available genomes. IMG provides users a set of tools for comparative analysis of microbial genomes along three dimensions: genes, genomes and functions. Users can select and transfer them in the comparative analysis carts based upon a variety of criteria. IMG also includes a genome annotation pipeline that integrates information from several tools, including KEGG, Pfam, InterPro, and the Gene Ontology, among others. Users can also type or upload their own gene annotations and the IMG system will allow them to generate Genbank or EMBL format files containing these annotations.
16S ribosomal RNA is the RNA component of the 30S subunit of a prokaryotic ribosome. It binds to the Shine-Dalgarno sequence and provides most of the SSU structure.
The Reference Sequence (RefSeq) database is an open access, annotated and curated collection of publicly available nucleotide sequences and their protein products. RefSeq was introduced in 2000. This database is built by National Center for Biotechnology Information (NCBI), and, unlike GenBank, provides only a single record for each natural biological molecule for major organisms ranging from viruses to bacteria to eukaryotes.
The Human Microbiome Project (HMP) was a United States National Institutes of Health (NIH) research initiative to improve understanding of the microbiota involved in human health and disease. Launched in 2007, the first phase (HMP1) focused on identifying and characterizing human microbiota. The second phase, known as the Integrative Human Microbiome Project (iHMP) launched in 2014 with the aim of generating resources to characterize the microbiome and elucidating the roles of microbes in health and disease states. The program received $170 million in funding by the NIH Common Fund from 2007 to 2016.
MEGAN is a computer program that allows optimized analysis of large metagenomic datasets.
Fibrolytic bacteria constitute a group of microorganisms that are able to process complex plant polysaccharides thanks to their capacity to synthesize cellulolytic and hemicellulolytic enzymes. Polysaccharides are present in plant cellular cell walls in a compact fiber form where they are mainly composed of cellulose and hemicellulose.
De novo transcriptome assembly is the de novo sequence assembly method of creating a transcriptome without the aid of a reference genome.
The Earth Microbiome Project (EMP) is an initiative founded by Janet Jansson, Jack Gilbert and Rob Knight in 2010 to collect natural samples and to analyze the microbial community around the globe.
Viral metagenomics uses metagenomic technologies to detect viral genomic material from diverse environmental and clinical samples. Viruses are the most abundant biological entity and are extremely diverse; however, only a small fraction of viruses have been sequenced and only an even smaller fraction have been isolated and cultured. Sequencing viruses can be challenging because viruses lack a universally conserved marker gene so gene-based approaches are limited. Metagenomics can be used to study and analyze unculturable viruses and has been an important tool in understanding viral diversity and abundance and in the discovery of novel viruses. For example, metagenomics methods have been used to describe viruses associated with cancerous tumors and in terrestrial ecosystems.
Metatranscriptomics is the set of techniques used to study gene expression of microbes within natural environments, i.e., the metatranscriptome.
PICRUSt is a bioinformatics software package. The name is an abbreviation for Phylogenetic Investigation of Communities by Reconstruction of Unobserved States.
Virome refers to the assemblage of viruses that is often investigated and described by metagenomic sequencing of viral nucleic acids that are found associated with a particular ecosystem, organism or holobiont. The word is frequently used to describe environmental viral shotgun metagenomes. Viruses, including bacteriophages, are found in all environments, and studies of the virome have provided insights into nutrient cycling, development of immunity, and a major source of genes through lysogenic conversion. Also, the human virome has been characterized in nine organs of 31 Finnish individuals using qPCR and NGS methodologies.
Machine learning in bioinformatics is the application of machine learning algorithms to bioinformatics, including genomics, proteomics, microarrays, systems biology, evolution, and text mining.
Clinical metagenomic next-generation sequencing (mNGS) is the comprehensive analysis of microbial and host genetic material in clinical samples from patients by next-generation sequencing. It uses the techniques of metagenomics to identify and characterize the genome of bacteria, fungi, parasites, and viruses without the need for a prior knowledge of a specific pathogen directly from clinical specimens. The capacity to detect all the potential pathogens in a sample makes metagenomic next generation sequencing a potent tool in the diagnosis of infectious disease especially when other more directed assays, such as PCR, fail. Its limitations include clinical utility, laboratory validity, sense and sensitivity, cost and regulatory considerations.
Genome skimming is a sequencing approach that uses low-pass, shallow sequencing of a genome, to generate fragments of DNA, known as genome skims. These genome skims contain information about the high-copy fraction of the genome. The high-copy fraction of the genome consists of the ribosomal DNA, plastid genome (plastome), mitochondrial genome (mitogenome), and nuclear repeats such as microsatellites and transposable elements. It employs high-throughput, next generation sequencing technology to generate these skims. Although these skims are merely 'the tip of the genomic iceberg', phylogenomic analysis of them can still provide insights on evolutionary history and biodiversity at a lower cost and larger scale than traditional methods. Due to the small amount of DNA required for genome skimming, its methodology can be applied in other fields other than genomics. Tasks like this include determining the traceability of products in the food industry, enforcing international regulations regarding biodiversity and biological resources, and forensics.
