Comparative genomicsComparative genomics is a field of biological research in which the genomic features of different organisms are compared. The genomic features may include the DNA sequence, genes, gene order, regulatory sequences, and other genomic structural landmarks. In this branch of genomics, whole or large parts of genomes resulting from genome projects are compared to study basic biological similarities and differences as well as evolutionary relationships between organisms.
Transcriptomics technologiesTranscriptomics technologies are the techniques used to study an organism's transcriptome, the sum of all of its RNA transcripts. The information content of an organism is recorded in the DNA of its genome and expressed through transcription. Here, mRNA serves as a transient intermediary molecule in the information network, whilst non-coding RNAs perform additional diverse functions. A transcriptome captures a snapshot in time of the total transcripts present in a cell.
Gene expressionGene expression is the process by which information from a gene is used in the synthesis of a functional gene product that enables it to produce end products, proteins or non-coding RNA, and ultimately affect a phenotype. These products are often proteins, but in non-protein-coding genes such as transfer RNA (tRNA) and small nuclear RNA (snRNA), the product is a functional non-coding RNA.
GeneIn biology, the word gene (from γένος, génos; meaning generation or birth or gender) can have several different meanings. The Mendelian gene is a basic unit of heredity and the molecular gene is a sequence of nucleotides in DNA that is transcribed to produce a functional RNA. There are two types of molecular genes: protein-coding genes and noncoding genes. During gene expression, the DNA is first copied into RNA. The RNA can be directly functional or be the intermediate template for a protein that performs a function.
Metabolic network modellingMetabolic network modelling, also known as metabolic network reconstruction or metabolic pathway analysis, allows for an in-depth insight into the molecular mechanisms of a particular organism. In particular, these models correlate the genome with molecular physiology. A reconstruction breaks down metabolic pathways (such as glycolysis and the citric acid cycle) into their respective reactions and enzymes, and analyzes them within the perspective of the entire network.
Gene expression profilingIn the field of molecular biology, gene expression profiling is the measurement of the activity (the expression) of thousands of genes at once, to create a global picture of cellular function. These profiles can, for example, distinguish between cells that are actively dividing, or show how the cells react to a particular treatment. Many experiments of this sort measure an entire genome simultaneously, that is, every gene present in a particular cell. Several transcriptomics technologies can be used to generate the necessary data to analyse.
De novo gene birthDe novo gene birth is the process by which new genes evolve from DNA sequences that were ancestrally non-genic. De novo genes represent a subset of novel genes, and may be protein-coding or instead act as RNA genes. The processes that govern de novo gene birth are not well understood, although several models exist that describe possible mechanisms by which de novo gene birth may occur. Although de novo gene birth may have occurred at any point in an organism's evolutionary history, ancient de novo gene birth events are difficult to detect.
RNA interferenceRNA interference (RNAi) is a biological process in which RNA molecules are involved in sequence-specific suppression of gene expression by double-stranded RNA, through translational or transcriptional repression. Historically, RNAi was known by other names, including co-suppression, post-transcriptional gene silencing (PTGS), and quelling. The detailed study of each of these seemingly different processes elucidated that the identity of these phenomena were all actually RNAi. Andrew Fire and Craig C.
BioinformaticsBioinformatics (ˌbaɪ.oʊˌɪnfɚˈmætɪks) 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.
DataIn common usage and statistics, data (USˈdætə; UKˈdeɪtə) is a collection of discrete or continuous values that convey information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted formally. A datum is an individual value in a collection of data. Data is usually organized into structures such as tables that provide additional context and meaning, and which may themselves be used as data in larger structures.
HumanHumans, or modern humans (Homo sapiens), are the most common and widespread species of primate. A great ape characterized by their hairlessness, bipedalism, and high intelligence, humans have a large brain and resulting cognitive skills that enable them to thrive in varied environments and develop complex societies and civilizations. Humans are highly social and tend to live in complex social structures composed of many cooperating and competing groups, from families and kinship networks to political states.
Serial analysis of gene expressionSerial Analysis of Gene Expression (SAGE) is a transcriptomic technique used by molecular biologists to produce a snapshot of the messenger RNA population in a sample of interest in the form of small tags that correspond to fragments of those transcripts. Several variants have been developed since, most notably a more robust version, LongSAGE, RL-SAGE and the most recent SuperSAGE. Many of these have improved the technique with the capture of longer tags, enabling more confident identification of a source gene.
Regulation of gene expressionRegulation of gene expression, or gene regulation, includes a wide range of mechanisms that are used by cells to increase or decrease the production of specific gene products (protein or RNA). Sophisticated programs of gene expression are widely observed in biology, for example to trigger developmental pathways, respond to environmental stimuli, or adapt to new food sources. Virtually any step of gene expression can be modulated, from transcriptional initiation, to RNA processing, and to the post-translational modification of a protein.
MetagenomicsMetagenomics 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. While traditional microbiology and microbial genome sequencing and genomics rely upon cultivated clonal cultures, early environmental gene sequencing cloned specific genes (often the 16S rRNA gene) to produce a profile of diversity in a natural sample.
Overlapping geneAn overlapping gene (or OLG) is a gene whose expressible nucleotide sequence partially overlaps with the expressible nucleotide sequence of another gene. In this way, a nucleotide sequence may make a contribution to the function of one or more gene products. Overlapping genes are present and a fundamental feature of both cellular and viral genomes. The current definition of an overlapping gene varies significantly between eukaryotes, prokaryotes, and viruses.
Threading (protein sequence)In molecular biology, protein threading, also known as fold recognition, is a method of protein modeling which is used to model those proteins which have the same fold as proteins of known structures, but do not have homologous proteins with known structure. It differs from the homology modeling method of structure prediction as it (protein threading) is used for proteins which do not have their homologous protein structures deposited in the Protein Data Bank (PDB), whereas homology modeling is used for those proteins which do.
HomoHomo () is the genus that emerged from the genus Australopithecus and encompasses the extant species Homo sapiens (modern humans) and several extinct species classified as either ancestral to or closely related to modern humans, including Homo erectus and Homo neanderthalensis. The oldest member of the genus is Homo habilis, with records of just over 2 million years ago. Homo, together with the genus Paranthropus, is probably sister to Australopithecus africanus, which itself had split from the lineage of Pan, the chimpanzees.
Single-nucleotide polymorphismIn genetics and bioinformatics, a single-nucleotide polymorphism (SNP snɪp; plural SNPs snɪps) is a germline substitution of a single nucleotide at a specific position in the genome that is present in a sufficiently large fraction of considered population (generally regarded as 1% or more). For example, a G nucleotide present at a specific location in a reference genome may be replaced by an A in a minority of individuals. The two possible nucleotide variations of this SNP – G or A – are called alleles.
Whole genome sequencingWhole genome sequencing (WGS), also known as full genome sequencing, complete genome sequencing, or entire genome sequencing, is the process of determining the entirety, or nearly the entirety, of the DNA sequence of an organism's genome at a single time. This entails sequencing all of an organism's chromosomal DNA as well as DNA contained in the mitochondria and, for plants, in the chloroplast. Whole genome sequencing has largely been used as a research tool, but was being introduced to clinics in 2014.
Microarray analysis techniquesMicroarray analysis techniques are used in interpreting the data generated from experiments on DNA (Gene chip analysis), RNA, and protein microarrays, which allow researchers to investigate the expression state of a large number of genes - in many cases, an organism's entire genome - in a single experiment. Such experiments can generate very large amounts of data, allowing researchers to assess the overall state of a cell or organism. Data in such large quantities is difficult - if not impossible - to analyze without the help of computer programs.
