Genom glossary

Genom glossary

Genom glossary


J. S.
Diese Karteikarten bieten einen umfassenden Überblick über grundlegende und fortgeschrittene Konzepte der Genomik, einschließlich DNA-Sequenzierung, Metagenomik und Genomanalyse. Sie decken Themen wie Contigs, Genomanalyse, Sequenzierung und Genomanalyse ab und sind ideal für Studierende und Forscher, die ihr Verständnis der Genomik vertiefen möchten.
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Deutsch
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Biologie
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Erstellt / Aktualisiert
01.02.2018 / 01.02.2018

Lernkarten

Positive selection

• Acts to increase the frequency of beneficial alleles in the population.

Integron

• A mobile genetic element carrying an integrase, which allows acquisition (or loss) of genes by homologous recombination.

Bacteriophage

• A virus that infects bacteria. A bacteriophage can either lyse a cell or integrate into its genome.

Phase variation

• A spontaneous genetically defined switch between expression of alternative, usually surface-associated, proteins that occurs at a high frequency.

Pathoadaptation

• Genome modification to a pathogenic lifestyle by genome reduction and acquisition of pathogenicity-related genes

Virulence factor

• A factor that is produced by a pathogen and required for it to cause disease. It should be noted that defining this term precisely is difficult.

Pathogen

• An organism that can cause disease in another organism.

Pathogenicity island

• A cluster of genes acquired by horizontal gene transfer that encodes products that contribute to virulence.

Insertion sequence

• The simplest type of transposable element in bacteria. It contains only the genes required for its own transposition.

Horizontal gene transfer

• Any process in which an organism transfers genetic material to another cell that is not its offspring. This process is in contrast to vertical gene transfer, which is much more common and occurs when genetic material is passed from parent to offspring or, more generally, from ancestor to descendent.

Singletons (unique genes)

• Specific genes to single strains

Dispensable genome

• Genes present in two or more strains, but not in all

Pan genome

• The total of gene sets of all strains in a clade. • Includes the core genome, dispensable genome and unique genes (singletons).

Next Generation Sequencing

• High-throughput sequencing method that parallelizes the sequencing process to produce millions of sequences at once.

First Generation Sequencing

• Sanger sequencing aka Chain termination sequencing

Primer walking

• Method for closing gaps in genomes using Sanger sequencing. Slow progress through repetitive cycles of sequencing and primer design

Coding density

• Amount of “free space” on the genome.

CDS

• Coding sequence, i.e. a region on the genome that is translated into a protein.

Genome

• The collective DNA sequences of an organism.

Metagenomics

• Study of metagenomes, genetic material recovered directly from environmental samples.

Metabolomics

• Study of the collection of all metabolites in a biological cell, tissue, organ or organism, which are the end products of cellular processes.

Proteomics

• Study of the entire complement of proteins, including the modifications made to a particular set of proteins, produced by an organism or system.

Transcriptomics

• Study of the set of all RNA molecules, including mRNA, rRNA, tRNA, and other non-coding RNA produced in one or a population of cells under a given condition.

Genomics

• Study of the set of all DNA molecules in one or a population of cells.

Bioinformatics

• Field of science in which biology, computer science, and information technology merge to form a single discipline. The ultimate goal of the field is to enable the discovery of new biological insights as well as to create a global perspective from which unifying principles in biology can be discerned.• Bioinformatics deals with algorithms, databases and information systems, web technologies, artificial intelligence and soft computing, information and computation theory, software engineering, data mining, image processing, modeling and simulation, signal processing, discrete mathematics, control and system theory, circuit theory, and statistics, for generating new knowledge of biology and medicine, and improving & discovering new models of computation (e.g. DNA computing, neural computing, evolutionary computing, immuno-computing, swarm-computing, cellular-computing).

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