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FASTGenomics enables the user to upload their own data and generate customized and reproducible workflows for the exploration and analysis of gene expression data (Scholz et al. 2018). FX FX is a user-Friendly RNA-Seq gene eXpression analysis tool, empowered by the concept of cloud-computing. With FX, you can simply upload your RNA-Seq raw ...
Name Description Knots [Note 1]Links References trRosettaRNA: trRosettaRNA is an algorithm for automated prediction of RNA 3D structure. It builds the RNA structure by Rosetta energy minimization, with deep learning restraints from a transformer network (RNAformer). trRosettaRNA has been validated in blind tests, including CASP15 and RNA-Puzzles, which suggests that the automated predictions ...
Regulation of gene expression gives control over the timing, location, and amount of a given gene product (protein or ncRNA) present in a cell and can have a profound effect on the cellular structure and function. Regulation of gene expression is the basis for cellular differentiation, development, morphogenesis and the versatility and ...
An example Gene Ontology (GO) ancestor chart organized as a directed acyclic graph taken from QuickGO. [39] It shows the molecular functions, biological processes, and cellular components in which the matrilin complex, a component of the extracellular matrix, is involved. Every box is an ontology term that falls into one of the three GO ...
In 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.
[131] [132] Weighted gene co-expression network analysis has been successfully used to identify co-expression modules and intramodular hub genes based on RNA seq data. Co-expression modules may correspond to cell types or pathways. Highly connected intramodular hubs can be interpreted as representatives of their respective module.
There are two distinctive mapping approaches used in the field of genome mapping: genetic maps (also known as linkage maps) [7] and physical maps. [3] While both maps are a collection of genetic markers and gene loci, [8] genetic maps' distances are based on the genetic linkage information, while physical maps use actual physical distances usually measured in number of base pairs.
The Punnett square is a visual representation of Mendelian inheritance, a fundamental concept in genetics discovered by Gregor Mendel. [10] For multiple traits, using the "forked-line method" is typically much easier than the Punnett square.