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Bioinformatics is the name given to these mathematical and computing approaches used to glean understanding of biological processes. Common activities in bioinformatics include mapping and analyzing DNA and protein sequences, aligning DNA and protein sequences to compare them, and creating and viewing 3-D models of protein structures.
Structural bioinformatics is the branch of bioinformatics that is related to the analysis and prediction of the three-dimensional structure of biological macromolecules such as proteins, RNA, and DNA. It deals with generalizations about macromolecular 3D structures such as comparisons of overall folds and local motifs, principles of molecular ...
Proteomics enables the identification of ever-increasing numbers of proteins. This varies with time and distinct requirements, or stresses, that a cell or organism undergoes. [3] Proteomics is an interdisciplinary domain that has benefited greatly from the genetic information of various genome projects, including the Human Genome Project. [4]
Spectronaut 19 Elevates the Scale and Scope of DIA Proteomics. A seminar on Wednesday, October 23 will feature two key presentations that showcase novel applications of Spectronaut 19. Ben Collins, PhD, from Queen’s University Belfast, will introduce a newly established pipeline for large-scale analysis of dia-PASEF data using Spectronaut 19 ...
Its main goal is to provide user-friendly, high-throughput data processing services to analyse proteomics liquid chromatography-mass spectrometry (LC-MS) data based on open source tools or tools developed and available within the platform members and build an infrastructure that will make possible for non-experts i.e. wet lab scientists to run ...
wapRNA This is a free web-based application for the processing of high-throughput RNA-Seq data (wapRNA) from next generation sequencing (NGS) platforms, such as Genome Analyzer of Illumina Inc. (Solexa) and SOLiD of Applied Biosystems (SOLiD). wapRNA provides an integrated tool for RNA sequence, refers to the use of High-throughput sequencing ...
Deep learning applications have been used for regulatory genomics and cellular imaging. [33] Other applications include medical image classification, genomic sequence analysis, as well as protein structure classification and prediction. [34] Deep learning has been applied to regulatory genomics, variant calling and pathogenicity scores. [35]
Proteomics pertains to protein expression profiling i.e. which proteins are expressed in the lysate of a particular cell. Protein functional analysis is the identification of protein–protein interactions (e.g. identification of members of a protein complex), protein–phospholipid interactions, small molecule targets, enzymatic substrates ...