In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI's website. NCBI resources include Entrez, PubMed, PubMed Central, LocusLink, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR, OrfFinder, Spidey, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosome Aberration Project (CCAP), Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups (COGs) database, Retroviral Genotyping Tools, SARS Coronavirus Resource, SAGEmap, Gene Expression Omnibus (GEO), Online Mendelian Inheritance in Man (OMIM), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD) and the Conserved Domain Architecture Retrieval Tool (CDART). Augmenting many of the web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of the resources can be accessed through the NCBI home page at: http://www.ncbi.nlm.nih.gov.

/pdf/database-resources-of-the-national-center-for-biotechnology-36jlaw3fxd.pdf

Database resources of the National Center for Biotechnology Information

A main bottleneck in proteomics is the downstream biological analysis of highly multivariate quantitative protein abundance data generated using mass-spectrometry-based analysis. We developed the Perseus software platform (http://www.perseus-framework.org) to support biological and biomedical researchers in interpreting protein quantification, interaction and post-translational modification data. Perseus contains a comprehensive portfolio of statistical tools for high-dimensional omics data analysis covering normalization, pattern recognition, time-series analysis, cross-omics comparisons and multiple-hypothesis testing. A machine learning module supports the classification and validation of patient groups for diagnosis and prognosis, and it also detects predictive protein signatures. Central to Perseus is a user-friendly, interactive workflow environment that provides complete documentation of computational methods used in a publication. All activities in Perseus are realized as plugins, and users can extend the software by programming their own, which can be shared through a plugin store. We anticipate that Perseus's arsenal of algorithms and its intuitive usability will empower interdisciplinary analysis of complex large data sets.

/pdf/the-perseus-computational-platform-for-comprehensive-5a4p3g7pp4.pdf

The Perseus computational platform for comprehensive analysis of (prote)omics data.

BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

“Bioinformatics” 특집을 내면서

A key step in mass spectrometry (MS)-based proteomics is the identification of peptides in sequence databases by their fragmentation spectra. Here we describe Andromeda, a novel peptide search engine using a probabilistic scoring model. On proteome data, Andromeda performs as well as Mascot, a widely used commercial search engine, as judged by sensitivity and specificity analysis based on target decoy searches. Furthermore, it can handle data with arbitrarily high fragment mass accuracy, is able to assign and score complex patterns of post-translational modifications, such as highly phosphorylated peptides, and accommodates extremely large databases. The algorithms of Andromeda are provided. Andromeda can function independently or as an integrated search engine of the widely used MaxQuant computational proteomics platform and both are freely available at www.maxquant.org. The combination enables analysis of large data sets in a simple analysis workflow on a desktop computer. For searching individual spect...

https://pubs.acs.org/doi/pdfplus/10.1021/pr101065j?src=recsys

Andromeda: a peptide search engine integrated into the MaxQuant environment

基礎講座 電気泳動(Electrophoresis)

Large numbers of MS/MS peptide spectra generated in proteomics experiments require efficient, sensitive and specific algorithms for peptide identification. In the Open Mass Spectrometry Search Algorithm [OMSSA], specificity is calculated by a classic probability score using an explicit model for matching experimental spectra to sequences. At default thresholds, OMSSA matches more spectra from a standard protein cocktail than a comparable algorithm. OMSSA is designed to be faster than published algorithms in searching large MS/MS datasets.

Open Mass Spectrometry Search Algorithm

Large numbers of MS/MS peptide spectra generated in proteomics experiments require efficient, sensitive and specific algorithms for peptide identification. In the Open Mass Spectrometry Search Algorithm (OMSSA), specificity is calculated by a classic probability score using an explicit model for matching experimental spectra to sequences. At default thresholds, OMSSA matches more spectra from a standard protein cocktail than a comparable algorithm. OMSSA is designed to be faster than published algorithms in searching large MS/MS datasets. Keywords: protein identification • algorithm • bioinformatics • mass spectrometry • proteomics • significance testing

Open mass spectrometry search algorithm.

Electrospray ionization (ESI) tandem mass spectrometry coupled with liquid chromatography is a routine technique for identifying and quantifying compounds in complex mixtures. The identification step can be aided by matching acquired tandem mass spectra (MS2) against reference library spectra as is routine for electron ionization (EI) spectra from gas chromatography/mass spectrometry (GC/MS). However, unlike the latter spectra, ESI MS2 spectra are likely to originate from various precursor ions for a given target molecule and may be acquired at varying energies and resolutions and have characteristic noise signatures, requiring processing methods very different from EI to obtain complete and high quality reference spectra for individual analytes. This paper presents procedures developed for creating a tandem mass spectral library that addresses these factors. Library building begins by acquiring MS2 spectra for all major MS1 peaks in an infusion run, followed by assigning MS2 spectra to clusters and creat...

Quality control for building libraries from electrospray ionization tandem mass spectra.

https://link.springer.com/content/pdf/10.1007%2Fs13361-017-1748-2.pdf

Extending a Tandem Mass Spectral Library to Include MS 2 Spectra of Fragment Ions Produced In-Source and MS n Spectra

https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=831981

Xiaoyu Yang

Papers

Open Mass Spectrometry Search Algorithm

Open mass spectrometry search algorithm.

Quality control for building libraries from electrospray ionization tandem mass spectra.

Extending a Tandem Mass Spectral Library to Include MS 2 Spectra of Fragment Ions Produced In-Source and MS n Spectra

Dehydration versus deamination of N-terminal glutamine in collision-induced dissociation of protonated peptides