Dataset Information

Discovery of diffuse optical emission lines from the inner Galaxy: Evidence for LI(N)ER-like gas.

ABSTRACT: Optical emission lines are used to categorize galaxies into three groups according to their dominant central radiation source: active galactic nuclei, star formation, or low-ionization (nuclear) emission regions [LI(N)ERs] that may trace ionizing radiation from older stellar populations. Using the Wisconsin H-Alpha Mapper, we detect optical line emission in low-extinction windows within eight degrees of Galactic Center. The emission is associated with the 1.5-kiloparsec-radius "Tilted Disk" of neutral gas. We modify a model of this disk and find that the hydrogen gas observed is at least 48% ionized. The ratio [NII] ?6584 angstroms/H? ?6563 angstroms increases from 0.3 to 2.5 with Galactocentric radius; [OIII] ?5007 angstroms and H? ?4861 angstroms are also sometimes detected. The line ratios for most Tilted Disk sightlines are characteristic of LI(N)ER galaxies.

SUBMITTER: Krishnarao D

PROVIDER: S-EPMC7455492 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Discovery of diffuse optical emission lines from the inner Galaxy: Evidence for LI(N)ER-like gas.

Krishnarao D D Benjamin R A RA Haffner L M LM

Science advances 20200703 27

Optical emission lines are used to categorize galaxies into three groups according to their dominant central radiation source: active galactic nuclei, star formation, or low-ionization (nuclear) emission regions [LI(N)ERs] that may trace ionizing radiation from older stellar populations. Using the Wisconsin H-Alpha Mapper, we detect optical line emission in low-extinction windows within eight degrees of Galactic Center. The emission is associated with the 1.5-kiloparsec-radius "Tilted Disk" of n ...[more]

PMID: 32923581

Similar Datasets

Project description:BackgroundCurrent practice in mass spectrometry (MS)-based proteomics is to identify peptides by comparison of experimental mass spectra with theoretical mass spectra derived from a reference protein database; however, this strategy necessarily fails to detect peptide and protein sequences that are absent from the database. We and others have recently shown that customized proteomic databases derived from RNA-Seq data can be employed for MS-searching to both improve MS analysis and identify novel peptides. While this general strategy constitutes a significant advance for the discovery of novel protein variations, it has not been readily transferable to other laboratories due to the need for many specialized software tools. To address this problem, we have implemented readily accessible, modifiable, and extensible workflows within Galaxy-P, short for Galaxy for Proteomics, a web-based bioinformatic extension of the Galaxy framework for the analysis of multi-omics (e.g. genomics, transcriptomics, proteomics) data.ResultsWe present three bioinformatic workflows that allow the user to upload raw RNA sequencing reads and convert the data into high-quality customized proteomic databases suitable for MS searching. We show the utility of these workflows on human and mouse samples, identifying 544 peptides containing single amino acid polymorphisms (SAPs) and 187 peptides corresponding to unannotated splice junction peptides, correlating protein and transcript expression levels, and providing the option to incorporate transcript abundance measures within the MS database search process (reduced databases, incorporation of transcript abundance for protein identification score calculations, etc.).ConclusionsUsing RNA-Seq data to enhance MS analysis is a promising strategy to discover novel peptides specific to a sample and, more generally, to improve proteomics results. The main bottleneck for widespread adoption of this strategy has been the lack of easily used and modifiable computational tools. We provide a solution to this problem by introducing a set of workflows within the Galaxy-P framework that converts raw RNA-Seq data into customized proteomic databases.

Dataset Information

Discovery of diffuse optical emission lines from the inner Galaxy: Evidence for LI(N)ER-like gas.

Publications

Discovery of diffuse optical emission lines from the inner Galaxy: Evidence for LI(N)ER-like gas.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets