scholarly journals Selymatra: A web application for protein‐profiling analysis of mass spectra

2021 ◽  
Author(s):  
Davide Nardone ◽  
Angelo Ciaramella ◽  
Mariangela Cerreta ◽  
Salvatore Pulcrano ◽  
Gian C. Bellenchi ◽  
...  
Keyword(s):  
Web Application ◽  
Mass Spectra ◽  
Protein Profiling ◽  
Profiling Analysis

Protein profiling analysis of Gossypium hirsutum (Malvales: Malvaceae) leaves infested by cotton whitefly Bemisia tabaci (Homoptera: Aleyrodidae)

2016 ◽  
Vol 51 (4) ◽  
pp. 599-607 ◽  
Author(s):  
Muhammad Ibrahim ◽  
Sumaira Yasmeen ◽  
Ghanva Zaman ◽  
Li Bin ◽  
Fahad Al-Qurainy ◽  
...  
Keyword(s):  
Gossypium Hirsutum ◽  
Bemisia Tabaci ◽  
Protein Profiling ◽  
Cotton Whitefly ◽  
Profiling Analysis

scholarly journals Transcript and Protein Profiling Analysis of the Destruxin A-Induced Response in Larvae of Plutella xylostella

PLoS ONE ◽  
2013 ◽  
Vol 8 (4) ◽  
pp. e60771 ◽  
Author(s):  
Pengfei Han ◽  
Fengliang Jin ◽  
Xiaolin Dong ◽  
Jiqiao Fan ◽  
Baoli Qiu ◽  
...  
Keyword(s):  
Plutella Xylostella ◽  
Protein Profiling ◽  
Induced Response ◽  
Profiling Analysis

Mass-spectra-based peak alignment for automatic nontargeted metabolic profiling analysis for biomarker screening in plant samples

2017 ◽  
Vol 1513 ◽  
pp. 201-209 ◽  
Author(s):  
Hai-Yan Fu ◽  
Ou Hu ◽  
Yue-Ming Zhang ◽  
Li Zhang ◽  
Jing-Jing Song ◽  
...  
Keyword(s):  
Metabolic Profiling ◽  
Mass Spectra ◽  
Peak Alignment ◽  
Plant Samples ◽  
Metabolic Profiling Analysis ◽  
Profiling Analysis

scholarly journals Mass spectrometry analysis of protein blood extracts of animals with experimental brucellos

2019 ◽  
pp. 11-18
Author(s):  
D. V. Ulshina ◽  
D. A. Kovalev ◽  
D. G. Ponomarenko ◽  
D. V. Rusanova ◽  
T. V. Berdnikova ◽  
...  
Keyword(s):  
Mass Spectra ◽  
Direct Detection ◽  
Protein Profiling ◽  
Mass Spectrometry Analysis ◽  
Experimental Conditions ◽  
Spectrometry Analysis ◽  
Maldi Tof ◽  
Maldi Tof Mass Spectra ◽  
Causative Agents ◽  
Bruker Daltonics

Aim. The aim of the present research was to study the possibility of direct detection of the causative agent of brucellosis in a biomaterial under experimental conditions via the MALDI-TOF MS method using Mass-Up program resources and a set of packages for open-source statistical software R. Materials and methods. We used laboratory mice infected with the causative agents of Brucellosis (strains B. melitensis 548, B. abortus 544, B. suis 1330) as models. Protein profiling was performed on a MALDI-TOF Microflex «Bruker Daltonics» mass spectrometer. Results. The bioinformatic-statistical approach used for analyzing MALDI-TOF mass spectra allows to carry out a direct detection of Brucella in the biomaterial; besides, it is possible to determinate their species via the identification of a group of biomarkers. Conclusion. It was experimentally confirmed that the protein profiles of the blood extracts of infected animals contain 11 markers, including 6 genus specific for Brucella spp., which can be associated with Brucella infection.

Protein profiling analysis of skeletal muscle of a pufferfish, Takifugu rubripes

2009 ◽  
Vol 37 (5) ◽  
pp. 2141-2147 ◽  
Author(s):  
Jian Lu ◽  
Jianzhou Zheng ◽  
Haijun Liu ◽  
Jun Li ◽  
Huayou Chen ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Protein Profiling ◽  
Takifugu Rubripes ◽  
Profiling Analysis

scholarly journals Transcript and protein profiling analysis of OTA-induced cell death reveals the regulation of the toxicity response process in Arabidopsis thaliana

2011 ◽  
Vol 63 (5) ◽  
pp. 2171-2187 ◽  
Author(s):  
Yan Wang ◽  
Xiaoli Peng ◽  
Wentao Xu ◽  
YunBo Luo ◽  
Weiwei Zhao ◽  
...  
Keyword(s):  
Arabidopsis Thaliana ◽  
Cell Death ◽  
Protein Profiling ◽  
Response Process ◽  
Toxicity Response ◽  
Profiling Analysis

Identification of molds with MALDI-TOF mass spectrometry: performance of the newly developed MSI-2 application in comparison with the Bruker filamentous fungi database and MSI-1

2021 ◽  
Author(s):  
Anne-Cécile Normand ◽  
Marion Blaize ◽  
Sébastien Imbert ◽  
Ann Packeu ◽  
Pierre Becker ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Cryptic Species ◽  
Web Application ◽  
Mass Spectra ◽  
Positive Impact ◽  
Identification Performance ◽  
Ionization Time ◽  
Maldi Tof ◽  
Flight Mass Spectrometry ◽  
Promising Tool

Matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS) represents a promising tool for the rapid and efficient identification of molds, but improvements are still necessary to achieve satisfactory results when identifying cryptic species. Here, we aimed to validate a new web application, MSI-2, which replaces MSI-1, an application that was built and deployed online in 2017. For the evaluation, we gathered 633 challenging isolates obtained from daily hospital practice that were first identified with DNA-based methods, and we submitted their corresponding mass spectra to three identification programs (Bruker, MSI-1 and MSI-2). The MSI-2 application had a better identification performance at the species level than MSI-1 and Bruker, reaching 83.25% correct identifications compared with 63.19% (MSI-1), 38.07% (Bruker with 1.7 threshold) and 21.8% (Bruker with 2.0 threshold). The MSI-2 application performed especially well for Aspergillus and Fusarium species, including for many cryptic species, reaching 90% correct identifications for Aspergillus species and 78% for Fusarium species compared to 69% and 43% with MSI-1. Such improvement may have a positive impact on patient management by facilitating the identification of cryptic species potentially associated with a specific antifungal resistance profile.

scholarly journals NPS: scoring and evaluating the statistical significance of peptidic natural product–spectrum matches

2019 ◽  
Vol 35 (14) ◽  
pp. i315-i323 ◽  
Author(s):  
Azat M Tagirdzhanov ◽  
Alexander Shlemov ◽  
Alexey Gurevich
Keyword(s):  
Natural Product ◽  
Web Application ◽  
Mass Spectra ◽  
Statistical Significance ◽  
Database Search ◽  
Supplementary Information ◽  
Command Line ◽  
False Discovery ◽  
High Throughput Technology ◽  
Command Line Tool

Abstract Motivation Peptidic natural products (PNPs) are considered a promising compound class that has many applications in medicine. Recently developed mass spectrometry-based pipelines are transforming PNP discovery into a high-throughput technology. However, the current computational methods for PNP identification via database search of mass spectra are still in their infancy and could be substantially improved. Results Here we present NPS, a statistical learning-based approach for scoring PNP–spectrum matches. We incorporated NPS into two leading PNP discovery tools and benchmarked them on millions of natural product mass spectra. The results demonstrate more than 45% increase in the number of identified spectra and 20% more found PNPs at a false discovery rate of 1%. Availability and implementation NPS is available as a command line tool and as a web application at http://cab.spbu.ru/software/NPS. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Universal Spectrum Explorer: A standalone (web-)application for cross-resource spectrum comparison

2020 ◽  
Author(s):  
Tobias Schmidt ◽  
Patroklos Samaras ◽  
Viktoria Dorfer ◽  
Christian Panse ◽  
Tobias Kockmann ◽  
...  
Keyword(s):  
Web Application ◽  
Mass Spectra ◽  
Seamless Integration ◽  
Web Based ◽  
Tandem Mass Spectra ◽  
Learning Framework ◽  
Time Prediction ◽  
Link Type ◽  
Comparison Results ◽  
Universal Spectrum

AbstractHere we present the Universal Spectrum Explorer (USE), a web-based tool based on IPSA for cross-resource (peptide) spectrum visualization and comparison (https://www.proteomicsdb.org/use/). Mass spectra under investigation can either be provided manually by the user (table format), or automatically retrieved from online repositories supporting access to spectral data via the universal spectrum identifier (USI), or requested from other resources and services implementing a newly designed REST interface. As a proof of principle we implemented such an interface in ProteomicsDB thereby allowing the retrieval of spectra acquired within the ProteomeTools project. In addition, USE can retrieve real-time prediction of tandem mass spectra from the deep learning framework Prosit. Comparison results like annotated mirror spectrum plots can be exported from USE as editable scalable high quality vector graphics. The USE was designed and implemented with minimal external dependencies allowing local usage and seamless integration into websites (https://github.com/kusterlab/universal_spectrum_explorer).

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