scholarly journals Towards Mass Spectrometry-Based Chemical Exposome: Current Approaches, Challenges, and Future Directions

Toxics ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 41 ◽  
Author(s):  
Jingchuan Xue ◽  
Yunjia Lai ◽  
Chih-Wei Liu ◽  
Hongyu Ru
Keyword(s):  
Mass Spectrometry ◽  
Data Analysis ◽  
Measurement Techniques ◽  
Future Directions ◽  
Computational Tools ◽  
High Throughput Data ◽  
Chemical Pollutants ◽  
Health And Disease ◽  
High Throughput Data Analysis

The proposal of the “exposome” concept represents a shift of the research paradigm in studying exposure-disease relationships from an isolated and partial way to a systematic and agnostic approach. Nevertheless, exposome implementation is facing a variety of challenges including measurement techniques and data analysis. Here we focus on the chemical exposome, which refers to the mixtures of chemical pollutants people are exposed to from embryo onwards. We review the current chemical exposome measurement approaches with a focus on those based on the mass spectrometry. We further explore the strategies in implementing the concept of chemical exposome and discuss the available chemical exposome studies. Early progresses in the chemical exposome research are outlined, and major challenges are highlighted. In conclusion, efforts towards chemical exposome have only uncovered the tip of the iceberg, and further advancement in measurement techniques, computational tools, high-throughput data analysis, and standardization may allow more exciting discoveries concerning the role of exposome in human health and disease.

High-Throughput Data Analysis of Proteomic Mass Spectra on the SwissBioGrid

2011 ◽  
pp. 228-244
Author(s):  
Andreas Quandt ◽  
Sergio Maffioletti ◽  
Cesare Pautasso ◽  
Heinz Stockinger ◽  
Frederique Lisacek
Keyword(s):  
Mass Spectrometry ◽  
Data Analysis ◽  
High Throughput ◽  
Protein Function ◽  
Mass Spectra ◽  
High Throughput Data ◽  
Analysis Process ◽  
Speed Up ◽  
Grid Infrastructures ◽  
High Throughput Data Analysis

Proteomics is currently one of the most promising fields in bioinformatics as it provides important insights into the protein function of organisms. Mass spectrometry is one of the techniques to study the proteome, and several software tools exist for this purpose. The authors provide an extendable software platform called swissPIT that combines different existing tools and exploits Grid infrastructures to speed up the data analysis process for the proteomics pipeline.

scholarly journals Unraveling molecular mechanism underlying biomaterial and stem cells interaction during cell fate commitment using high throughput data analysis

2020 ◽  
Author(s):  
Erfan Sharifi ◽  
Niusha Khazaei ◽  
Nicholas Kieran ◽  
Sahel Jahangiri Esfahani ◽  
Abdulshakour Mohammadnia ◽  
...  
Keyword(s):  
Stem Cells ◽  
Data Analysis ◽  
Molecular Mechanism ◽  
Cell Fate ◽  
High Throughput ◽  
High Throughput Data ◽  
High Throughput Data Analysis

Are Cyber Attackers Thinking Fast and Slow? Exploratory Analysis Reveals Evidence of Decision-Making Biases in Red Teamers

2019 ◽  
Vol 63 (1) ◽  
pp. 427-431 ◽  
Author(s):  
Robert S. Gutzwiller ◽  
Kimberly J. Ferguson-Walter ◽  
Sunny J. Fugate
Keyword(s):  
Decision Making ◽  
Cognitive Biases ◽  
Measurement Techniques ◽  
Observational Evidence ◽  
Experimental Conditions ◽  
Future Directions ◽  
Take The Best ◽  
Behavioral Measurement ◽  
Decision Making Biases

We report on whether cyber attacker behaviors contain decision making biases. Data from a prior experiment were analyzed in an exploratory fashion, making use of think-aloud responses from a small group of red teamers. The analysis provided new observational evidence of traditional decision-making biases in red team behaviors (confirmation bias, anchoring, and take-the-best heuristic use). These biases may disrupt red team decisions and goals, and simultaneously increase their risk of detection. Interestingly, at least part of the bias induction may be related to the use of cyber deception. Future directions include the development of behavioral measurement techniques for these and additional cognitive biases in cyber operators, examining the role of attacker traits, and identifying the conditions where biases can be induced successfully in experimental conditions.

scholarly journals Unraveling molecular mechanism underlying biomaterial and stem cells interaction during cell fate commitment using high throughput data analysis

Gene ◽  
2021 ◽  
pp. 146111
Author(s):  
Erfan Sharifi ◽  
Niusha Khazaei ◽  
Nicholas W. Kieran ◽  
Sahel Jahangiri Esfahani ◽  
Abdulshakour Mohammadnia ◽  
...  
Keyword(s):  
Stem Cells ◽  
Data Analysis ◽  
Molecular Mechanism ◽  
Cell Fate ◽  
High Throughput ◽  
High Throughput Data ◽  
High Throughput Data Analysis

scholarly journals CSI NGS Portal: An Online Platform for Automated NGS Data Analysis and Sharing

2020 ◽  
Vol 21 (11) ◽  
pp. 3828
Author(s):  
Omer An ◽  
Kar-Tong Tan ◽  
Ying Li ◽  
Jia Li ◽  
Chan-Shuo Wu ◽  
...  
Keyword(s):  
Data Analysis ◽  
Final Report ◽  
Online Platform ◽  
Fastq Format ◽  
Health And Disease ◽  
Ngs Data Analysis ◽  
Next Generation Sequencing Ngs ◽  
User Friendly ◽  
Ngs Data

Next-generation sequencing (NGS) has been a widely-used technology in biomedical research for understanding the role of molecular genetics of cells in health and disease. A variety of computational tools have been developed to analyse the vastly growing NGS data, which often require bioinformatics skills, tedious work and a significant amount of time. To facilitate data processing steps minding the gap between biologists and bioinformaticians, we developed CSI NGS Portal, an online platform which gathers established bioinformatics pipelines to provide fully automated NGS data analysis and sharing in a user-friendly website. The portal currently provides 16 standard pipelines for analysing data from DNA, RNA, smallRNA, ChIP, RIP, 4C, SHAPE, circRNA, eCLIP, Bisulfite and scRNA sequencing, and is flexible to expand with new pipelines. The users can upload raw data in FASTQ format and submit jobs in a few clicks, and the results will be self-accessible via the portal to view/download/share in real-time. The output can be readily used as the final report or as input for other tools depending on the pipeline. Overall, CSI NGS Portal helps researchers rapidly analyse their NGS data and share results with colleagues without the aid of a bioinformatician. The portal is freely available at: https://csibioinfo.nus.edu.sg/csingsportal.

scholarly journals Power and Stability Properties of Resampling-Based Multiple Testing Procedures with Applications to Gene Oncology Studies

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Dongmei Li ◽  
Timothy D. Dye
Keyword(s):  
Data Analysis ◽  
Sample Size ◽  
High Throughput ◽  
Rate Control ◽  
Multiple Testing ◽  
Testing Procedures ◽  
High Throughput Data ◽  
False Discovery ◽  
Multiple Testing Procedures ◽  
High Throughput Data Analysis

Resampling-based multiple testing procedures are widely used in genomic studies to identify differentially expressed genes and to conduct genome-wide association studies. However, the power and stability properties of these popular resampling-based multiple testing procedures have not been extensively evaluated. Our study focuses on investigating the power and stability of seven resampling-based multiple testing procedures frequently used in high-throughput data analysis for small sample size data through simulations and gene oncology examples. The bootstrap single-step minPprocedure and the bootstrap step-down minPprocedure perform the best among all tested procedures, when sample size is as small as 3 in each group and either familywise error rate or false discovery rate control is desired. When sample size increases to 12 and false discovery rate control is desired, the permutation maxTprocedure and the permutation minPprocedure perform best. Our results provide guidance for high-throughput data analysis when sample size is small.

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