A review on moderated-t methods for differential expression detection

2020 ◽  
pp. 1-4
Keyword(s):  
Differential Expression ◽  
Computational Methods ◽  
High Throughput ◽  
Biomedical Research ◽  
Expression Level ◽  
High Throughput Technology ◽  
Similarities And Differences ◽  
Statistical Approaches ◽  
Multiple Domains ◽  
Differential Expression Detection

With the advancement of high-throughput technology, identifying differential expression has become an essential task in multiple domains of biomedical research, such as transcriptome, proteome, metabolome. A wide variety of computational methods and statistical approaches were developed for detecting differential expression. Most of these methods were applicable to modeling expression level of the entire set of features simultaneously. In this article, we provide a review emphasizing on moderated-t methods published in last two decades. We compared similarities and differences between them, and also discussed their limitations in applications.

scholarly journals Enhanced longitudinal differential expression detection in proteomics with robust reproducibility optimization regression

2021 ◽  
Author(s):  
Tommi Valikangas ◽  
Tomi Suomi ◽  
Courtney E Chandler ◽  
Alison J Scott ◽  
Bao Q Tran ◽  
...  
Keyword(s):  
Differential Expression ◽  
High Throughput ◽  
Quantitative Proteomics ◽  
Missing Values ◽  
Comprehensive Evaluation ◽  
Omics Data ◽  
Good Reproducibility ◽  
Proteomics Data ◽  
Time Points ◽  
Differential Expression Detection

Quantitative proteomics has matured into an established tool and longitudinal proteomic experiments have begun to emerge. However, no effective, simple-to-use differential expression method for longitudinal proteomics data has been released. Typically, such data is noisy, contains missing values, has only few time points and biological replicates. To address this need, we provide a comprehensive evaluation of several existing differential expression methods for high-throughput longitudinal omics data and introduce a new method, Robust longitudinal Differential Expression (RolDE). The methods were evaluated using nearly 2000 semi-simulated spike-in proteomic datasets and a large experimental dataset. The RolDE method performed overall best; it was most tolerant to missing values, displayed good reproducibility and was the top method in ranking the results in a biologically meaningful way. Furthermore, contrary to many approaches, the open source RolDE does not require prior knowledge concerning the types of differences searched, but can easily be applied even by non-experienced users.

Kinetic Solvent Effects in Organic Reactions

2017 ◽  
Author(s):  
Belinda Slakman ◽  
Richard West
Keyword(s):  
Solvent Effect ◽  
Reaction Kinetics ◽  
Computational Methods ◽  
High Throughput ◽  
Kinetic Modeling ◽  
Solvent Effects ◽  
Reaction Rates ◽  
Prior Work ◽  
Solvent Phase ◽  
High Throughput Manner

<div> <div> <div> <p>This article reviews prior work studying reaction kinetics in solution, with the goal of using this information to improve detailed kinetic modeling in the solvent phase. Both experimental and computational methods for calculating reaction rates in liquids are reviewed. Previous studies, which used such methods to determine solvent effects, are then analyzed based on reaction family. Many of these studies correlate kinetic solvent effect with one or more solvent parameters or properties of reacting species, but it is not always possible, and investigations are usually done on too few reactions and solvents to truly generalize. From these studies, we present suggestions on how best to use data to generalize solvent effects for many different reaction types in a high throughput manner. </p> </div> </div> </div>

scholarly journals Applications of Metabolomics in Forensic Toxicology and Forensic Medicine

2021 ◽  
Vol 22 (6) ◽  
pp. 3010
Author(s):  
Michal Szeremeta ◽  
Karolina Pietrowska ◽  
Anna Niemcunowicz-Janica ◽  
Adam Kretowski ◽  
Michal Ciborowski
Keyword(s):  
Machine Learning ◽  
Multivariate Statistics ◽  
High Throughput ◽  
Forensic Medicine ◽  
Forensic Toxicology ◽  
Metabolic Changes ◽  
Untargeted Metabolomics ◽  
Criminal Cases ◽  
Statistical Approaches

Forensic toxicology and forensic medicine are unique among all other medical fields because of their essential legal impact, especially in civil and criminal cases. New high-throughput technologies, borrowed from chemistry and physics, have proven that metabolomics, the youngest of the “omics sciences”, could be one of the most powerful tools for monitoring changes in forensic disciplines. Metabolomics is a particular method that allows for the measurement of metabolic changes in a multicellular system using two different approaches: targeted and untargeted. Targeted studies are focused on a known number of defined metabolites. Untargeted metabolomics aims to capture all metabolites present in a sample. Different statistical approaches (e.g., uni- or multivariate statistics, machine learning) can be applied to extract useful and important information in both cases. This review aims to describe the role of metabolomics in forensic toxicology and in forensic medicine.

Simultaneous Water Droplet Formation and Sorting Using an Electric Field

2008 ◽  
Author(s):  
Byungwook Ahn ◽  
Rajagopal Panchapakesan ◽  
Kangsun Lee ◽  
Kwang W. Oh
Keyword(s):  
Electric Field ◽  
High Throughput ◽  
Biomedical Research ◽  
Water Droplet ◽  
Droplet Formation ◽  
Electrical Actuation ◽  
Microfluidic Technology ◽  
Droplet Sorting ◽  
Control Water

The droplet-based microfluidic technology has a potent high throughput platform for biomedical research and applications [1]. Recently, Link et al. showed that an electric field can be very useful to control water droplet in carrier oil [2]. In this research, simultaneous droplet formation and sorting has been demonstrated using an electric field, allowing very precise droplet sorting to different outlets depending on the electrical actuation.

High throughput technology: approaches of research in homogeneous and heterogeneous catalysis

Catalysis ◽  
2013 ◽  
pp. 172-215 ◽  
Author(s):  
Stephan A. Schunk ◽  
Natalia Böhmer ◽  
Cornelia Futter ◽  
Andreas Kuschel ◽  
Eko Prasetyo ◽  
...  
Keyword(s):  
Heterogeneous Catalysis ◽  
High Throughput ◽  
High Throughput Technology

Development of a dual-fluorescence reporter system for high-throughput screening of L-aspartate-α-decarboxylase

2020 ◽  
Vol 52 (12) ◽  
pp. 1420-1426
Author(s):  
Mingyue Fei ◽  
Xudan Mao ◽  
Yiyang Chen ◽  
Yalan Lu ◽  
Lin Wang ◽  
...  
Keyword(s):  
High Throughput ◽  
Industrial Production ◽  
High Throughput Screening ◽  
Relative Activity ◽  
Expression Level ◽  
Rapid Screening ◽  
Dual Fluorescence ◽  
Reporter System ◽  
The Cost ◽  
Chemical Synthesis Route

Abstract β-Alanine (3-aminopropionic acid) holds great potential in industrial application. It can be obtained through a chemical synthesis route, which is hazardous to the environment. It is well known that l-aspartate-α-decarboxylase (ADC) can convert l-aspartate to β-alanine in bacteria. However, due to the low activity of ADC, industrial production of β-alanine through the green biological route remains unclear. Thus, improving the activity of ADC is critical to reduce the cost of β-alanine production. In this study, we established a dual-fluorescence high-throughput system for efficient ADC screening. By measuring the amount of β-alanine and the expression level of ADC using two different fluorescence markers, we can rapidly quantify the relative activity of ADC variants. From a mutagenesis library containing 2000 ADC variants, we obtained a mutant with 33% increased activity. Further analysis revealed that mutations of K43R and P103Q in ADC significantly improved the yield of β-alanine produced by the whole-cell biocatalysis. Compared with the previous single-fluorescence method, our system can not only quantify the amount of β-alanine but also measure the expression level of ADC with different fluorescence, making it able to effectively screen out ADC variants with improved relative activity. The dual-fluorescence high-throughput system for rapid screening of ADC provides a good strategy for industrial production of β-alanine via the biological conversion route in the future.

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