scholarly journals Simple Method for Cutoff Point Identification In Descriptive High-Throughput Biological Studies

2021 ◽  
Author(s):  
Alexander Suvorov
Keyword(s):  
High Throughput ◽  
Rapid Development ◽  
Cutoff Point ◽  
Second Phase ◽  
Continuous Variables ◽  
Human Cerebral Cortex ◽  
Simple Method ◽  
Biological Studies ◽  
Mammalian Genes ◽  
Common Shape

Rapid development of high-throughput omics technologies generates an increasing interests in algorithms for cutoff point identification. Existing cutoff methods and tools identify cutoff points based on association of continuous variables with another variable, such as phenotype, disease state or treatment group. These approaches are not applicable for descriptive studies in which continuous variables are reported without known association with any biologically meaningful variables. The most common shape of the ranked distribution of continuous variables in high-throughput descriptive studies corresponds to a biphasic exponential/super-exponential curve, where the first phase includes big number of variables with values slowly growing with rank and the second phase includes smaller number of variables rapidly growing with rank. This study describes an easy algorithm to identify the boundary between these phases to be used as a cutoff point. The major assumption of that approach is that small number of variables with high values dominate biological system and determine its major processes and functions. This approach was tested on three different datasets: genes in the human cerebral cortex, mammalian genes sensitive to chemical exposures, and proteins expressed in human heart. In every case, the described cutoff identification method produced shortlists of variables (genes, proteins) highly relevant for dominant functions/pathways of the analyzed biological systems. Thus, our described method for cutoff identification may be used to prioritize variables for a focused functional analysis, in situations where other methods of dichotomization of data are inaccessible.

scholarly journals A simple method to co-purify genomic DNA, RNA, and proteins for functional studies

2018 ◽  
Author(s):  
Jian Jiang ◽  
Junfei Ma ◽  
Bin Liu ◽  
Ying Wang
Keyword(s):  
Gene Expression ◽  
Molecular Biology ◽  
High Throughput ◽  
Genomic Dna ◽  
Molecular Mechanisms ◽  
Rapid Development ◽  
Regulation Of Gene Expression ◽  
Robust Method ◽  
Simple Method ◽  
Functional Studies

AbstractUnderstanding the regulation of gene expression, from the epigenetic modifications on genomes to posttranscriptional and translational controls, are critical for elucidating molecular mechanisms underlying distinct phenotypes in biology. With the rapid development of Multi-Omics analyses, it is desirable to minimize sample variations by using DNA, RNA, and proteins co-purified from the same samples. Currently, most of the co-purification protocols rely on Tri Reagent (Trizol as a common representative) and require protein precipitation and dissolving steps, which render difficulties in experimental handling and high-throughput analyses. Here, we established a simple and robust method to minimize the precipitation steps and yield ready-to-use RNA and protein in solutions. This method can be applied to samples in small quantity, such as protoplasts. We demonstrated that the protoplast system equipped with this method may facilitate studies on viroid biogenesis. Given the ease and the robustness of this new method, it will have broad applications for plant research and other disciplines in molecular biology.

scholarly journals High-Throughput Phenotyping Methods for Breeding Drought-Tolerant Crops

2021 ◽  
Vol 22 (15) ◽  
pp. 8266
Author(s):  
Minsu Kim ◽  
Chaewon Lee ◽  
Subin Hong ◽  
Song Lim Kim ◽  
Jeong-Ho Baek ◽  
...  
Keyword(s):  
Drought Stress ◽  
High Throughput ◽  
Large Scale ◽  
Crop Yields ◽  
Plant Traits ◽  
Rapid Development ◽  
Plant Responses ◽  
Phenotypic Data ◽  
Agricultural Technologies ◽  
High Throughput Phenotyping

Drought is a main factor limiting crop yields. Modern agricultural technologies such as irrigation systems, ground mulching, and rainwater storage can prevent drought, but these are only temporary solutions. Understanding the physiological, biochemical, and molecular reactions of plants to drought stress is therefore urgent. The recent rapid development of genomics tools has led to an increasing interest in phenomics, i.e., the study of phenotypic plant traits. Among phenomic strategies, high-throughput phenotyping (HTP) is attracting increasing attention as a way to address the bottlenecks of genomic and phenomic studies. HTP provides researchers a non-destructive and non-invasive method yet accurate in analyzing large-scale phenotypic data. This review describes plant responses to drought stress and introduces HTP methods that can detect changes in plant phenotypes in response to drought.

DNA-Directed Patterning for Versatile Validation and Characterization of a Lipid-Based Nanoparticle Model of SARS-CoV-2

2021 ◽  
Author(s):  
Molly Kozminsky ◽  
Thomas Carey ◽  
Lydia L. Sohn
Keyword(s):  
High Throughput ◽  
Glass Substrate ◽  
Rapid Development ◽  
Neutralizing Antibody ◽  
S Protein ◽  
Biological Relevance ◽  
The Face ◽  
Great Control ◽  
Tetraspanin Cd63

Lipid-based nanoparticles have risen to the forefront of the COVID-19 pandemic—from encapsulation of vaccine components to modeling the virus, itself. Their rapid development in the face of the volatile nature of the pandemic requires high-throughput, highly flexible methods for characterization. DNA-directed patterning is a versatile method to immobilize and segregate lipid-based nanoparticles for subsequent analysis. DNA-directed patterning selectively conjugates oligonucleotides onto a glass substrate and then hybridizes them to complementary oligonucleotides tagged to the liposomes, thereby patterning them with great control and precision. The power of this method is demonstrated by characterizing a novel recapitulative lipid-based nanoparticle model of SARS-CoV-2 —S-liposomes— which present the SARS-CoV-2 spike (S) protein on their surfaces. Patterning of a mixture of S-liposomes and liposomes that display the tetraspanin CD63 into discrete regions of a substrate is used to show that ACE2 specifically binds to S-liposomes. Importantly, DNA-directed patterning of S-liposomes is used to verify the performance of a commercially available neutralizing antibody against the S protein. Ultimately, the introduction of S-liposomes to ACE2-expressing cells demonstrates the biological relevance of DNA-directed patterning. Overall, DNA-directed patterning enables a wide variety of custom assays for the characterization of any lipid-based nanoparticle.

scholarly journals ReactomeFIViz: the Reactome FI Cytoscape app for pathway and network-based data analysis

F1000Research ◽  
2014 ◽  
Vol 3 ◽  
pp. 146 ◽  
Author(s):  
Guanming Wu ◽  
Eric Dawson ◽  
Adrian Duong ◽  
Robin Haw ◽  
Lincoln Stein
Keyword(s):  
Experimental Data ◽  
Data Analysis ◽  
Graphical Models ◽  
High Throughput ◽  
Interaction Network ◽  
Large Data ◽  
Relevant Information ◽  
Data Sets ◽  
Data Types ◽  
Biological Studies

High-throughput experiments are routinely performed in modern biological studies. However, extracting meaningful results from massive experimental data sets is a challenging task for biologists. Projecting data onto pathway and network contexts is a powerful way to unravel patterns embedded in seemingly scattered large data sets and assist knowledge discovery related to cancer and other complex diseases. We have developed a Cytoscape app called “ReactomeFIViz”, which utilizes a highly reliable gene functional interaction network and human curated pathways from Reactome and other pathway databases. This app provides a suite of features to assist biologists in performing pathway- and network-based data analysis in a biologically intuitive and user-friendly way. Biologists can use this app to uncover network and pathway patterns related to their studies, search for gene signatures from gene expression data sets, reveal pathways significantly enriched by genes in a list, and integrate multiple genomic data types into a pathway context using probabilistic graphical models. We believe our app will give researchers substantial power to analyze intrinsically noisy high-throughput experimental data to find biologically relevant information.

scholarly journals HTSeq - A Python framework to work with high-throughput sequencing data

2014 ◽  
Author(s):  
Simon Anders ◽  
Paul Theodor Pyl ◽  
Wolfgang Huber
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Rapid Development ◽  
Differential Expression Analysis ◽  
Rna Seq ◽  
Sequencing Data ◽  
Standard Work ◽  
Data Formats ◽  
High Throughput Sequencing Data ◽  
Python Package

Motivation: A large choice of tools exists for many standard tasks in the analysis of high-throughput sequencing (HTS) data. However, once a project deviates from standard work flows, custom scripts are needed. Results: We present HTSeq, a Python library to facilitate the rapid development of such scripts. HTSeq offers parsers for many common data formats in HTS projects, as well as classes to represent data such as genomic coordinates, sequences, sequencing reads, alignments, gene model information, variant calls, and provides data structures that allow for querying via genomic coordinates. We also present htseq-count, a tool developed with HTSeq that preprocesses RNA-Seq data for differential expression analysis by counting the overlap of reads with genes. Availability: HTSeq is released as open-source software under the GNU General Public Licence and available from http://www-huber.embl.de/HTSeq or from the Python Package Index, https://pypi.python.org/pypi/HTSeq

scholarly journals MRBLES 2.0: High-throughput generation of chemically functionalized spectrally and magnetically encoded hydrogel beads using a simple single-layer microfluidic device

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Yinnian Feng ◽  
Adam K. White ◽  
Jamin B. Hein ◽  
Eric A. Appel ◽  
Polly M. Fordyce
Keyword(s):  
Functional Groups ◽  
High Throughput ◽  
Single Layer ◽  
Device Fabrication ◽  
Polymer Mixtures ◽  
Simple Method ◽  
Hydrogel Beads ◽  
Custom Made ◽  
Basic Biology ◽  
A Minor

AbstractThe widespread adoption of bead-based multiplexed bioassays requires the ability to easily synthesize encoded microspheres and conjugate analytes of interest to their surface. Here, we present a simple method (MRBLEs 2.0) for the efficient high-throughput generation of microspheres with ratiometric barcode lanthanide encoding (MRBLEs) that bear functional groups for downstream surface bioconjugation. Bead production in MRBLEs 2.0 relies on the manual mixing of lanthanide/polymer mixtures (each of which comprises a unique spectral code) followed by droplet generation using single-layer, parallel flow-focusing devices and the off-chip batch polymerization of droplets into beads. To streamline downstream analyte coupling, MRBLEs 2.0 crosslinks copolymers bearing functional groups on the bead surface during bead generation. Using the MRBLEs 2.0 pipeline, we generate monodisperse MRBLEs containing 48 distinct well-resolved spectral codes with high throughput (>150,000/min and can be boosted to 450,000/min). We further demonstrate the efficient conjugation of oligonucleotides and entire proteins to carboxyl MRBLEs and of biotin to amino MRBLEs. Finally, we show that MRBLEs can also be magnetized via the simultaneous incorporation of magnetic nanoparticles with only a minor decrease in the potential code space. With the advantages of dramatically simplified device fabrication, elimination of the need for custom-made equipment, and the ability to produce spectrally and magnetically encoded beads with direct surface functionalization with high throughput, MRBLEs 2.0 can be directly applied by many labs towards a wide variety of downstream assays, from basic biology to diagnostics and other translational research.

Research on City 3D Modeling and Application Based on Skyline

2012 ◽  
Vol 594-597 ◽  
pp. 2394-2397
Author(s):  
Jian Cui ◽  
Dong Ling Ma ◽  
Fei Cai
Keyword(s):  
Urban Design ◽  
Computer Technology ◽  
Traditional Method ◽  
3D Visualization ◽  
Rapid Development ◽  
Three Dimensional ◽  
Computer Software ◽  
Communications Technology ◽  
Digital City ◽  
Simple Method

With the rapid development of computer technology, communications technology, and other related technologies, the Digital City has become a hot topic of current research. The traditional method of constructing digital city based on ArcGis is very complex, the type of computer software that related is much more, and the interaction between the software is poor. For the traditional method of digital urban design is difficult to design and visualization effect is poor, this paper builds the techniques of campus apartment modeling based on the skyline combined specific examples of campus apartments, realizes three dimensional (3D) visualization and query and analysis functions of the campus apartment system and proposes a simple method of creating 3D landscape efficiently.

High-throughput proteomics and the fight against pathogens

2016 ◽  
Vol 12 (8) ◽  
pp. 2373-2384 ◽  
Author(s):  
Anita Horvatić ◽  
Josipa Kuleš ◽  
Nicolas Guillemin ◽  
Asier Galan ◽  
Vladimir Mrljak ◽  
...  
Keyword(s):  
Infectious Diseases ◽  
Animal Welfare ◽  
High Throughput ◽  
Protein Interactions ◽  
Rapid Development ◽  
Protein Protein Interactions ◽  
Major Threat ◽  
Host Pathogen ◽  
Pathogen Protein

Pathogens pose a major threat to human and animal welfare. Understanding the interspecies host–pathogen protein–protein interactions could lead to the development of novel strategies to combat infectious diseases through the rapid development of new therapeutics.

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