scholarly journals CoExp: A Web Tool for the Exploitation of Co-expression Networks

2021 ◽  
Vol 12 ◽  
Author(s):  
Sonia García-Ruiz ◽  
Ana L. Gil-Martínez ◽  
Alejandro Cisterna ◽  
Federico Jurado-Ruiz ◽  
Regina H. Reynolds ◽  
...  
Keyword(s):  
Web Application ◽  
Network Models ◽  
Software Tool ◽  
Cell Types ◽  
Brain Network ◽  
Data Sets ◽  
Mrna Levels ◽  
Cellular Specificity ◽  
R Packages ◽  
Highly Correlated

Gene co-expression networks are a powerful type of analysis to construct gene groupings based on transcriptomic profiling. Co-expression networks make it possible to discover modules of genes whose mRNA levels are highly correlated across samples. Subsequent annotation of modules often reveals biological functions and/or evidence of cellular specificity for cell types implicated in the tissue being studied. There are multiple ways to perform such analyses with weighted gene co-expression network analysis (WGCNA) amongst one of the most widely used R packages. While managing a few network models can be done manually, it is often more advantageous to study a wider set of models derived from multiple independently generated transcriptomic data sets (e.g., multiple networks built from many transcriptomic sources). However, there is no software tool available that allows this to be easily achieved. Furthermore, the visual nature of co-expression networks in combination with the coding skills required to explore networks, makes the construction of a web-based platform for their management highly desirable. Here, we present the CoExp Web application, a user-friendly online tool that allows the exploitation of the full collection of 109 co-expression networks provided by the CoExpNets suite of R packages. We describe the usage of CoExp, including its contents and the functionality available through the family of CoExpNets packages. All the tools presented, including the web front- and back-ends are available for the research community so any research group can build its own suite of networks and make them accessible through their own CoExp Web application. Therefore, this paper is of interest to both researchers wishing to annotate their genes of interest across different brain network models and specialists interested in the creation of GCNs looking for a tool to appropriately manage, use, publish, and share their networks in a consistent and productive manner.

scholarly journals Over-Generalizing About GC (Hypoxia): Pitfalls of Limiting Breadth of Experimental Systems and Analyses in Framing Informatics Conclusions

2021 ◽  
Vol 12 ◽  
Author(s):  
Mark R. Boothby ◽  
Ariel Raybuck ◽  
Sung Hoon Cho ◽  
Kristy R. Stengel ◽  
Volker H. Haase ◽  
...  
Keyword(s):  
B Cells ◽  
Cell Types ◽  
Germinal Centers ◽  
Nutrient Concentrations ◽  
Data Sets ◽  
Mrna Levels ◽  
Independent Evidence ◽  
Experimental Systems ◽  
Protein Immunization ◽  
Technical Features

Accumulating evidence suggests that many immune responses are influenced by local nutrient concentrations in addition to the programming of intermediary metabolism within immune cells. Humoral immunity and germinal centers (GC) are settings in which these factors are under active investigation. Hypoxia is an example of how a particular nutrient is distributed in lymphoid follicles during an antibody response, and how oxygen sensors may impact the qualities of antibody output after immunization. Using exclusively a bio-informatic analysis of mRNA levels in GC and other B cells, recent work challenged the concept that there is any hypoxia or that it has any influence. To explore this proposition, we performed new analyses of published genomics data, explored potential sources of disparity, and elucidated aspects of the apparently conflicting conclusions. Specifically, replicability and variance among data sets derived from different naïve as well as GC B cells were considered. The results highlight broader issues that merit consideration, especially at a time of heightened focus on scientific reports in the realm of immunity and antibody responses. Based on these analyses, a standard is proposed under which the relationship of new data sets should be compared to prior “fingerprints” of cell types and reported transparently to referees and readers. In light of independent evidence of diversity within and among GC elicited by protein immunization, avoidance of overly broad conclusions about germinal centers in general when experimental systems are subject to substantial constraints imposed by technical features also is warranted.

scholarly journals Design and Implementation of Reliability Analysis Tool using Real Time Data

2019 ◽  
Vol 8 (12) ◽  
pp. 3210-3213
Keyword(s):  
Real Time ◽  
Software Reliability ◽  
Web Application ◽  
Research Work ◽  
Software Tool ◽  
Security Level ◽  
Data Sets ◽  
Analysis Tool ◽  
Time Data ◽  
Design And Testing

To estimate the reliability of software numerous statistical methods are in practice. To accomplish the software reliability prediction in more accurate way there is a huge demand for data sets. The data sets that can be acquired as a result of testing the software can be used for predicting the reliability. The research work focuses on creating a layer of software design and testing method namely web software testing. The main purpose is to collect the erroneous data from real time. The reliability of software can be measured in different aspects like traffic handling capability when there are a greater number of users, the security level for cracking the passwords and the possibility of different combinations of errors that occurs when inputting the data. This proposed software tool will read the software description, and will generate test patterns according to the input types and collects testing results, predicting the software reliability in real time and suggesting the possible ways to improve the software. For designing purpose PHP for web application will be used to give the testing results.

scholarly journals Generalizing about GC (hypoxia): Dys- & Dat-Informatica Comment on “Germinal center B cells selectively oxidize fatty acids for energy while conducting minimal glycolysis”

2021 ◽  
Author(s):  
Mark R. Boothby ◽  
Ariel Raybuck ◽  
Sung Hoon Cho ◽  
Kristy R. Stengel ◽  
Scott Hiebert ◽  
...  
Keyword(s):  
B Cells ◽  
Germinal Center ◽  
Cell Types ◽  
Germinal Centers ◽  
Data Sets ◽  
Mrna Levels ◽  
Experimental Systems ◽  
Protein Immunization ◽  
Technical Features ◽  
Germinal Center B Cells

AbstractSteadily accumulating evidence supports the concept that the outputs of immune responses are influenced by local nutrient and metabolite conditions or concentrations, as well as by the molecular programming of intermediary metabolism within immune cells. Humoral immunity and germinal center reactions are one setting in which these factors are under active investigation. Hypoxia has been highlighted as one example of how a particular nutrient is distributed in primary and secondary follicles during an antibody response, and how its sensors could impact the qualities of antibody output after immunization. Based on a bio-informatic analysis of mRNA levels in germinal center and other B cells, recently published work challenges the concept that there is any hypoxia or that it has any influence. In this perspective, we perform new analyses of published genomics data to explore potential sources of disparity and elucidate aspects of what on the surface might seem to be conflicting conclusions. In particular, the replicability and variance among data sets derived from different naïve as well as germinal center B cells are considered. The results of the investigation highlight several broader issues that merit consideration, especially at a time of heightened focus on scientific reports in the realm of immunity and antibody responses. From one finding of this re-analysis, it is proposed that a standard should be expected in which the relationship of new data sets compared to prior “fingerprints” of cell types should be reported transparently to referees and readers. In light of the strong evidence for diversity in the constituencies within germinal centers elicited by protein immunization, it also is proposed that a core practice should be to avoid overly broad conclusions about germinal centers in general when experimental systems are subject to substantial constraints imposed by technical features.

Truck Weight Enforcement Measures of Effectiveness: Development and Software Application

1998 ◽  
Vol 1643 (1) ◽  
pp. 152-160 ◽  
Author(s):  
F. R. Hanscom ◽  
M. W. Goelzer
Keyword(s):  
Software Tool ◽  
Field Evaluation ◽  
Seasonal Effects ◽  
Data Sets ◽  
Activity Data ◽  
Software Application ◽  
Enforcement Effort ◽  
Measures Of Effectiveness ◽  
Truck Weight ◽  
Enforcement Activity

A software tool was developed to determine what is accomplished as the result of truck weight enforcement efforts. Traditionally applied measures (e.g., numbers of trucks weighed and citations issued) have simply provided indications of enforcement effort. These previously applied measures failed to provide results in terms of real enforcement objectives, such as deterring overweight trucks and minimizing pavement wear and tear. Consequently the need exists to develop and validate truck weight enforcement measures of effectiveness (MOE). MOEs were developed via a series of analytical procedures. They were subsequently validated in a comprehensive four-state field evaluation. Matched (weigh-in-motion) (WIM) data sets, collected under controlled baseline and enforcement conditions, were analyzed to determine the sensitivity of candidate MOEs to actual enforcement activity. Data collection conditions were controlled in order to avoid contamination from hour-of-day, day-of-week, and seasonal effects. The following MOEs, were validated on the basis of their demonstrated sensitivity to truck weight enforcement objectives and the presence of enforcement activity: (1) severity of overweight violations, (2) proportion of overweight trucks, (3) average equivalent single-axle load (ESAL), (4) excess ESALs, and (5) bridge formula violations. These measures are sensitive to legal load-limit compliance objectives of truck weight enforcement procedures as well as the potential for overweight trucks to produce pavement deterioration. The software User Guide that statistically compares calculated MOEs between observed enforcement conditions is described in this paper. The User Guide also allows users to conduct an automated pavement design life analysis estimating, the theoretical pavement-life effect resulting from the observed enforcement activity.

scholarly journals Software Benchmark—Classification Tree Algorithms for Cell Atlases Annotation Using Single-Cell RNA-Sequencing Data

2021 ◽  
Vol 12 (2) ◽  
pp. 317-334
Author(s):  
Omar Alaqeeli ◽  
Li Xing ◽  
Xuekui Zhang
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Classification Tree ◽  
Area Under The Curve ◽  
Data Sets ◽  
Sequencing Data ◽  
Single Cell Rna Sequencing ◽  
Tree Algorithms ◽  
R Packages

Classification tree is a widely used machine learning method. It has multiple implementations as R packages; rpart, ctree, evtree, tree and C5.0. The details of these implementations are not the same, and hence their performances differ from one application to another. We are interested in their performance in the classification of cells using the single-cell RNA-Sequencing data. In this paper, we conducted a benchmark study using 22 Single-Cell RNA-sequencing data sets. Using cross-validation, we compare packages’ prediction performances based on their Precision, Recall, F1-score, Area Under the Curve (AUC). We also compared the Complexity and Run-time of these R packages. Our study shows that rpart and evtree have the best Precision; evtree is the best in Recall, F1-score and AUC; C5.0 prefers more complex trees; tree is consistently much faster than others, although its complexity is often higher than others.

scholarly journals Advantages of using graph databases to explore chromatin conformation capture experiments

2021 ◽  
Vol 22 (S2) ◽  
Author(s):  
Daniele D’Agostino ◽  
Pietro Liò ◽  
Marco Aldinucci ◽  
Ivan Merelli
Keyword(s):  
Web Application ◽  
High Throughput Sequencing ◽  
Cell Types ◽  
Graph Database ◽  
Graph Databases ◽  
Sources Of Information ◽  
Chromosome Conformation ◽  
Wide Scale ◽  
User Friendly ◽  
Different Cell Types

Abstract Background High-throughput sequencing Chromosome Conformation Capture (Hi-C) allows the study of DNA interactions and 3D chromosome folding at the genome-wide scale. Usually, these data are represented as matrices describing the binary contacts among the different chromosome regions. On the other hand, a graph-based representation can be advantageous to describe the complex topology achieved by the DNA in the nucleus of eukaryotic cells. Methods Here we discuss the use of a graph database for storing and analysing data achieved by performing Hi-C experiments. The main issue is the size of the produced data and, working with a graph-based representation, the consequent necessity of adequately managing a large number of edges (contacts) connecting nodes (genes), which represents the sources of information. For this, currently available graph visualisation tools and libraries fall short with Hi-C data. The use of graph databases, instead, supports both the analysis and the visualisation of the spatial pattern present in Hi-C data, in particular for comparing different experiments or for re-mapping omics data in a space-aware context efficiently. In particular, the possibility of describing graphs through statistical indicators and, even more, the capability of correlating them through statistical distributions allows highlighting similarities and differences among different Hi-C experiments, in different cell conditions or different cell types. Results These concepts have been implemented in NeoHiC, an open-source and user-friendly web application for the progressive visualisation and analysis of Hi-C networks based on the use of the Neo4j graph database (version 3.5). Conclusion With the accumulation of more experiments, the tool will provide invaluable support to compare neighbours of genes across experiments and conditions, helping in highlighting changes in functional domains and identifying new co-organised genomic compartments.

Improvements for research data repositories: The case of text spam

2021 ◽  
pp. 016555152199863
Author(s):  
Ismael Vázquez ◽  
María Novo-Lourés ◽  
Reyes Pavón ◽  
Rosalía Laza ◽  
José Ramón Méndez ◽  
...  
Keyword(s):  
Web Application ◽  
Research Data ◽  
Data Sets ◽  
Data Repositories ◽  
Software Applications ◽  
Public Data ◽  
Protection Mechanisms ◽  
Experimental Protocols ◽  
Learning Research ◽  
Processing Steps

Current research has evolved in such a way scientists must not only adequately describe the algorithms they introduce and the results of their application, but also ensure the possibility of reproducing the results and comparing them with those obtained through other approximations. In this context, public data sets (sometimes shared through repositories) are one of the most important elements for the development of experimental protocols and test benches. This study has analysed a significant number of CS/ML ( Computer Science/ Machine Learning) research data repositories and data sets and detected some limitations that hamper their utility. Particularly, we identify and discuss the following demanding functionalities for repositories: (1) building customised data sets for specific research tasks, (2) facilitating the comparison of different techniques using dissimilar pre-processing methods, (3) ensuring the availability of software applications to reproduce the pre-processing steps without using the repository functionalities and (4) providing protection mechanisms for licencing issues and user rights. To show the introduced functionality, we created STRep (Spam Text Repository) web application which implements our recommendations adapted to the field of spam text repositories. In addition, we launched an instance of STRep in the URL https://rdata.4spam.group to facilitate understanding of this study.

scholarly journals Characterization and Regulation of Type A Endothelin Receptor Gene Expression in Bovine Luteal Cell Types

Endocrinology ◽  
1999 ◽  
Vol 140 (5) ◽  
pp. 2110-2116 ◽  
Author(s):  
Roni Mamluk ◽  
Nitzan Levy ◽  
Bo Rueda ◽  
John S. Davis ◽  
Rina Meidan
Keyword(s):  
Gene Expression ◽  
Receptor Gene ◽  
Cell Types ◽  
Cell Populations ◽  
Mrna Levels ◽  
Factor I ◽  
Receptor Mrna ◽  
Progesterone Production ◽  
Eta Receptor ◽  
Receptor Gene Expression

Abstract Our previous studies demonstrated that endothelin-1 (ET-1), a 21-amino acid vasoconstrictor peptide, has a paracrine regulatory role in bovine corpus luteum (CL). The peptide is produced within the gland where it inhibits progesterone production by acting via the selective type A endothelin (ETA) receptors. The present study was designed to characterize ETA receptor gene expression in different ovarian cell types and its hormonal regulation. ETA receptor messenger RNA (mRNA) levels were high in follicular cells as well as in CL during luteal regression. At this latter stage, high ETA receptor expression concurred with low prostaglandin F2α receptor mRNA. The ETA receptor gene was expressed by all three major cell populations of the bovine CL; i.e. small and large luteal cells, as well as in luteal endothelial cells. Among these various cell populations, the highest ETA receptor mRNA levels were found in endothelial cells. cAMP elevating agents, forskolin and LH, suppressed ETA receptor mRNA expression in luteinized theca cells (LTC). This inhibition was dose dependent and was evident already after 24 h of incubation. In luteinized granulosa cells (LGC), 10 and 100 ng/ml of insulin-like growth factor I and insulin (only at a concentration of 2000 ng/ml) markedly decreased ETA receptor mRNA levels. In both LGC and LTC there was an inverse relationship between ETA receptor gene expression and progesterone production; insulin (in LGC) and forskolin (in LTC) enhanced progesterone production while inhibiting ETA receptor mRNA levels. Our findings may therefore suggest that, during early stages of luteinization when peak levels of both LH and insulin-like growth factor I exist, the expression of ETA receptors in the gland are suppressed. This study demonstrates physiologically relevant regulatory mechanisms controlling ETA receptor gene expression and further supports the inhibitory role of ET-1 in CL function.

scholarly journals Profiling Bioactivity of the ToxCast Chemical Library Using BioMAP Primary Human Cell Systems

2009 ◽  
Vol 14 (9) ◽  
pp. 1054-1066 ◽  
Author(s):  
Keith A. Houck ◽  
David J. Dix ◽  
Richard S. Judson ◽  
Robert J. Kavlock ◽  
Jian Yang ◽  
...  
Keyword(s):  
Human Cell ◽  
Regulatory Networks ◽  
Cell Types ◽  
Environmental Chemicals ◽  
Data Sets ◽  
Chemical Library ◽  
Data Set ◽  
Cell Systems ◽  
Disease Biology ◽  
Nfκb Pathway

The complexity of human biology has made prediction of health effects as a consequence of exposure to environmental chemicals especially challenging. Complex cell systems, such as the Biologically Multiplexed Activity Profiling (BioMAP) primary, human, cell-based disease models, leverage cellular regulatory networks to detect and distinguish chemicals with a broad range of target mechanisms and biological processes relevant to human toxicity. Here the authors use the BioMAP human cell systems to characterize effects relevant to human tissue and inflammatory disease biology following exposure to the 320 environmental chemicals in the Environmental Protection Agency’s (EPA’s) ToxCast phase I library. The ToxCast chemicals were assayed at 4 concentrations in 8 BioMAP cell systems, with a total of 87 assay endpoints resulting in more than 100,000 data points. Within the context of the BioMAP database, ToxCast compounds could be classified based on their ability to cause overt cytotoxicity in primary human cell types or according to toxicity mechanism class derived from comparisons to activity profiles of BioMAP reference compounds. ToxCast chemicals with similarity to inducers of mitochondrial dysfunction, cAMP elevators, inhibitors of tubulin function, inducers of endoplasmic reticulum stress, or NFκB pathway inhibitors were identified based on this BioMAP analysis. This data set is being combined with additional ToxCast data sets for development of predictive toxicity models at the EPA. ( Journal of Biomolecular Screening 2009:1054-1066)

scholarly journals A data-driven neural network architecture for sentiment analysis

2019 ◽  
Vol 53 (1) ◽  
pp. 2-19 ◽  
Author(s):  
Erion Çano ◽  
Maurizio Morisio
Keyword(s):  
Neural Network ◽  
Sentiment Analysis ◽  
Network Architecture ◽  
Network Models ◽  
Data Sets ◽  
Feature Maps ◽  
Neural Network Architecture ◽  
Neural Network Models ◽  
Content Type ◽  
Max Pooling

Purpose The fabulous results of convolution neural networks in image-related tasks attracted attention of text mining, sentiment analysis and other text analysis researchers. It is, however, difficult to find enough data for feeding such networks, optimize their parameters, and make the right design choices when constructing network architectures. The purpose of this paper is to present the creation steps of two big data sets of song emotions. The authors also explore usage of convolution and max-pooling neural layers on song lyrics, product and movie review text data sets. Three variants of a simple and flexible neural network architecture are also compared. Design/methodology/approach The intention was to spot any important patterns that can serve as guidelines for parameter optimization of similar models. The authors also wanted to identify architecture design choices which lead to high performing sentiment analysis models. To this end, the authors conducted a series of experiments with neural architectures of various configurations. Findings The results indicate that parallel convolutions of filter lengths up to 3 are usually enough for capturing relevant text features. Also, max-pooling region size should be adapted to the length of text documents for producing the best feature maps. Originality/value Top results the authors got are obtained with feature maps of lengths 6–18. An improvement on future neural network models for sentiment analysis could be generating sentiment polarity prediction of documents using aggregation of predictions on smaller excerpt of the entire text.

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